CN118377330B - Remote control method of medical molecular sieve oxygenerator - Google Patents
Remote control method of medical molecular sieve oxygenerator Download PDFInfo
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- 239000002808 molecular sieve Substances 0.000 title claims abstract description 190
- URGAHOPLAPQHLN-UHFFFAOYSA-N sodium aluminosilicate Chemical compound [Na+].[Al+3].[O-][Si]([O-])=O.[O-][Si]([O-])=O URGAHOPLAPQHLN-UHFFFAOYSA-N 0.000 title claims abstract description 190
- 238000000034 method Methods 0.000 title claims abstract description 52
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims abstract description 322
- 229910052757 nitrogen Inorganic materials 0.000 claims abstract description 161
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 140
- 239000001301 oxygen Substances 0.000 claims abstract description 140
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 140
- 230000032683 aging Effects 0.000 claims abstract description 115
- 239000013598 vector Substances 0.000 claims abstract description 90
- 238000010521 absorption reaction Methods 0.000 claims abstract description 80
- 230000000694 effects Effects 0.000 claims abstract description 59
- 239000006096 absorbing agent Substances 0.000 claims abstract description 18
- 238000001179 sorption measurement Methods 0.000 claims description 140
- 230000008569 process Effects 0.000 claims description 14
- 238000013139 quantization Methods 0.000 claims description 14
- 238000009825 accumulation Methods 0.000 claims description 4
- 238000011002 quantification Methods 0.000 claims description 3
- 238000013528 artificial neural network Methods 0.000 claims description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 11
- 238000012549 training Methods 0.000 abstract description 6
- 238000002360 preparation method Methods 0.000 abstract description 3
- 239000007789 gas Substances 0.000 description 7
- 238000003062 neural network model Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 239000003463 adsorbent Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000006403 short-term memory Effects 0.000 description 2
- MYMOFIZGZYHOMD-UHFFFAOYSA-N Dioxygen Chemical compound O=O MYMOFIZGZYHOMD-UHFFFAOYSA-N 0.000 description 1
- 230000003213 activating effect Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 229910001882 dioxygen Inorganic materials 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000008929 regeneration Effects 0.000 description 1
- 238000011069 regeneration method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000036962 time dependent Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Classifications
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- C—CHEMISTRY; METALLURGY
- C01—INORGANIC CHEMISTRY
- C01B—NON-METALLIC ELEMENTS; COMPOUNDS THEREOF; METALLOIDS OR COMPOUNDS THEREOF NOT COVERED BY SUBCLASS C01C
- C01B13/00—Oxygen; Ozone; Oxides or hydroxides in general
- C01B13/02—Preparation of oxygen
- C01B13/0229—Purification or separation processes
- C01B13/0248—Physical processing only
- C01B13/0259—Physical processing only by adsorption on solids
- C01B13/0262—Physical processing only by adsorption on solids characterised by the adsorbent
- C01B13/0274—Other molecular sieve materials
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D11/00—Control of flow ratio
- G05D11/02—Controlling ratio of two or more flows of fluid or fluent material
- G05D11/13—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means
- G05D11/131—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring the values related to the quantity of the individual components
- G05D11/132—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring the values related to the quantity of the individual components by controlling the flow of the individual components
-
- C—CHEMISTRY; METALLURGY
- C01—INORGANIC CHEMISTRY
- C01B—NON-METALLIC ELEMENTS; COMPOUNDS THEREOF; METALLOIDS OR COMPOUNDS THEREOF NOT COVERED BY SUBCLASS C01C
- C01B2210/00—Purification or separation of specific gases
- C01B2210/0001—Separation or purification processing
- C01B2210/0009—Physical processing
- C01B2210/0014—Physical processing by adsorption in solids
- C01B2210/0015—Physical processing by adsorption in solids characterised by the adsorbent
- C01B2210/002—Other molecular sieve materials
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- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Organic Chemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Materials Engineering (AREA)
- Analytical Chemistry (AREA)
- Inorganic Chemistry (AREA)
- Separation Of Gases By Adsorption (AREA)
Abstract
The application relates to the field of oxygen preparation, in particular to a remote control method of a medical molecular sieve oxygenerator. The method comprises the following steps: collecting the flow velocity of an inlet and an outlet of an absorber and the oxygen concentration of the inlet and the outlet and the oxygen concentration of the sensor position; acquiring a side flow effect weight according to the difference between the oxygen concentration and the difference of the inlet flow velocity; establishing a coordinate system, acquiring a position vector of each sensor position, and determining an unbalanced vector of the nitrogen suction position based on the position vector and the edge flow effect weight; obtaining a local aging coefficient of the molecular sieve based on the local aging coefficient; obtaining the integral aging coefficient of the molecular sieve through the difference of the outlet oxygen concentration and the air oxygen concentration and the outlet flow velocity; acquiring the consumption proportion of the nitrogen absorption capacity and the oxygen purity offset; the medical molecular sieve oxygenerator is remotely controlled through a training network of the nitrogen absorption capacity consumption proportion, the oxygen purity offset, the molecular sieve local aging coefficient and the molecular sieve integral aging coefficient. The present application increases the overall oxygen production rate.
Description
Technical Field
The application relates to the field of oxygen preparation, in particular to a remote control method of a medical molecular sieve oxygenerator.
Background
The molecular sieve oxygenerator is a machine for producing oxygen through PSA (Pressure Swing Adsorption) pressure swing adsorption oxygenerator, absorbs nitrogen in compressed air through molecular sieves in adsorbers, and collects residual oxygen to achieve the purpose of producing oxygen, and is currently often used as oxygen supply equipment of modern hospitals.
Molecular sieve oxygenerator usually is equipped with two adsorbers and works alternately, and when one adsorber absorbs nitrogen, the other adsorber accomplishes the regeneration of adsorbent through pressure release, so continuously accomplish continuous oxygen supply repeatedly. The process involves a switching control problem of the adsorber, wherein a fixed air inflow rate is used and the oxygen concentration is detected at the adsorber gas outlet and the adsorber is replaced when the oxygen concentration is below a certain threshold. Firstly, the concentration of produced oxygen is uncontrollable, so that the concentration of the produced oxygen fluctuates; in addition, in the early stage of the new adsorber, the adsorber has stronger nitrogen absorbing capacity at the moment, so that the oxygen production speed can be increased by adopting the air inflow speed higher than the fixed air inflow speed. Therefore, the application solves the problem of slower oxygen production speed caused by adopting fixed air flow when the traditional molecular sieve oxygenerator is controlled.
Disclosure of Invention
In order to solve the technical problem of slower oxygen production speed, the application provides a medical molecular sieve oxygenerator remote control method, which adopts the following technical scheme:
the application provides a remote control method of a medical molecular sieve oxygenerator, which comprises the following steps:
Collecting inlet and outlet flow velocity and inlet and outlet oxygen concentration of the adsorber at each moment and oxygen concentration of different groups of different sensor positions;
Acquiring the side flow effect weight of each level of each layer according to the difference between the oxygen concentration and the inlet flow velocity at the same level at all times;
Establishing a coordinate system for each layer of molecular sieve, acquiring a position vector of each sensor position, and determining a nitrogen absorption position imbalance vector based on the position vector and the side flow effect weight; obtaining a molecular sieve local aging coefficient of each layer of molecular sieve according to the model and the elements of the position unbalance vector;
obtaining the integral aging coefficient of the molecular sieve through the difference of the outlet oxygen concentration and the air oxygen concentration at all times and the outlet flow velocity;
acquiring the nitrogen absorption capacity consumption proportion of the adsorption tower through the outlet oxygen concentration and the outlet flow rate, and acquiring the oxygen purity offset at each moment through the outlet oxygen concentration and the rated oxygen concentration; the neural network is trained to complete remote control on the medical molecular sieve oxygenerator through the nitrogen absorption capacity consumption proportion, the oxygen purity offset, the molecular sieve local aging coefficient and the molecular sieve integral aging coefficient.
In the scheme, aiming at the influence of the side flow effect existing in the adsorption tower on the aging degree of the adsorption tower, a sensor array is arranged in the adsorption tower, the change degree of the nitrogen absorbing capacity of different level positions along with time is calculated according to the distance grading of the sensor array from the inner wall of the stripping tower, the side flow effect weight is obtained, and the occurrence intensity of the side flow effect at different positions inside the adsorption tower is represented. And constructing a position vector according to the position of the sensor, combining the nitrogen absorption capacity and the side flow effect weight of the sensor, eliminating the influence of the side flow effect on the judgment of the aging degree of the local molecular sieve, constructing an unbalanced vector of the nitrogen absorption position, further obtaining the local aging coefficient of the molecular sieve, and representing the structural aging degree of the molecular sieve. And simultaneously, calculating the total nitrogen capacity and the real-time nitrogen absorption capacity of the adsorption tower according to the outlet oxygen concentration and the oxygen amount, taking the total nitrogen capacity of the adsorption tower as the integral aging coefficient of the molecular sieve, and representing the integral aging degree of the molecular sieve. And finally, calculating the nitrogen absorption capacity consumption proportion according to the total nitrogen capacity and the real-time nitrogen absorption capacity of the adsorption tower, calculating the oxygen purity offset according to the outlet oxygen concentration and the rated oxygen concentration, extracting the capacity consumption condition of the adsorption tower, adopting a neural network model to process data, and completing the control of the inlet flow rate of the adsorption tower. Because the influence of the side flow effect on the feature extraction is eliminated, the inlet flow velocity of the adsorption tower can be accurately controlled, the outlet oxygen concentration is further stabilized at the rated oxygen concentration, the fluctuation condition of the outlet oxygen concentration is reduced, and meanwhile, the faster inlet flow velocity can be adopted at the beginning stage of the adsorption tower, so that the overall oxygen production rate is improved.
In one embodiment, the adsorber has a plurality of groups of oxygen sensors, the number of groups being the number of molecular sieve layers plus one, and for each group of sensors, the sensor positions are classified into different classes according to their distance from the molecular sieve center position, the classes of sensor positions being in positive correlation with the distance from the molecular sieve center.
In one embodiment, the method for obtaining the side flow effect weight of each level of each layer according to the difference between the oxygen concentration and the inlet flow velocity at the same level at all times is as follows:
each layer of molecular sieve is arranged between the same group of sensors and the next group of sensors, and for each moment, the absolute value of the difference value of the oxygen concentration corresponding to the sensors at the positions of the two adjacent groups of sensors is used as the nitrogen absorption capacity value of the same sensor position of the molecular sieve between the two groups of sensors;
Acquiring the adsorption capacity attenuation of each level at each moment according to the difference of the nitrogen adsorption capacity values of all the sensor positions of each level of each layer of molecular sieve at adjacent moments and the difference of inlet flow velocity;
and obtaining the side flow effect weight of each grade according to the adsorption capacity attenuation amount of each grade at all times in the adsorption process of one round.
In one embodiment, the method for obtaining the adsorption capacity attenuation of each level at each moment according to the difference of the nitrogen adsorption capacity values of all the sensor positions of each level of each layer of molecular sieve at adjacent moments and the difference of the inlet flow rate is as follows:
The average value of the nitrogen absorption capacity values of all the sensor positions of the same level of each layer of molecular sieve at each moment is used as a real-time nitrogen absorption capacity quantization index of each layer of molecular sieve under the level; under the same level, recording the difference value of the real-time nitrogen absorption capacity quantization index at the current moment and the next moment as a first quantization difference value;
determining adsorption capacity attenuation according to the first quantized difference value and the inlet flow rate; the adsorption capacity attenuation amount and the first quantification difference value are in positive correlation, and the adsorption capacity attenuation amount and the inlet flow velocity are in negative correlation.
In one embodiment, the method for obtaining the side flow effect weight of each grade according to the adsorption capacity attenuation amount of each grade at all times in a round of adsorption process comprises the following steps:
In the adsorption process of one round, the adsorption capacity attenuation of each grade of each layer at all times is added and then is linearly normalized to be used as the side flow effect weight of each grade of each layer.
In one embodiment, a coordinate system is established for each layer of molecular sieve, a position vector of each sensor position is obtained, and a nitrogen absorption position imbalance vector is determined based on the position vector and the side flow effect weight; the method for obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the mode and the element of the position unbalance vector comprises the following steps:
For each layer of molecular sieve, taking the position of the sensor corresponding to the highest level as a coordinate origin, establishing a plane coordinate system by taking the cross section of the adsorption tower, and taking a vector from the coordinate origin as a starting point to each sensor position as an end point as a position vector;
combining each position vector at each moment with a nitrogen absorbing capacity value and an edge flow effect weight to obtain a nitrogen absorbing position vector, and obtaining a nitrogen absorbing position unbalanced vector through the nitrogen absorbing position vector;
And obtaining the local aging strength of the molecular sieve according to the module length of the unbalanced vector of the nitrogen absorption position, obtaining the local aging coefficient certainty according to the standard deviation of the unbalanced vector element of the nitrogen absorption position, and obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the local aging strength and the local aging coefficient certainty of the molecular sieve.
In one embodiment, the method for obtaining the nitrogen absorption position vector by combining each position vector at each moment with the nitrogen absorption capacity value and the edge flow effect weight and obtaining the nitrogen absorption position imbalance vector through the nitrogen absorption position vector comprises the following steps:
the product of the position vector and the nitrogen absorbing capacity value and the ratio of the product to the edge flow effect weight are used as the nitrogen absorbing position vector;
And adding all nitrogen absorption position vectors in each layer of molecular sieve at each moment to obtain a nitrogen absorption position imbalance vector.
In one embodiment, the method for obtaining the local aging strength of the molecular sieve according to the module length of the unbalanced vector of the nitrogen absorption position, obtaining the certainty factor of the local aging coefficient according to the standard deviation of the unbalanced vector element of the nitrogen absorption position, and obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the local aging strength and the certainty factor of the local aging coefficient of the molecular sieve comprises the following steps:
in the adsorption process of one round, taking the model length of the unbalanced vector of the nitrogen absorption position of each layer of molecular sieve at all times, and solving the average value, wherein the average value is used as the local aging strength of the molecular sieve;
For all unbalanced vectors of nitrogen absorption positions of each layer of molecular sieve, marking the standard deviation of all first element values as a first standard deviation, marking the standard deviation of all second element values as a second standard deviation, and marking the sum of the first standard deviation and the second standard deviation as a local aging coefficient determination degree;
Obtaining a local aging coefficient of the molecular sieve according to the local aging strength and the local aging coefficient certainty degree of the molecular sieve;
the local aging coefficient of the molecular sieve and the local aging strength of the molecular sieve are in positive correlation, and the local aging coefficient of the molecular sieve and the local aging coefficient definition are in negative correlation.
In one embodiment, the method for obtaining the integral aging coefficient of the molecular sieve through the difference of the outlet oxygen concentration, the air oxygen concentration and the outlet flow rate at all times is as follows:
Taking the reciprocal of the outlet oxygen concentration at each moment as the molecular weight of the outlet of the absorber, taking the reciprocal of the air oxygen concentration constant as the molecular weight of the inlet of the absorber, subtracting the molecular weight of the outlet of the absorber from the molecular weight of the inlet of the absorber, multiplying the molecular weight of the outlet of the absorber by the outlet flow rate at each moment, recording as the nitrogen adsorption quantity at each moment, summing the nitrogen adsorption quantities at all moments to obtain the total nitrogen capacity of the adsorption tower, and recording as the integral aging coefficient of the molecular sieve.
In one embodiment, the method for obtaining the nitrogen absorption capacity consumption proportion of the adsorption tower through the outlet oxygen concentration and the outlet flow rate and obtaining the oxygen purity offset of each moment through the outlet oxygen concentration and the rated oxygen concentration comprises the following steps:
Acquiring nitrogen adsorption quantity at each moment through outlet oxygen concentration and outlet flow rate, accumulating all nitrogen adsorption quantity from the beginning of adsorption to the current moment to be used as a first nitrogen accumulation value, and taking the ratio of the first nitrogen accumulation value to the total nitrogen capacity of the adsorption tower as the nitrogen adsorption capacity consumption proportion of the adsorption tower;
Presetting a rated oxygen concentration, making a difference between the outlet oxygen concentration and the rated oxygen concentration, and recording the difference as an oxygen purity offset at the current moment.
The beneficial effects of the invention are as follows:
Aiming at the influence of the side flow effect existing in the adsorption tower on the aging degree of the adsorption tower, a sensor array is arranged in the adsorption tower, the change degree of the nitrogen absorbing capacity of different grade positions along with time is calculated according to the distance grading of the sensor array from the inner wall of the stripping tower, the side flow effect weight is obtained, and the occurrence intensity of the side flow effect at different positions inside the adsorption tower is represented. And constructing a position vector according to the position of the sensor, combining the nitrogen absorption capacity and the side flow effect weight of the sensor, eliminating the influence of the side flow effect on the judgment of the aging degree of the local molecular sieve, constructing an unbalanced vector of the nitrogen absorption position, further obtaining the local aging coefficient of the molecular sieve, and representing the structural aging degree of the molecular sieve. And simultaneously, calculating the total nitrogen capacity and the real-time nitrogen absorption capacity of the adsorption tower according to the outlet oxygen concentration and the oxygen amount, taking the total nitrogen capacity of the adsorption tower as the integral aging coefficient of the molecular sieve, and representing the integral aging degree of the molecular sieve. And finally, calculating the nitrogen absorption capacity consumption proportion according to the total nitrogen capacity and the real-time nitrogen absorption capacity of the adsorption tower, calculating the oxygen purity offset according to the outlet oxygen concentration and the rated oxygen concentration, extracting the capacity consumption condition of the adsorption tower, adopting a neural network model to process data, and completing the control of the inlet flow rate of the adsorption tower. Because the influence of the side flow effect on the feature extraction is eliminated, the inlet flow velocity of the adsorption tower can be accurately controlled, the outlet oxygen concentration is further stabilized at the rated oxygen concentration, the fluctuation condition of the outlet oxygen concentration is reduced, and meanwhile, the faster inlet flow velocity can be adopted at the beginning stage of the adsorption tower, so that the overall oxygen production rate is improved.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for remotely controlling a medical molecular sieve oxygenerator according to an embodiment of the present application;
FIG. 2 is a graph showing the distribution of sensors in each layer of molecular sieve.
Detailed Description
In order to further describe the technical means and effects adopted by the application to achieve the preset aim, the following description refers to a specific implementation, structure, characteristics and effects of a medical molecular sieve oxygenerator remote control method according to the application, and the different "one embodiment" or "another embodiment" refers to the same embodiment. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
An embodiment of a remote control method for a medical molecular sieve oxygenerator:
the application provides a specific scheme of a medical molecular sieve oxygenerator remote control method, which is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a method for remotely controlling a medical molecular sieve oxygenerator according to an embodiment of the application is shown, the method includes the following steps:
and S001, collecting inlet and outlet flow rates and inlet and outlet oxygen concentration of the adsorber at each moment and oxygen concentration of different groups of different sensor positions.
In the embodiment, the adsorber is remotely controlled by remote monitoring of the molecular sieve oxygenerator, and the adsorber is replaced when appropriate, so that the adsorber efficiency is improved. Therefore, gas flow rate sensors and oxygen concentration sensors are arranged at the inlet and the outlet of an absorber of the molecular sieve oxygenerator; and simultaneously, a total of N groups of oxygen concentration sensors are arranged among each layer of molecular sieve, on the upper surface of the uppermost layer of molecular sieve and on the lower surface of the lowermost layer of molecular sieve.
Wherein N is the number of layers of the molecular sieve plus one, and for each group of sensors, the sensors are classified into different grades, the grade is larger as the distance from the center of the molecular sieve is closer, and the subsequent analysis is carried out on the sensors of different grades. The sensor placement location is noted as the sensor location.
The inlet flow rate, the outlet flow rate, the inlet oxygen concentration, and the outlet oxygen concentration are obtained by gas flow rate sensors and oxygen concentration sensors installed at the inlet and outlet of the adsorber. And acquiring the corresponding oxygen concentration of each sensor in each group, wherein the oxygen concentration and the inlet and outlet flow rates corresponding to the sensors are acquired once every preset time in the preparation process of each round of oxygen in the adsorber.
Preferably, in one embodiment of the present application, the molecular sieve filter layer of the molecular sieve oxygenerator is 8 layers, that is, N is 9, because the absorber is also called an adsorption tower, the molecular sieve is a tray of the adsorption tower, the section of the tray is circular, the sensor arrays are arranged in a square array, four corners of the square array are tightly attached to the wall of the adsorption tower, as shown in fig. 2, 4 sensors tightly attached to the inner wall of the adsorption tower are in the 1 st stage, 4 sensors second closest to the inner wall of the adsorption tower are in the 2 nd stage, and the central sensor is in the 3 rd stage, and all three stages are shared. During each round of adsorption, each sensor is collected once every 1 s. The gas flow rate sensor is an FA10 type glass rotameter, and the oxygen concentration sensor is an S4LFO2-25 oxygen gas detection sensor.
Thus, the gas flow rate and the oxygen concentration at different positions are obtained.
Step S002, obtaining the side flow effect weight of each level of each layer according to the difference between the oxygen concentration and the inlet flow velocity at the same level at all times.
Because the molecular sieve in the molecular sieve oxygenerator can slightly shake when compressed air passes through, adsorption particles in the molecular sieve can be caused to shake, collide and then be worn, so that the adsorption capacity of the molecular sieve is continuously changed, the control on the molecular sieve should be dynamically controlled along with the aging condition of the molecular sieve, the condition that the original control scheme is invalid due to the gradual aging of the molecular sieve is avoided, and the oxygen production capacity of the molecular sieve needs to be evaluated in real time. In this embodiment, the current adsorption capacity of the adsorption tower is determined by using the oxygen production data of the current adsorption tower.
Each sensor obtains R data, i.e., R time instants, during a round of adsorber operation.
Because of the influence of the side flow effect, more fluid flows through the edge positions of the molecular sieve generally, so that the side flow effect can interfere with the comparison result when judging the aging condition of the molecular sieve through the nitrogen absorption capacity of different positions of the molecular sieve. The side stream effect is a well-known technique in the field of adsorption equipment and will not be described in detail.
For the nth layer of molecular sieves, it is between the n+1th and nth sets of sensors; for each moment, the absolute value of the difference of the oxygen concentration corresponding to the sensors of two adjacent groups of identical sensor positions is used as the nitrogen absorption capacity value of the molecular sieve at the position.
Because of the side flow effect, the molecular sieves close to the sensor position of the inner wall of the absorber flow more at the same time, so that the nitrogen absorbing capacity of the molecular sieves at the edge position is consumed more quickly, and the time-dependent change strength of the nitrogen absorbing capacities of the molecular sieves at different grades at the same layer of molecular sieves can be used as a quantification standard of the side flow effect in the molecular sieves at different layers in the adsorption tower.
And obtaining the adsorption capacity attenuation of each grade at each moment according to the difference of the nitrogen adsorption capacity values of all the sensor positions of each grade of each layer of molecular sieve at adjacent moments and the difference of the inlet flow velocity.
For each grade, the adsorption capacity attenuation of each grade at each moment and the difference of the nitrogen adsorption capacity values of each layer of molecular sieve at the same grade and all sensor positions at adjacent moment are in positive correlation, and the adsorption capacity attenuation of each grade at each moment and the inlet flow rate at each moment are in negative correlation.
Preferably, in one embodiment of the present application, the average value of the nitrogen absorption capacity values of all the sensor positions of the same level of each layer of molecular sieve at each moment is calculated as the real-time nitrogen absorption capacity quantization index of each layer of molecular sieve under the level; and under the same grade, recording the difference value of the real-time nitrogen absorption capacity quantization index at the current moment and the next moment as a first quantization difference value, and taking the ratio of the first quantization difference value to the inlet flow rate at the current moment as the adsorption capacity attenuation at the current moment.
Preferably, in one embodiment of the present application, the average value of the nitrogen absorption capacity values of all the sensor positions of the same level of each layer of molecular sieve at each moment is calculated as the real-time nitrogen absorption capacity quantization index of each layer of molecular sieve under the level; and under the same grade, recording the difference value of the real-time nitrogen absorption capacity quantization index at the current moment and the next moment as a first quantization difference value, and taking the difference value of the first quantization difference value and the inlet flow rate at the current moment as the adsorption capacity attenuation quantity at the current moment.
The difference from the inlet flow rate is that the adsorption tower adopts a variable inlet flow rate in the embodiment, and the inlet flow rate can cause the difference of the oxygen concentration of the sensor to change, so that the influence of the inlet flow rate is eliminated.
It should be noted that, positive correlation indicates that one variable grows, the other variable also grows, the directions of the two variable changes are the same, and when one variable changes from big to small or from small to big, the other variable also changes from big to small or from small to big; the specific relation can be multiplication relation, addition relation, exponential function idempotent and the like, and is determined by practical application, and the application is not particularly limited.
It should be noted that, the negative correlation indicates that one variable increases, the other variable decreases, and the directions of the two variable changes are opposite, when one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small; the specific relationship may be a ratio relationship, a subtraction relationship, etc., and is determined by practical application, and the present application is not particularly limited.
In the adsorption process of one round, each grade of each layer acquires a plurality of adsorption capacity attenuation amounts, and the side flow effect weight of each grade of each layer and all adsorption capacity attenuation amounts form a positive correlation.
Preferably, in one embodiment of the present application, the adsorption capacity attenuation amount of each level of each layer at all times is added and then linearly normalized as the side flow effect weight of each level of each layer.
Preferably, in one embodiment of the present application, the maximum and minimum values of the product of the adsorption capacity attenuation amounts of each level of each layer at all times are normalized as the edge flow effect weight of each level of each layer.
The greater the adsorption capacity attenuation of each level, the greater the edge flow effect weight corresponding to each level, and the higher the edge flow effect weight of the lower level than the edge flow effect weight of the higher level, the more serious the edge flow effect of the layer.
Thus, the side stream effect weight of each level of each layer is obtained.
Step S003, a coordinate system is established for each layer of molecular sieve, a position vector of each sensor position is obtained, and an unbalanced vector of the nitrogen absorption position is determined based on the position vector; and obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the modulus and the element of the position unbalance vector.
And further analyzing the aging degree of the adsorption tower on the basis of the side flow effect weight. Aging of the adsorption tower is divided into integral aging and local aging, wherein integral aging refers to aging caused by reduction of the integral efficiency of the adsorbent of the adsorption tower; the local aging refers to local pulverization caused by the impact of air flow from an air inlet on the adsorption tower, so that the efficiency of the adsorption tower is reduced.
For each layer of molecular sieve, the position of the sensor corresponding to the highest level is taken as the origin of coordinates, a plane coordinate system is established by taking the cross section of the adsorption tower, and a vector from the origin of coordinates to the position of each sensor is taken as a position vector.
And obtaining a nitrogen absorption position vector according to the combination of each position vector at each moment and the nitrogen absorption capacity value and the edge flow effect weight.
Preferably, in one embodiment of the present application, a ratio of a product of the position vector and the nitrogen absorbing capacity value to the edge flow effect weight is taken as the nitrogen absorbing position vector.
The product of the position vector and the nitrogen absorbing capacity value is the multiplication of each number in the position vector and the nitrogen absorbing capacity value, and the ratio of the position vector to the side flow effect weight is the ratio of each number in the vector to the side flow effect weight.
The position vector represents the azimuth, the difference value of the oxygen concentration represents the nitrogen absorbing capacity, the vector obtained by integrating the position vector and the nitrogen absorbing capacity can represent the size of the nitrogen absorbing capacity of different positions of the molecular sieve, further, the spatial unbalance condition of the nitrogen absorbing capacity of the molecular sieve can be directly reflected by comparing different nitrogen absorbing position vectors, and meanwhile, the nitrogen absorbing position vector is adjusted through the side flow effect weight, so that the influence of the side flow effect on the judgment of the spatial unbalance condition of the nitrogen absorbing capacity is eliminated.
Further analysis, besides the difference of local nitrogen absorption capacity caused by side flow effect and local aging of the molecular sieve, the imbalance of local nitrogen absorption capacity in space position caused by the turbulence of the airflow of the adsorption tower in a short time can also be caused.
And adding all nitrogen absorption position vectors in each layer of molecular sieve at each moment to complete the comparison of different nitrogen absorption position vectors to obtain a nitrogen absorption position imbalance vector, wherein if the addition of all the nitrogen absorption position vectors is 0, the spatial balance is represented, and if the addition of all the nitrogen absorption position vectors is not 0, namely the nitrogen absorption position imbalance vector appears, the spatial imbalance condition of the nitrogen absorption capacity of the molecular sieve is reflected.
In the adsorption process of one round, the unbalanced vector of the nitrogen absorption position of each layer of molecular sieve at all times is taken as the modulus length and the average value, and the average value is taken as the local aging strength of the molecular sieve, so that the spatial unbalanced strength of the nitrogen absorption capacity of the molecular sieve is represented.
For all nitrogen uptake position imbalance vectors of each layer of molecular sieve, the value of the first element is recorded as the first standard deviation, the value of the second element is recorded as the second standard deviation, the sum of the first standard deviation and the second standard deviation is recorded as the local aging coefficient certainty, the smaller the value is indicative of the stability of the nitrogen uptake capacity spatial imbalance intensity, the more the nitrogen uptake capacity spatial imbalance intensity is caused by structural damage of the molecular sieve, and not caused by short-time airflow flow imbalance.
And determining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the local aging strength and the local aging coefficient certainty of the molecular sieve of each layer of molecular sieve.
The local aging coefficient of the molecular sieve and the local aging strength of the molecular sieve are in positive correlation, and the local aging coefficient of the molecular sieve and the local aging coefficient definition are in negative correlation.
Preferably, in one embodiment of the present application, the ratio of the local aging strength of the molecular sieve to the certainty of the local aging coefficient is used as the local aging coefficient of the molecular sieve.
Preferably, in one embodiment of the present application, the difference between the local aging strength of the molecular sieve and the certainty of the local aging coefficient is used as the local aging coefficient of the molecular sieve.
Based on the obtained local aging coefficient of the molecular sieve, the side flow effect and the influence of transient turbulent airflow in the adsorption tower are removed, and the local aging condition of each layer of molecular sieve is accurately represented.
Thus, the local aging coefficient of the molecular sieve of each layer of molecular sieve is obtained.
And S004, obtaining the integral aging coefficient of the molecular sieve through the outlet oxygen concentration at all times, the difference of the air oxygen concentration and the outlet flow rate.
In the embodiment, the total nitrogen capacity of the adsorption tower is used for representing the overall aging degree of the molecular sieve of the adsorption tower, and the smaller the total nitrogen capacity is, the more serious the overall aging is. The inverse of the outlet oxygen concentration at each moment is used as the molecular weight of the outlet of the absorber, the inverse of the air oxygen concentration constant is used as the molecular weight of the inlet of the absorber, the molecular weight of the outlet of the absorber is subtracted from the molecular weight of the inlet of the absorber, the outlet flow rate at each moment is multiplied, the nitrogen adsorption quantity at each moment is recorded, the nitrogen adsorption quantity at all moments is summed to obtain the total nitrogen capacity of the adsorption tower, and the total nitrogen capacity is recorded as the integral aging coefficient of the molecular sieve.
In the present embodiment, the air oxygen concentration constant=0.21.
The total amount of oxygen in the gas at the inlet of the adsorption tower is almost unchanged, so that the reciprocal of the concentration of oxygen represents the relative size of the molecular number in the corresponding gas, the difference is then accumulated with the outlet flow rate, and the value represents the total amount of nitrogen adsorbed by the adsorption tower at each moment. And then taking each moment as an index for summing the total amount of the nitrogen to be adsorbed, wherein the total amount of the nitrogen can be contained in the adsorption tower when the adsorption tower is used for carrying out the adsorption of the round, and the smaller the total amount of the nitrogen can be contained in the adsorption tower, the more serious the overall aging degree of the nitrogen is.
Thus, the integral aging coefficient of the molecular sieve is obtained.
Step S005, obtaining the nitrogen absorption capacity consumption proportion of the adsorption tower through the outlet oxygen concentration and the outlet flow rate, and obtaining the oxygen purity offset at each moment through the outlet oxygen concentration and the rated oxygen concentration; the medical molecular sieve oxygenerator is remotely controlled through a training network of the nitrogen absorption capacity consumption proportion, the oxygen purity offset, the molecular sieve local aging coefficient and the molecular sieve integral aging coefficient.
After the aging characteristics of the adsorption tower are extracted, the adsorption capacity of the adsorption tower to nitrogen can be judged according to the aging degree of the adsorption tower, and then the corresponding optimal inlet flow rate can be set under the condition that the nitrogen adsorption capacity of the adsorption tower is in different consumption, so that oxygen can be produced at the maximum speed while the oxygen is kept in the specified purity. This embodiment uses an LSTM (long short term memory Long Short Term Memory) network to obtain the optimal inlet flow rate.
When the adsorption tower of the current round works, the outlet oxygen concentration and the outlet flow velocity are recorded in real time, so that the real-time nitrogen adsorption quantity can be obtained, and the total nitrogen capacity of the adsorption tower is obtained by accumulating the nitrogen adsorption quantity from the beginning to the current moment, namely the nitrogen adsorption capacity consumption proportion of the adsorption tower.
And (3) for the current moment, the difference value is made between the outlet oxygen concentration and the rated oxygen concentration, and the difference value is recorded as the oxygen purity offset of the current moment, so that the influence of the current inlet flow rate on the oxygen purity can be judged in real time, and the inlet flow rate is further finely adjusted to ensure that the outlet oxygen concentration reaches the standard. In this example, the oxygen concentration takes an empirical value of 0.932.
Further, the molecular sieve machine is obtained by a technician controlling the flow rate in real time to obtain a data set. And operating the flow rate of the adsorption tower by a technician to perform first-round oxygen generation to obtain data serving as initial data, and calculating the local aging coefficients of all molecular sieves and the integral aging coefficient of one molecular sieve of the adsorption tower according to the first-round data. And calculating the nitrogen absorption capacity consumption proportion and the oxygen purity offset at the current moment when oxygen is produced in the next round, wherein the two characteristic values, all the local aging coefficients of the molecular sieves in the previous round and the total aging coefficient of the molecular sieve are N+3 characteristic values to form a group of training data. One set of data is available at each time from the second round of oxygen production, the sets of data comprising a training data set.
Further, the training data set is taken as input, the LSTM neural network model is taken as a calculation model, the activating function is an RLU function, the optimizer is a Adma optimizer, the output value is recorded as the inlet control flow rate at the next moment, the loss function is a mean square error function, and the output is the trained LSTM neural network model. The training process of LSTM neural network models is well known in the art.
And finally, calculating a local aging coefficient of the molecular sieve and an overall aging coefficient of the molecular sieve according to operation data of a round of operation data on the adsorption tower during control, calculating a nitrogen absorption capacity consumption proportion and an oxygen purity offset at the current moment, inputting a trained LSTM neural network model as a group of input data at the current moment, and outputting an inlet control flow rate at the next moment for controlling an inlet flow rate of the adsorber at the next moment.
The molecular oxygenerator is controlled by controlling the flow rate, so that the concentration of produced oxygen is stable and controllable, and the higher air inflow speed can be adopted in the early stage of new adsorber exchange, so that the oxygen production speed is improved while the oxygen production purity is ensured; further, the rated oxygen concentration and the lowest inlet flow rate are set through the remote terminal, and when the inlet flow rate of the oxygenerator is smaller than the lowest inlet flow rate, the adsorption tower is automatically switched, so that the remote control of the molecular oxygenerator is completed.
It should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application and are intended to be included within the scope of the application.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments.
Claims (8)
1. The remote control method of the medical molecular sieve oxygenerator is characterized by comprising the following steps of:
Collecting inlet and outlet flow velocity and inlet and outlet oxygen concentration of the adsorber at each moment and oxygen concentration of different groups of different sensor positions;
Acquiring the side flow effect weight of each level of each layer according to the difference between the oxygen concentration and the inlet flow velocity at the same level at all times;
Establishing a coordinate system for each layer of molecular sieve, acquiring a position vector of each sensor position, and determining a nitrogen absorption position imbalance vector based on the position vector and the side flow effect weight; obtaining a molecular sieve local aging coefficient of each layer of molecular sieve according to the model and the elements of the position unbalance vector;
obtaining the integral aging coefficient of the molecular sieve through the difference of the outlet oxygen concentration and the air oxygen concentration at all times and the outlet flow velocity;
Acquiring the nitrogen absorption capacity consumption proportion of the adsorption tower through the outlet oxygen concentration and the outlet flow rate, and acquiring the oxygen purity offset at each moment through the outlet oxygen concentration and the rated oxygen concentration; the neural network is trained through the nitrogen absorption capacity consumption proportion, the oxygen purity offset, the molecular sieve local aging coefficient and the molecular sieve integral aging coefficient to complete remote control on the medical molecular sieve oxygenerator;
the method for obtaining the side flow effect weight of each level of each layer according to the difference between the oxygen concentration and the inlet flow velocity at the same level at all times comprises the following steps:
each layer of molecular sieve is arranged between the same group of sensors and the next group of sensors, and for each moment, the absolute value of the difference value of the oxygen concentration corresponding to the sensors at the positions of the two adjacent groups of sensors is used as the nitrogen absorption capacity value of the same sensor position of the molecular sieve between the two groups of sensors;
Acquiring the adsorption capacity attenuation of each level at each moment according to the difference of the nitrogen adsorption capacity values of all the sensor positions of each level of each layer of molecular sieve at adjacent moments and the difference of inlet flow velocity;
acquiring the side flow effect weight of each grade according to the adsorption capacity attenuation amount of each grade at all times in one round of adsorption process;
Establishing a coordinate system for each layer of molecular sieve, acquiring a position vector of each sensor position, and determining a nitrogen absorption position imbalance vector based on the position vector and the side flow effect weight; the method for obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the mode and the element of the position unbalance vector comprises the following steps:
For each layer of molecular sieve, taking the position of the sensor corresponding to the highest level as a coordinate origin, establishing a plane coordinate system by taking the cross section of the adsorption tower, and taking a vector from the coordinate origin as a starting point to each sensor position as an end point as a position vector;
combining each position vector at each moment with a nitrogen absorbing capacity value and an edge flow effect weight to obtain a nitrogen absorbing position vector, and obtaining a nitrogen absorbing position unbalanced vector through the nitrogen absorbing position vector;
And obtaining the local aging strength of the molecular sieve according to the module length of the unbalanced vector of the nitrogen absorption position, obtaining the local aging coefficient certainty according to the standard deviation of the unbalanced vector element of the nitrogen absorption position, and obtaining the local aging coefficient of the molecular sieve of each layer of molecular sieve according to the local aging strength and the local aging coefficient certainty of the molecular sieve.
2. The method of claim 1, wherein the plurality of groups of oxygen sensors are provided in the adsorber, the number of groups being one more than the number of layers of the molecular sieve, and for each group of sensors, the sensor positions are classified into different classes according to the distance from the sensor position to the center of the molecular sieve, the classes of the sensor positions being in positive correlation with the distance from the center of the molecular sieve.
3. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 1, wherein the method for obtaining the adsorption capacity attenuation of each level at each moment according to the difference of the nitrogen adsorption capacity values of all the sensor positions of each level of each layer of molecular sieve at adjacent moments and the difference of inlet flow rates is as follows:
The average value of the nitrogen absorption capacity values of all the sensor positions of the same level of each layer of molecular sieve at each moment is used as a real-time nitrogen absorption capacity quantization index of each layer of molecular sieve under the level; under the same level, recording the difference value of the real-time nitrogen absorption capacity quantization index at the current moment and the next moment as a first quantization difference value;
determining adsorption capacity attenuation according to the first quantized difference value and the inlet flow rate; the adsorption capacity attenuation amount and the first quantification difference value are in positive correlation, and the adsorption capacity attenuation amount and the inlet flow velocity are in negative correlation.
4. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 1, wherein the method for obtaining the side flow effect weight of each grade according to the adsorption capacity attenuation amount of each grade at all times in a round of adsorption process is as follows:
In the adsorption process of one round, the adsorption capacity attenuation of each grade of each layer at all times is added and then is linearly normalized to be used as the side flow effect weight of each grade of each layer.
5. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 1, wherein the method for obtaining the nitrogen absorption position vector by combining each position vector at each moment with the nitrogen absorption capacity value and the edge flow effect weight and obtaining the nitrogen absorption position imbalance vector through the nitrogen absorption position vector is as follows:
the product of the position vector and the nitrogen absorbing capacity value and the ratio of the product to the edge flow effect weight are used as the nitrogen absorbing position vector;
And adding all nitrogen absorption position vectors in each layer of molecular sieve at each moment to obtain a nitrogen absorption position imbalance vector.
6. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 1, wherein the method for obtaining the local aging strength of the molecular sieve according to the modular length of the unbalanced vector of the nitrogen absorption position, obtaining the certainty of the local aging coefficient according to the standard deviation of the unbalanced vector element of the nitrogen absorption position, and obtaining the local aging coefficient of the molecular sieve of each layer according to the local aging strength and the certainty of the local aging coefficient of the molecular sieve is as follows:
in the adsorption process of one round, taking the model length of the unbalanced vector of the nitrogen absorption position of each layer of molecular sieve at all times, and solving the average value, wherein the average value is used as the local aging strength of the molecular sieve;
For all unbalanced vectors of nitrogen absorption positions of each layer of molecular sieve, marking the standard deviation of all first element values as a first standard deviation, marking the standard deviation of all second element values as a second standard deviation, and marking the sum of the first standard deviation and the second standard deviation as a local aging coefficient determination degree;
Obtaining a local aging coefficient of the molecular sieve according to the local aging strength and the local aging coefficient certainty degree of the molecular sieve;
the local aging coefficient of the molecular sieve and the local aging strength of the molecular sieve are in positive correlation, and the local aging coefficient of the molecular sieve and the local aging coefficient definition are in negative correlation.
7. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 2, wherein the method for obtaining the integral aging coefficient of the molecular sieve through the difference of the outlet oxygen concentration and the air oxygen concentration at all times and the outlet flow rate is as follows:
Taking the reciprocal of the outlet oxygen concentration at each moment as the molecular weight of the outlet of the absorber, taking the reciprocal of the air oxygen concentration constant as the molecular weight of the inlet of the absorber, subtracting the molecular weight of the outlet of the absorber from the molecular weight of the inlet of the absorber, multiplying the molecular weight of the outlet of the absorber by the outlet flow rate at each moment, recording as the nitrogen adsorption quantity at each moment, summing the nitrogen adsorption quantities at all moments to obtain the total nitrogen capacity of the adsorption tower, and recording as the integral aging coefficient of the molecular sieve.
8. The method for remotely controlling a medical molecular sieve oxygenerator according to claim 1, wherein the method for obtaining the nitrogen absorption capacity consumption ratio of the adsorption tower through the outlet oxygen concentration and the outlet flow rate and obtaining the oxygen purity offset of each moment through the outlet oxygen concentration and the rated oxygen concentration is as follows:
Acquiring nitrogen adsorption quantity at each moment through outlet oxygen concentration and outlet flow rate, accumulating all nitrogen adsorption quantity from the beginning of adsorption to the current moment to be used as a first nitrogen accumulation value, and taking the ratio of the first nitrogen accumulation value to the total nitrogen capacity of the adsorption tower as the nitrogen adsorption capacity consumption proportion of the adsorption tower;
Presetting a rated oxygen concentration, making a difference between the outlet oxygen concentration and the rated oxygen concentration, and recording the difference as an oxygen purity offset at the current moment.
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| US4916630A (en) * | 1988-09-30 | 1990-04-10 | The United States Of America As Represented By The Secretary Of The Air Force | Bed tester for molecular sieve oxygen concentrator |
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| US9014858B2 (en) * | 2008-09-30 | 2015-04-21 | Rockwell Automation Technologies, Inc. | Energy optimizer for dehydrating biofuels through distillation towers and molecular sieves |
| US8702841B2 (en) * | 2012-04-17 | 2014-04-22 | Inogen, Inc. | Adsorber replacement notification for a portable gas concentrator |
| CA2944040C (en) * | 2014-03-28 | 2022-06-21 | Caire Inc. | Controlling oxygen concentrator timing cycle based on flow rate of oxygen output |
| CA3003720C (en) * | 2015-10-30 | 2023-10-17 | Richard Givens | Oxygen concentrating self-rescuer device |
| US10478770B2 (en) * | 2017-12-21 | 2019-11-19 | Air Products And Chemicals, Inc. | Separation process and apparatus for light noble gas |
| CN112919420B (en) * | 2020-12-30 | 2022-06-10 | 南京瑞杨医用科技有限公司 | Medical molecular sieve oxygen generator system |
| CN114906814A (en) * | 2022-05-07 | 2022-08-16 | 西南化工研究设计院有限公司 | Oxygen-making molecular sieve and pressure swing adsorption oxygen-making method |
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