WO2018232930A1

WO2018232930A1 - Intelligent monitoring system and method for industrial production equipment

Info

Publication number: WO2018232930A1
Application number: PCT/CN2017/097762
Authority: WO
Inventors: 杜光东
Original assignee: 深圳市盛路物联通讯技术有限公司
Priority date: 2017-06-23
Filing date: 2017-08-17
Publication date: 2018-12-27
Also published as: CN107272619A

Abstract

An intelligent monitoring method and system for industrial production equipment, the method comprising: collecting real time production data of industrial production equipment (S1); obtaining the real time production state of the industrial production equipment (S2); generating an adjustment instruction (S3); simulating the execution of the adjustment instruction, and outputting simulation production data (S4); comparing the simulation production data of the industrial production equipment to the real time production data, and obtaining a fluctuation value between the simulation production data of the industrial production equipment and the real time production data (S5); determining the position relation of the fluctuation value in a preset fluctuation range, and issuing a corresponding feedback signal according to the position relation (S6); and adjusting the real time production state of the industrial production equipment online by means of the adjustment instruction according to the feedback signal, or modifying the adjustment instruction according to the feedback signal (S7). With the described method, the production state of industrial production equipment may be monitored in real time, and the reasonableness of a control instruction may be determined by simulating the execution of the instruction, thereby improving the effect of monitoring.

Description

Intelligent monitoring system and method for industrial production equipment

Technical field

The invention relates to the technical field of equipment supervision, in particular to an intelligent monitoring system and method for industrial production equipment.

Background technique

With the development of the times and the advancement of science and technology, intelligent control technology has been adopted in various fields. Especially in the process of industrial production, a one-stop production mode is often adopted, and in the process of industrial production equipment operation, it is important to The core equipment is monitored in real time to ensure the normal operation of the entire production line; in the prior art, most of the ordinary monitoring systems are installed - TV monitoring, and the TV monitoring system is mainly composed of front-end monitoring equipment, transmission equipment, back-end storage, control and display. The device is composed of five parts, wherein the back-end device can be further divided into a central control device and a sub-control device. The front and back devices have multiple configurations, and the connections between them (also referred to as transmission systems) can be implemented in a variety of ways, such as cable, fiber, and microwave. However, the monitoring effect of the ordinary monitoring system is poor, and it cannot form a unified management. In particular, it cannot grasp the performance of the equipment. In addition, after the industrial production equipment fails, the staff needs to find the fault point and detect and debug it online. Real monitoring significance.

Summary of the invention

In order to solve the above technical problems, the present invention provides an intelligent monitoring method and system for industrial production equipment.

In a first aspect, the present invention provides an intelligent monitoring method for an industrial production device, comprising the following steps:

S1, collecting real-time production data of industrial production equipment;

S2, processing real-time production data of the industrial production equipment, and obtaining real-time production status of the industrial production equipment;

S3, according to the real-time production state of the industrial production equipment, when the real-time production state of the industrial production equipment does not satisfy the preset condition, generating an adjustment instruction for adjusting the real-time production state of the industrial production equipment;

S4, simulating execution of the adjustment instruction, obtaining an analog production state of the industrial production equipment, and outputting simulated production data of the industrial production equipment;

S5, comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment;

S6, determining a positional relationship of the fluctuation value in a preset fluctuation range, and according to the position The relationship sends a corresponding feedback signal;

S7, according to the feedback signal, and adjusting the real-time production state of the industrial production device online by using the adjustment instruction;

Or modifying the adjustment instruction according to the feedback signal.

The beneficial effect of the above solution is that the intelligent monitoring method of the industrial production equipment of the present invention obtains the real-time production state of the industrial production equipment by collecting real-time production data of the industrial production equipment, and needs to adjust the real-time production status of the industrial production equipment when it is necessary to adjust the real-time production status of the industrial production equipment. At the time, according to the real-time production state of the industrial production equipment, a corresponding adjustment instruction is generated. In order to judge whether the adjustment instruction is correct, and to avoid erroneous operation and damage to the industrial production equipment, it is necessary to simulate and execute the adjustment instruction to obtain the simulated production data of the industrial production equipment. And comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment (the fluctuation value reflects the difference between them) And determining a positional relationship between the fluctuation value and a preset fluctuation range, and issuing a corresponding feedback signal according to the position relationship, and finally executing a corresponding strategy according to the feedback signal; the invention can not only monitor the production status of the industrial production equipment in real time. , you can also adjust online Production, and execute instructions based on a reasonable simulation of the control command, which also increases the effect of the present invention to monitor.

Further, further comprising S8, plotting a production state fluctuation curve of the industrial production equipment according to real-time production data of the industrial production equipment, and fluctuation values between simulated production data and real-time production data of the industrial production equipment.

In the above further solution, the production state fluctuation curve of the industrial production equipment can intuitively display the change of the production state of the industrial equipment and the performance change, and can provide guiding suggestions for the later maintenance and replacement of the industrial equipment, and further improve The meaning of monitoring of the present invention.

In a second aspect, the present invention provides an intelligent monitoring system for industrial production equipment, including a real-time production data acquisition module, a real-time production state generation module, a control instruction generation module, an analog execution module, a comparison module, a feedback module, and an online execution module.

The real-time production data acquisition module is configured to collect real-time production data of industrial production equipment;

The real-time production state generation module is configured to process real-time production data of the industrial production equipment to obtain a real-time production state of the industrial production equipment;

The control instruction generating module is configured to adjust a real-time production state of the industrial production device when the real-time production state of the industrial production device does not meet a preset condition according to a real-time production state of the industrial production device Adjustment instruction;

The simulation execution module is configured to simulate execution of the adjustment instruction, obtain an analog production state of the industrial production equipment, and output simulated production data of the industrial production equipment;

The comparison module is configured to compare the simulated production data of the industrial production equipment with the real-time production data, and obtain a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment;

The feedback module is configured to determine a positional relationship of the fluctuation value in a preset fluctuation range, and issue a corresponding feedback signal according to the position relationship;

The online execution module is configured to adjust, according to the feedback signal, an online production state of the industrial production device by using the adjustment instruction;

Or modifying the adjustment instruction according to the feedback signal.

The beneficial effect of the above solution is that the intelligent monitoring system of the industrial production equipment of the invention obtains the real-time production state of the industrial production equipment by collecting real-time production data of the industrial production equipment, and needs to adjust the real-time production state of the industrial production equipment when it is necessary to adjust the real-time production status of the industrial production equipment. At the time, according to the real-time production state of the industrial production equipment, a corresponding adjustment instruction is generated. In order to judge whether the adjustment instruction is correct, and to avoid erroneous operation and damage to the industrial production equipment, it is necessary to simulate and execute the adjustment instruction to obtain the simulated production data of the industrial production equipment. And comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment (the fluctuation value reflects the difference between them) And determining a positional relationship between the fluctuation value and a preset fluctuation range, and issuing a corresponding feedback signal according to the position relationship, and finally executing a corresponding strategy according to the feedback signal; the invention can not only monitor the production status of the industrial production equipment in real time. , you can also adjust online Production, and execute instructions based on a reasonable simulation of the control command, which also increases the effect of the present invention to monitor.

Further, the method further includes a production state fluctuation graph generating module, configured to draw the industrial production equipment according to real-time production data of the industrial production equipment, and fluctuation values between simulated production data and real-time production data of the industrial production equipment. The production state fluctuation curve.

DRAWINGS

1 is a flowchart of an intelligent monitoring method for an industrial production device according to Embodiment 1 of the present invention;

2 is a structural view of an industrial production apparatus according to Embodiment 1 and Embodiment 7 of the present invention;

3 is a diagram showing a mapping relationship between production states of industrial production equipment in an intelligent monitoring method for industrial production equipment according to Embodiment 2 of the present invention;

4 is a state cloud diagram of each data and instruction in an intelligent monitoring method for an industrial production device according to Embodiment 3 of the present invention;

5 is a logic schematic diagram of an intelligent monitoring method for an industrial production device according to Embodiment 1 to Embodiment 5 of the present invention;

6 is a flowchart of an intelligent monitoring method for an industrial production device according to Embodiment 6 of the present invention;

7 is a structural block diagram of an intelligent monitoring system for an industrial production device according to Embodiment 7 of the present invention;

8 is a structural block diagram of an intelligent monitoring system for an industrial production device according to Embodiment 12 of the present invention;

FIG. 9 is a data signaling diagram of an intelligent monitoring system for an industrial production device according to Embodiment 7 to Embodiment 12 of the present invention.

Detailed ways

In the following description, for purposes of illustration and description However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the invention.

Example 1:

FIG. 1 is a flowchart of an intelligent monitoring method for an industrial production device according to Embodiment 1 of the present invention.

Specifically, as shown in FIG. 1 , an intelligent monitoring method for industrial production equipment includes the following steps:

S1, collecting real-time production data of industrial production equipment;

S6, determining a positional relationship of the fluctuation value in a preset fluctuation range, and issuing a corresponding feedback signal according to the position relationship;

Or modifying the adjustment instruction according to the feedback signal.

In the first embodiment of the present invention, the real-time production data of the industrial production equipment is collected, including the production data of the industrial production equipment under the conditions of shutdown, no load, full load, and downtime, and the production data reflecting the state can be industrial production equipment. Voltage, current, speed, flow, temperature, pressure, etc.

For example, take environmental protection production equipment (one type of industrial production equipment) as an example: environmental protection The production equipment is specifically a desulfurization equipment, and its structure is as shown in FIG. 2, including a desulfurization tower, and further comprises a lime pump connected to the desulfurization tower, a process water pump, a compressed air source, a boiler, an activated carbon device and a dust remover, and the dust remover is further provided with Induced draft fan. When real-time production data collection is required for this desulfurization equipment, the current of the lime pump, the process water pump and the induced draft fan can be collected by the current transformer, and then these currents (real-time production data) can be processed to obtain the sulfur dioxide for export and the carbon dioxide for export. The concentration of nitrogen oxides and outlet fumes (the principle of obtaining gas concentration data from equipment current data is: for example, the current of the lime pump is related to the speed of the lime pump, and the speed of the lime pump is related to its ability to treat sulfur dioxide, Here, the current of the lime pump can be reacted to the ability to treat sulfur dioxide. The sulfur dioxide that has not been treated is removed from the outlet, so the current of the lime pump can reflect the concentration of sulfur dioxide at the outlet. Here, the data of the lime pump can be processed to obtain the outlet. The concentration of sulfur dioxide), these concentrations can reflect the operation of the desulfurization treatment, so as to determine whether the desulfurization equipment is in normal working condition. If a certain concentration value exceeds the preset value, the desulfurization equipment is abnormally treated and does not meet the normal treatment of the desulfurization equipment. Preset condition At this time, it is necessary to adjust the operating parameters of the desulfurization equipment, that is, to adjust the current of the lime pump and/or the process water pump and/or the induced draft fan.

When it is necessary to adjust the current of the lime pump and/or the process water pump and/or the induced draft fan to make the desulfurization equipment operate normally, the adjustment command is used to adjust the current of the lime pump and/or the process water pump and/or the induced draft fan. Before making adjustments, you need to judge whether the adjustment command is correct or not to damage the device due to excessive or too low current regulation. The invention determines whether the adjustment instruction is correct by simulating the execution of the adjustment instruction to ensure the normal operation of the device.

Example 2:

Based on the intelligent monitoring method of an industrial production device provided by Embodiment 1 of the present invention, the present invention further provides Embodiment 2, in Embodiment 2,

The S3 is specifically configured to establish a mapping relationship between the real-time production state of the industrial production equipment and a target production state of the industrial production equipment, and set a mapping condition, and generate the adjustment instruction according to the mapping condition;

The specific process of generating the adjustment instruction according to the mapping condition is: programming the mapping condition to form a machine language, and packaging the machine language to form the adjustment instruction.

In the second embodiment of the present invention, the target production state is a state that needs to be finally reached after the industrial production equipment is adjusted. The real-time state to the final state are mapped one by one through mapping conditions, and the mapping condition is an instruction for adjusting the state. 3 is a diagram showing a mapping relationship between production states of industrial production equipment in an intelligent monitoring method for industrial production equipment according to Embodiment 3 of the present invention; in FIG. 3, a real-time production state x corresponds to a target production state x by a mapping condition x. The following is a brief description of environmentally friendly production equipment: for example, the real-time production status of environmentally friendly production equipment is Ag/m ³ for exporting sulfur dioxide, and the sulfur dioxide emission concentration required for environmental protection is Bg/m ³ (A>B). Then the concentration of sulfur dioxide exported to Bg/m ³ is the target production state that the environmentally-friendly production equipment needs to achieve; the real-time production equipment from the real-time production state to the target production state needs to be realized by adjusting the environmentally-friendly production equipment, for example, by adjusting the flow through the lime pump. The current of the process water pump and the induced draft fan; therefore, the current flowing through the lime pump, the process water pump and the induced draft fan is the mapping condition, that is, the adjustment command.

The invention can realize the generation of the adjustment instruction by mapping, and the adjustment instruction generation process is simple and fast, and the monitoring efficiency of the invention can be improved.

Example 3:

Based on the intelligent monitoring method of an industrial production device provided by Embodiment 1 or Embodiment 2 of the present invention, the present invention further provides Embodiment 3, in Embodiment 3,

The specific method for simulating the execution of the adjustment instruction in the S4 is to simulate performing the adjustment instruction by setting a device model and a control model corresponding to the industrial production device;

The device model is specifically a model obtained by mathematically modeling an entity of an industrial production device;

The control model is specifically a model obtained by mathematically modeling a control system of an entity of an industrial production facility;

The control model is embedded in the device model.

In the third embodiment of the present invention, the equipment model is obtained by mathematically modeling the physical industrial production equipment, and the control model is obtained by mathematically modeling the control system of the physical industrial production equipment, the equipment model and the control model. The relevant parameters match the corresponding parameters of the physical industrial equipment, that is to say, the combination of the equipment model and the control model is the soft design of the physical equipment, so the adjustment command can be input to the control model, and then the control model adjusts the device model action by adjusting the instruction. . The following is a brief description of environmentally friendly production equipment: for example, the desulfurization tower, the lime pump connected to the desulfurization tower, the process water pump, the compressed air source, the boiler, the activated carbon device and the precipitator, and the induced draft fan connected to the precipitator Software design modeling, build a device model on the PC device with the same structure as the environmentally friendly production equipment, and then configure the control model of the control device model on the device model. This control model and control entity desulfurization tower, lime pump, process water pump, compression The control circuit of the air source, boiler, activated carbon device, dust collector and induced draft fan is the same, so that the control command can be controlled by the control model control device model; when the control model controls the device model according to the control command, if the control model When the parameters are normal, the control command is correct. If the parameters in the control model are abnormal, the control command is incorrect. At this time, the control command can be directly executed on the real device to avoid malfunction.

4 is a state cloud diagram of each data and instruction in an intelligent monitoring method for an industrial production device according to Embodiment 3 of the present invention. As shown in FIG. 4, an adjustment instruction is generated according to real-time production data, and an adjustment instruction is input into the control model. The control model is used to control the equipment model, and the simulated production data is generated by the equipment model. The simulated production data is compared with the real-time production data to obtain the fluctuation value, and the positional relationship of the fluctuation value in the preset fluctuation range is determined to generate a feedback signal, which is modified according to the feedback signal. Adjust the instruction or execute the adjustment instruction. For example, when the fluctuation value is within the preset fluctuation range, it means that the adjustment instruction is correct. At this time, the feedback signal is 0. When the feedback signal is 0, the adjustment command is executed, that is, the production status of the industrial production equipment is adjusted by the adjustment instruction; when the fluctuation value is not within the preset fluctuation range, the adjustment instruction is incorrect, and the feedback is The signal is 1, and the adjustment command is modified when the feedback signal is 1.

The device model and the control model of the embodiment 3 of the present invention simulate the execution of the adjustment instruction, and can simulate the working state of the industrial production equipment in a real scene, so that the simulation is more realistic.

Example 4:

The present invention further provides Embodiment 4, in Embodiment 4, based on an intelligent monitoring method for industrial production equipment provided by any one of Embodiments 1 to 3 of the present invention.

In the S7, when the real-time production state of the industrial production equipment fails to be adjusted online according to the feedback signal and the adjustment instruction, the industrial production equipment is forcibly controlled to be out of service.

In the fourth embodiment of the present invention, when the intelligent monitoring system of the present invention fails, or when the industrial production equipment fails, the adjustment instruction may be unsuccessful in execution, and then, in order to avoid the intelligent monitoring system and In the fourth step of the present invention, the industrial production equipment is forcibly controlled to stop the industrial production equipment from being shut down to protect the intelligent monitoring system and the industrial production equipment.

Example 5:

The present invention further provides Embodiment 5, in Embodiment 5, based on an intelligent monitoring method for industrial production equipment provided by any one of Embodiments 1 to 4 of the present invention.

In the S7, the feedback signal is trained by using a neural network to obtain a neural network training result, and the adjustment instruction is modified according to the neural network training result.

In the fifth embodiment of the present invention, the neural network is also called an artificial neural network, and the artificial neural network is an algorithm mathematical model that simulates the behavior characteristics of the animal neural network and performs distributed parallel information processing. This kind of network relies on the complexity of the system to adjust the relationship between a large number of internal nodes to achieve the purpose of processing information. On the basis of theoretical model research, a specific neural network model is constructed to realize computer simulation or human neural network preparation hardware, including network learning algorithm research. This work is also known as technical model research. The algorithm used by neural networks is vector multiplication, and symbolic functions and their various approximations are widely used. Parallel, fault tolerant, hardware-enabled, and self-learning. In the fifth embodiment of the present invention, the self-learning characteristic of the neural network is used to train the feedback signal to obtain a neural network training result, and the adjustment instruction is modified according to the neural network training result; the process of modifying the adjustment instruction is a self-learning The process of self-learning enables the adjustment instructions to be more precise, thereby improving the accuracy of intelligent monitoring.

The first embodiment to the fifth embodiment will be comprehensively described with reference to FIG. 5. FIG. 5 is a logic schematic diagram of an intelligent monitoring method for an industrial production device according to the present invention.

In the above FIG. 5, the real-time production data of the industrial production equipment is first collected; then the real-time production data of the industrial production equipment is processed to obtain the real-time production status of the industrial production equipment; and then it is determined whether the real-time production status satisfies The condition for judging whether the preset condition is met is whether the real-time production state is the production state we need. For example, in the desulfurization equipment, what we need to obtain is that the concentration of sulfur dioxide at the outlet is not higher than 0.01g/m ³ , if desulfurization The real-time production status of the equipment at this time is the concentration of sulfur dioxide of 0.007g/m ³ , which indicates that the state of industrial production equipment at this time meets our needs (within the preset range), then no adjustment is made, if the desulfurization equipment The real-time production status is that the concentration of sulfur dioxide is 0.015g/m ³ , which indicates that the state of industrial production equipment at this time does not meet our needs (not within the preset range), then the desulfurization equipment needs to be adjusted, and the adjustment is generated at this time. Instruction; before adjusting the desulfurization equipment, it is necessary to judge the adjustment to the real-time production status of the industrial equipment The instruction is simulated and the simulated production data of the industrial production equipment is obtained; after all, the production data of the industrial equipment simulation is not the real-time production data of the industrial equipment. If the adjustment instruction is very accurate, the simulated production data should be very close to or even equal to the real-time. Production data, if the adjustment instruction is not accurate, there will be a certain gap between the simulated production data and the real-time production data, that is, the fluctuation. At this time, it is necessary to judge the position of the fluctuation value within the preset fluctuation range, if the fluctuation value It is not within the preset fluctuation range, indicating that the adjustment of the command to adjust the co-production equipment will cause serious deviations. Therefore, when the fluctuation value is not within the preset fluctuation range, an alarm needs to be issued to alarm, indicating that the adjustment instruction at this time is not available. Line, when the fluctuation value is within the preset fluctuation range, it means that the adjustment instruction at this time is adjusted to adjust the industrial production equipment without serious deviation, and the adjustment is reasonable. At this time, a feedback signal is issued, indicating the adjustment at this time. The instructions are available, as to how much adjustment instructions are available at this time. This needs to be judged according to the signal value of the feedback signal. For example, the feedback value of the feedback signal is 1, indicating that the adjustment command can be directly executed at this time (representing the adjustment command accuracy). For example, the feedback signal has a feedback value of 2, indicating that this time The self-learning can be performed by the artificial neural network to modify the adjustment instruction, so that the adjustment instruction is more accurate.

Example 6

On the basis of the intelligent monitoring method for an industrial production device provided by any one of the first embodiment to the fifth embodiment of the present invention, the present invention further provides Embodiment 6, in Embodiment 6, as shown in FIG.

Also included is S8, which plots a production state fluctuation curve of the industrial production equipment based on real-time production data of the industrial production equipment, and fluctuation values between simulated production data and real-time production data of the industrial production equipment. For example, taking the time as the horizontal axis and the production data of the industrial production equipment as the vertical axis, establishing a two-dimensional coordinate system of the fluctuation state of the production state of the industrial production equipment, real-time production data of the industrial production equipment, and the industrial production equipment The fluctuations between the simulated production data and the real-time production data are plotted in the coordinate system, and all the real-time production data points are connected by a smooth curve, and all the fluctuation value points are connected by another smooth curve; according to the fluctuation of the two curves It can reflect the production status of industrial production equipment.

In the sixth embodiment of the present invention, the production state fluctuation curve of the industrial production equipment can intuitively display the change of the production state of the industrial equipment and the performance change, and can provide guiding suggestions for the later maintenance and replacement of the industrial equipment, further Improve the monitoring significance of the present invention.

In summary, a method for intelligently monitoring an industrial production device of the present invention obtains real-time production status of the industrial production equipment by collecting real-time production data of industrial production equipment, and real-time adjustment of the industrial production equipment when needed In the production state, the corresponding adjustment instruction is generated according to the real-time production state of the industrial production equipment. In order to judge whether the adjustment instruction is correct and avoid the misuse of the industrial production equipment, the simulation adjustment instruction is required to obtain the simulation of the industrial production equipment. Production data, and then comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining fluctuation values between the simulated production data and the real-time production data of the industrial production equipment (fluctuation values reflect between them) a difference), then determining a positional relationship between the fluctuation value and a preset fluctuation range, and issuing a corresponding feedback signal according to the positional relationship, and finally executing a corresponding strategy according to the feedback signal; the invention can not only monitor the industrial production equipment in real time Production status, you can also adjust it online Production, and the simulation execution instruction based on reasonable control instruction, which also improves the effect of the present invention to monitor.

Example 7

Based on the intelligent monitoring method of an industrial production device described in the above embodiment 1, the seventh embodiment of the present invention further provides an intelligent monitoring system for an industrial production device, which is the one according to the above embodiment 1. An intelligent monitoring method for industrial production equipment is processed. In Embodiment 7, as shown in FIG.

An intelligent monitoring system for industrial production equipment, comprising real-time production data acquisition module, real-time production state generation module, adjustment instruction generation module, simulation execution module, comparison module, feedback module and online execution module,

The instruction generating module is configured to, according to a real-time production state of the industrial production device, generate a real-time production state of the industrial production device when the real-time production state of the industrial production device does not meet a preset condition instruction;

Or modifying the adjustment instruction according to the feedback signal.

In Embodiment 7 of the present invention, the real-time production data acquisition module collects real-time production data of the industrial production equipment, including the production data of the industrial production equipment under the conditions of shutdown, no load, full load, and downtime, and reacts the production data of these states. It can be the voltage, current, speed, flow, temperature, pressure, etc. of industrial production equipment.

For example, taking environmentally friendly production equipment (one type of industrial production equipment) as an example: the environmentally friendly production equipment is specifically a desulfurization equipment, and its structure is shown in Figure 2, including a desulfurization tower, and also includes a lime pump connected to the desulfurization tower. Process water pump, compressed air source, boiler, activated carbon device and dust collector, and an air blower on the dust collector. When real-time production data collection is required for the desulfurization equipment, the current of the lime pump, the process water pump and the induced draft fan can be collected by the current transformer, and then these currents (real-time production data) are processed, and the real-time production state generation module can Obtaining the concentration of sulfur dioxide, export carbon dioxide, exporting nitrogen oxides and exporting soot. These concentrations can reflect the operation of the desulfurization treatment, so as to determine whether the desulfurization equipment is in normal working condition. If a certain concentration value exceeds the preset value, The desulfurization equipment is abnormally treated and does not meet the preset conditions for the normal treatment of the desulfurization equipment. At this time, the operating parameters of the desulfurization equipment need to be adjusted, that is, the current of the lime pump and/or the process water pump and/or the induced draft fan is adjusted.

Example 8

The present invention further provides Embodiment 8 in the eighth embodiment of the present invention.

The adjustment instruction generating module is specifically configured to: establish a mapping relationship between a real-time production state of the industrial production equipment and a target production state of the industrial production equipment, and set a mapping condition, and generate a location according to the mapping condition Adjustment instruction

In the eighth embodiment of the present invention, the target production state is a state that needs to be finally reached after the industrial production equipment is adjusted. The real-time state to the final state are mapped one by one through mapping conditions, and the mapping condition is an instruction for adjusting the state. The real-time production state x corresponds to the target production state x by the mapping condition x. The following is a brief description of environmentally friendly production equipment: for example, the real-time production status of environmentally friendly production equipment is the concentration of sulfur dioxide exported to A g / m ³ , and the concentration of sulfur dioxide emitted by environmental protection is Bg / m ³ , (A> B The concentration of sulfur dioxide exported to Bg/m ³ is the target production state that environmentally friendly production equipment needs to achieve; the production of environmentally friendly production equipment from the real-time production state to the target production state needs to be achieved by adjusting environmentally friendly production equipment, for example, by adjusting the flow through the lime. The current of the pump, process water pump and induced draft fan; therefore, the current flowing through the lime pump, the process water pump and the induced draft fan is the mapping condition, that is, the adjustment command.

Example 9

Based on the intelligent monitoring system of an industrial production device provided by Embodiment 7 or Embodiment 8 of the present invention, the present invention further provides Embodiment 9, in Embodiment 9

The simulation execution module is specifically configured to simulate execution of the adjustment instruction by setting a device model and a control model corresponding to the industrial production device, and output simulated production data of the industrial production device;

The control model is embedded in the device model.

In the embodiment 9 of the present invention, the equipment model is obtained by mathematically modeling the physical industrial production equipment, and the control model is obtained by mathematically modeling the control system of the physical industrial production equipment, and the equipment model and the control model are obtained. The relevant parameters match the corresponding parameters of the physical industrial equipment, that is to say, the combination of the equipment model and the control model is the soft design of the physical equipment, so the adjustment command can be input to the control model, and then the control model adjusts the device model action by adjusting the instruction. . The following is a brief description of environmentally friendly production equipment: for example, the desulfurization tower, the lime pump connected to the desulfurization tower, the process water pump, the compressed air source, the boiler, the activated carbon device and the precipitator, and the induced draft fan connected to the precipitator Software design modeling, build a device model on the PC device with the same structure as the environmentally friendly production equipment, and then configure the control model of the control device model on the device model. This control model and control entity desulfurization tower, lime pump, process water pump, compression The control circuit of the air source, boiler, activated carbon device, dust collector and induced draft fan is the same, so that the control command can be controlled by the control model control device model; when the control model controls the device model according to the control command, if the control model When the parameters are normal, the control command is correct. If the parameters in the control model are abnormal, the control command is incorrect. At this time, the control command can be directly executed on the real device to avoid malfunction.

The device model and the control model of the embodiment 9 of the present invention simulate and execute the adjustment instruction, and can simulate the working state of the industrial production equipment in a real scene, so that the simulation is more realistic.

Example 10:

The present invention further provides Embodiment 10, in Embodiment 10, based on an intelligent monitoring system for an industrial production device provided by any one of Embodiments 7 to 9 of the present invention.

The online execution module is specifically configured to be online when the feedback signal and the adjustment instruction are When the real-time production state of the industrial production equipment fails, the industrial production equipment is forcibly controlled to be shut down.

In the embodiment 10 of the present invention, when the intelligent monitoring system of the present invention fails, or when the industrial production equipment fails, the adjustment instruction may be unsuccessful in execution, then, in order to avoid the intelligent monitoring system and In the industrial production equipment, the serious consequences of the loss of control, the embodiment 10 of the present invention also requires forced control of the industrial production equipment to be shut down to protect the intelligent monitoring system and industrial production equipment.

Example 11

On the basis of an intelligent monitoring system for an industrial production device provided by any one of Embodiments 7 to 10 of the present invention, the present invention further provides Embodiment 11, in Embodiment 11,

The online execution module is specifically configured to: use a neural network to train the feedback signal, obtain a neural network training result, and modify the adjusted instruction according to the neural network training result.

In the embodiment 11 of the present invention, the neural network is also called an artificial neural network, and the artificial neural network is an algorithm mathematical model that simulates the behavior characteristics of the animal neural network and performs distributed parallel information processing. This kind of network relies on the complexity of the system to adjust the relationship between a large number of internal nodes to achieve the purpose of processing information. On the basis of theoretical model research, a specific neural network model is constructed to realize computer simulation or human neural network preparation hardware, including network learning algorithm research. This work is also known as technical model research. The algorithm used by neural networks is vector multiplication, and symbolic functions and their various approximations are widely used. Parallel, fault tolerant, hardware-enabled, and self-learning. In the embodiment 11 of the present invention, the self-learning characteristic of the neural network is used to train the feedback signal to obtain a neural network training result, and the adjustment instruction is modified according to the neural network training result; the process of modifying the adjustment instruction is a self-learning The process of self-learning enables the adjustment instructions to be more precise, thereby improving the accuracy of intelligent monitoring.

Example 12

On the basis of an intelligent monitoring system for an industrial production device provided by any of the embodiments 7 to 11 of the present invention, the present invention further provides Embodiment 12, and in Embodiment 12, as shown in FIG.

The system of the present invention further includes a production state fluctuation graph generation module for plotting the industrial production according to real-time production data of the industrial production equipment, and fluctuation values between simulated production data and real-time production data of the industrial production equipment The production state fluctuation curve of the equipment. For example, taking the time as the horizontal axis and the production data of the industrial production equipment as the vertical axis, establishing a two-dimensional coordinate system of the fluctuation state of the production state of the industrial production equipment, real-time production data of the industrial production equipment, and the industrial production equipment The fluctuations between the simulated production data and the real-time production data are plotted in the coordinate system, and all the real-time production data points are connected by a smooth curve, and all the fluctuation value points are connected by another smooth curve; according to the fluctuation of the two curves It can reflect the production status of industrial production equipment.

In the embodiment 12 of the present invention, the production state fluctuation curve of the industrial production equipment can intuitively display the change of the production state of the industrial equipment and the performance change, and can provide guiding suggestions for the later maintenance and replacement of the industrial equipment, further Improve the monitoring significance of the present invention.

The intelligent monitoring system of an industrial production equipment provided by Embodiments 7 to 12 of the present invention is comprehensively described below with reference to FIG. 9. FIG. 9 is an intelligent monitoring of an industrial production equipment provided by the embodiment 7 to the division strength 12 of the present invention. The data signaling diagram of the system clearly shows the flow of data signaling of the system of the present invention, which can deepen the understanding of the system of the present invention.

In summary, the system of the present invention provides an intelligent monitoring system for industrial production equipment to obtain real-time production status of the industrial production equipment by collecting real-time production data of industrial production equipment, and real-time adjustment of the industrial production equipment when needed In the production state, the corresponding adjustment instruction is generated according to the real-time production state of the industrial production equipment. In order to judge whether the adjustment instruction is correct and avoid the misuse of the industrial production equipment, the simulation adjustment instruction is required to obtain the simulation of the industrial production equipment. Production data, and then comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining fluctuation values between the simulated production data and the real-time production data of the industrial production equipment (fluctuation values reflect between them) a difference), then determining a positional relationship between the fluctuation value and a preset fluctuation range, and issuing a corresponding feedback signal according to the positional relationship, and finally executing a corresponding strategy according to the feedback signal; the invention can not only monitor the industrial production equipment in real time Production status, you can also adjust it online Production, and the simulation execution instruction based on reasonable control instruction, which also improves the effect of the present invention to monitor.

The reader should understand that in the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the embodiment or example is incorporated. The specific features, structures, materials, or characteristics described are included in at least one embodiment or example of the invention. In the present specification, the schematic representation of the above terms is not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, various embodiments or examples described in the specification and features of various embodiments or examples may be combined and combined without departing from the scope of the invention.

Although the embodiments of the present invention have been shown and described, it is understood that the above-described embodiments are illustrative and are not to be construed as limiting the scope of the invention. The embodiments are subject to variations, modifications, substitutions and variations.

Claims

An intelligent monitoring method for industrial production equipment, comprising: the following steps,

S1, collecting real-time production data of industrial production equipment;

S2, processing real-time production data of the industrial production equipment, and obtaining real-time production status of the industrial production equipment;

S3, according to the real-time production state of the industrial production equipment, when the real-time production state of the industrial production equipment does not satisfy the preset condition, generating an adjustment instruction for adjusting the real-time production state of the industrial production equipment;

S4, simulating execution of the adjustment instruction, obtaining an analog production state of the industrial production equipment, and outputting simulated production data of the industrial production equipment;

S5, comparing the simulated production data of the industrial production equipment with the real-time production data, and obtaining a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment;

S6, determining a positional relationship of the fluctuation value in a preset fluctuation range, and issuing a corresponding feedback signal according to the position relationship;

S7, according to the feedback signal, and adjusting the real-time production state of the industrial production device online by using the adjustment instruction;

Or modifying the adjustment instruction according to the feedback signal.
The intelligent monitoring method of an industrial production equipment according to claim 1, wherein the S3 is specifically, the real-time production state of the industrial production equipment and the target production of the industrial production equipment preset. The state establishes a mapping relationship, and sets a mapping condition, and generates the adjustment instruction according to the mapping condition;

The specific process of generating the adjustment instruction according to the mapping condition is: programming the mapping condition to form a machine language, and packaging the machine language to form the adjustment instruction.
The intelligent monitoring method for industrial production equipment according to claim 1 or 2, wherein the specific method of simulating the execution of the adjustment instruction in the S4 is by setting a device model corresponding to the industrial production equipment And controlling the model to simulate execution of the adjustment instruction;

The device model is specifically a model obtained by mathematically modeling an entity of an industrial production device;

The control model is specifically a model obtained by mathematically modeling a control system of an entity of an industrial production facility;

The control model is embedded in the device model.
The intelligent monitoring method for an industrial production facility according to claim 1 or 2, wherein in said S7, real-time production of said industrial production equipment is adjusted online according to said feedback signal and said adjustment command When the state fails, the industrial production equipment is forcibly controlled to be shut down.
The intelligent monitoring method for an industrial production device according to claim 1 or 2, wherein in the S7, the feedback signal is trained by using a neural network to obtain a god The adjustment instruction is modified according to the network training result and according to the neural network training result.
An intelligent monitoring system for industrial production equipment, comprising: a real-time production data acquisition module, a real-time production state generation module, a control instruction generation module, a simulation execution module, a comparison module, a feedback module, and an online execution module,

The real-time production data acquisition module is configured to collect real-time production data of industrial production equipment;

The real-time production state generation module is configured to process real-time production data of the industrial production equipment to obtain a real-time production state of the industrial production equipment;

The control instruction generating module is configured to adjust a real-time production state of the industrial production device when the real-time production state of the industrial production device does not meet a preset condition according to a real-time production state of the industrial production device Adjustment instruction;

The simulation execution module is configured to simulate execution of the adjustment instruction, obtain an analog production state of the industrial production equipment, and output simulated production data of the industrial production equipment;

The comparison module is configured to compare the simulated production data of the industrial production equipment with the real-time production data, and obtain a fluctuation value between the simulated production data and the real-time production data of the industrial production equipment;

The feedback module is configured to determine a positional relationship of the fluctuation value in a preset fluctuation range, and issue a corresponding feedback signal according to the position relationship;

The online execution module is configured to adjust, according to the feedback signal, an online production state of the industrial production device by using the adjustment instruction;

Or modifying the adjustment instruction according to the feedback signal.
The intelligent monitoring system of an industrial production equipment according to claim 6, wherein the control instruction generating module is specifically configured to: real-time production status of the industrial production equipment and the industrial production equipment preset The target production state establishes a mapping relationship, and sets a mapping condition, and generates the adjustment instruction according to the mapping condition;

The specific process of generating the adjustment instruction according to the mapping condition is: programming the mapping condition to form a machine language, and packaging the machine language to form the adjustment instruction.
The intelligent monitoring system for an industrial production device according to claim 6 or 7, wherein the simulation execution module is specifically configured to:

Simulating execution of the adjustment instruction by setting a device model and a control model corresponding to the industrial production equipment, and outputting simulated production data of the industrial production equipment;

The device model is specifically a model obtained by mathematically modeling an entity of an industrial production device;

The control model is specifically a model obtained by mathematically modeling a control system of an entity of an industrial production facility;

The control model is embedded in the device model.
The intelligent monitoring system for an industrial production device according to claim 6 or 7, wherein the online execution module is specifically configured to:

When the real-time production state of the industrial production equipment fails to be adjusted online according to the feedback signal and the adjustment instruction, the industrial production equipment is forcibly controlled to be out of service.
The intelligent monitoring system for an industrial production device according to claim 6 or 7, wherein the online execution module is further configured to:

The feedback signal is trained by using a neural network to obtain a neural network training result, and the adjusted instruction is modified according to the neural network training result.