CN108227676A - The online fault detect of valve-controlled cylinder electrohydraulic servo system, estimation and localization method - Google Patents
The online fault detect of valve-controlled cylinder electrohydraulic servo system, estimation and localization method Download PDFInfo
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Abstract
The invention discloses a kind of online fault detect of valve-controlled cylinder electrohydraulic servo system, estimation and localization methods, include the following steps：1) mission nonlinear models；2) system normal parameter recognizes；3) data during system normal operation that will be obtained in step 2) bring the nonlinear state equation of system in step 1) into, obtain the expression formula of normal system parameter matrix and the nonlinear state equation of system；4) the correlated inputs output parameter of real-time acquisition system；5) fault detection and identification under varying load；6) robust Fault decision；If 7) fault-free in step 6), return to step 4)；If faulty, starting step 5) fault vectors estimation module in fault-detecting-observer, 8) Fault Isolation positioning；The beneficial effects of the invention are as follows：System running state can in real time be monitored, reduce economic loss in valve-controlled cylinder system there are being loaded outside unknown time-varying, in the case of non-linear and uncertain parameter.
Description
Technical Field
The invention relates to the field of fault diagnosis of an electro-hydraulic servo system, in particular to an online fault detection, estimation and positioning method of a valve control cylinder electro-hydraulic servo system.
Background
The electro-hydraulic servo system is a feedback control system consisting of an electric signal processing device and a hydraulic power mechanism, and is widely applied to the fields of industrial manufacturing, transportation, engineering machinery and the like because of the advantages of high response speed, high output pressure, large power-to-volume ratio, convenience in control and the like. The valve control cylinder electro-hydraulic servo system is a common system with wide application, and the working principle of the valve control cylinder electro-hydraulic servo system is mainly that oil entering and exiting a hydraulic oil cylinder is controlled through a servo valve or a proportional valve and the like so as to control the position, the speed and the like of an oil cylinder piston, and the valve control cylinder electro-hydraulic servo system is adopted for controlling an airplane steering engine, a ship steering engine, a mechanical arm and the plate thickness of a plate and strip rolling mill. However, due to various unavoidable factors such as change of working environment and wear and aging of elements, any system is inevitably in fault, the electro-hydraulic servo system is a complex mechanical, electrical and hydraulic integrated system, and the fault is often characterized by diversity, concealment, coupling, complex cause-effect relationship and the like. With the development of modern manufacturing technology, control technology and automation technology, an electro-hydraulic servo system is developing towards the directions of light weight, small volume, high pressure, variable pressure and the like, and the scale, function, complexity and automation level of the system are improved, and meanwhile, higher requirements are provided for the state monitoring and fault diagnosis of the system, so that people hope to improve the reliability and safety of the system urgently.
The existing fault diagnosis method of the electro-hydraulic servo system mainly comprises a method based on an analytical model, a method based on knowledge and a method based on signal analysis, wherein the method of signal analysis is mainly used for fault analysis and diagnosis of a single hydraulic element, including a hydraulic pump, a valve and an oil cylinder; the knowledge-based method mainly comprises a neural network, an expert system and the like, does not need to establish a system model, belongs to the field of intelligent diagnosis, but needs to use typical data to train the neural network in advance or use expert experience to establish a knowledge base and the like; the method based on the analytical model does not need to acquire a large amount of historical data in advance, but needs to establish a system model and has certain requirements on the accuracy of the model. The methods have advantages and disadvantages, and in recent years, many fault methods based on model and data-driven fusion are developed, but mainly aim at the condition that external load is constant, and the load is known or measurable. Based on the complexity of the actual working conditions, the operation parameters of the system and the external load force are often not constant but time-varying and are difficult to obtain accurately, and under the unknown time-varying load, even under the normal condition, the pressure, the flow and the like output by the system are not constant values, but fluctuate up and down, and sometimes the fluctuation amplitude is large, so the fault form of the system is easily confused with the normal form and is difficult to distinguish. In addition, the valve control cylinder electro-hydraulic servo system has many inherent non-linear factors, such as the non-linear relation of pressure and flow, and the combination of the uncertain factors and the time-varying load brings great challenges to the real-time diagnosis of system faults.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides the online fault detection, estimation and positioning method of the valve control cylinder electro-hydraulic servo system, which has strong robustness and accurate detection.
The technical scheme of the invention is as follows:
the invention relates to an on-line fault detection, estimation and positioning method of a valve control cylinder electro-hydraulic servo system, which is based on the valve control cylinder electro-hydraulic servo system, wherein the valve control cylinder electro-hydraulic servo system comprises a hydraulic cylinder, a servo valve/a proportional valve connected with the hydraulic cylinder and a hydraulic pump connected with the servo valve/the proportional valve, a sensor is arranged on a piston of the hydraulic cylinder, the sensor is connected with a controller through a circuit, and the controller is connected with the servo valve/the proportional valve through a circuit;
the method is characterized by comprising the following steps:
1) and (3) system nonlinear modeling: establishing a mathematical model of a valve control cylinder electro-hydraulic servo system; selecting a system state variable; establishing a nonlinear state equation of the system;
2) and (3) identifying normal parameters of the system: acquiring input and output historical data under different working conditions and environmental conditions when the system normally operates, inputting an identification model, and obtaining parameters and a variation range thereof when the system normally operates by using the identification model;
3) substituting the data obtained in the step 2) during normal operation of the system into the nonlinear state equation of the system in the step 1) to obtain a normal system parameter matrix and an expression of the nonlinear state equation of the system;
4) acquiring relevant input and output parameters of a system in real time;
5) fault detection and estimation under variable load: establishing a fault detection observer, wherein the fault detection observer comprises an external load force decoupling module, a fault dominant module, a nonlinear module, a stability module and a fault vector estimation module, inputting collected module signals into the observer to obtain estimated output of the observer, and obtaining an output residual error by making a difference value with the output of an actual system;
6) and (3) robust fault decision: inputting the output residual error obtained in the step 3) into a calculation error estimation function, and diagnosing whether the system has a fault or not by combining a self-adaptive threshold value calculated in real time;
7) if no fault exists in the step 6), returning to the step 4); if the fault occurs, starting a fault vector estimation module in the step 5) of the fault detection observer, and obtaining an output residual error value by the observer and an actual system to carry out real-time adjustment on a network weight coefficient so as to finally obtain a fault vector estimation value;
8) fault isolation and positioning: and (4) judging the type and position of the possible fault by combining the fault vector estimated value in the step 7) and the motion direction of the hydraulic cylinder piston, and outputting a diagnosis result.
The method for detecting, estimating and positioning the online fault of the valve control cylinder electro-hydraulic servo system is characterized in that a mathematical model of the valve control cylinder electro-hydraulic servo system is established in the step 1): firstly, carrying out equivalence on each link of the valve control cylinder electro-hydraulic servo system, establishing a flow equation of a servo valve/proportional valve, a dynamic equation of the servo valve/proportional valve, a flow continuity equation of a hydraulic cylinder and a motion force balance equation of a piston of the hydraulic cylinder, and expressing a mathematical model of the whole system by the four equations as follows:
flow equation for servo/proportional valves:
in the formula q±，p±Flow and pressure, p, of two chambers of the hydraulic cylinder, respectivelys+，ps-Supply and return pressure, x, respectivelyvAnd α are respectively the displacement of the servo valve/proportional valve core from the neutral position and the positive covering quantity, k of the valve corecIs the flow coefficient;
servo valve/proportional valve dynamic equation:
in the formula kvAnd τ is a gain and time coefficient describing the dynamic characteristics of the servo valve/proportional valve, and u is the input voltage;
flow continuity equation for hydraulic cylinder:
a±and V±Respectively the area and effective volume of two chambers of the hydraulic cylinder, ci,ceRespectively the internal and external leakage coefficients, x, of the hydraulic cylinderpFor cylinder piston displacement, βeFor effective bulk modulus, p+And p-The pressure of the left cavity and the right cavity of the hydraulic cylinder is used;
the motion force balance equation of the hydraulic cylinder piston is as follows:
where m is the total mass converted to load, bpIs a viscous damping coefficient, f isExternal load force on the piston, d variable load disturbance force, a+And a-The area of two cavities of the hydraulic cylinder;
selecting a system state variable: selecting the moving speed of the piston of the hydraulic cylinderLeft and right two-cavity pressure p of hydraulic cylinder+And p-And spool displacement x of servo valve/proportional valvevFor the state variables of the system, defining the state variables of the system as
Establishing a nonlinear state equation of the system: the voltage input into the servo valve/proportional valve is taken as input u, and the movement speed of the piston of the hydraulic cylinder is definedLeft and right two-cavity pressure p of hydraulic cylinder+And p-As an output vectorThe flow equation of the servo valve/proportional valve, the dynamic equation of the servo valve/proportional valve, the flow continuity equation of the hydraulic cylinder and the motion force balance equation of the hydraulic cylinder piston are subjected to form transformation, a state variable x and a nonlinear term g (x) in the four equations are extracted and converted into the following state equation form, and matrixes A, B, C and D are parameter matrixes of the system;
the online fault detection, estimation and positioning method of the valve control cylinder electro-hydraulic servo system is characterized in that input and output historical data under different working conditions and environmental conditions in normal operation of the system are acquired in the step 2): given continuously variable servo valve/proportional valve voltage input signal, collecting hydraulic cylinder piston displacement value xpAnd hydraulic pressurePressure value p of two cavities of cylinder+And p-；
Identifying the model: obtaining a linear equation set containing identification parameters by a nonlinear state equation of the system:
Φθ＝Γ，
θ＝[βe -1cicekq]Tas the parameter to be identified, kq＝kc·kv，
A parameter matrix containing system state quantities, wherein k is 1,2, 3;
substituting the acquired data into the equation set, and identifying the unknown parameter theta in the equation set by adopting a least square method; and substituting the system parameters obtained by identification into a nonlinear state equation of the system, comparing and correcting the obtained output with the actual system output, and finally obtaining the parameter values and the variation range of the system in normal operation.
The on-line fault detection, estimation and positioning method of the valve control cylinder electro-hydraulic servo system under the variable load is characterized in that in the step 5), an external load force decoupling module: the method mainly realizes the function that the change of the external interference force does not influence the residual error for fault judgment, and comprises the following steps: setting the parameter matrix T ═ D (CD) of the observer++Y[I-(CD)(CD)+]Wherein (CD)+＝((CD)T(CD))-1(CD)TY is a parameter matrix to be set and is obtained in the stability module, C, D is a system parameter matrix obtained in the step 3), and I is an identity matrix;
a fault dominant module: once fault occurs in main implementation system, it will be used for faultThe function that the judged residual produces the influence, the realization method: set parameter matrix M ═ I + TC, and MFfNot equal to 0, wherein FfIs a fault matrix expressed as Ff＝[e1e2e3]，
A non-linear module: obtaining the non-linear expression g (x) of the original system to observe the state quantityThe original state quantity x is replaced, linear simplification is not needed, and the state quantity x is directly used for processing of a stability module;
a stability module: the method mainly realizes the quick and effective convergence of the observer, and comprises the following steps:
a: obtaining a positive definite symmetric matrix P by solving the following linear matrix inequality>0, and two matricesWherein P is1＝P(I+TaC),Ta＝-D(CD)+,Tb＝I-(CD)(CD)+γ is a normal number:
b: the matrix Y and the matrix K are obtained by calculation,and
c: obtaining other observer parameter matrixes, wherein G is MB, N is MA-KC, and L is K-NT;
a residual generation module: output signals of the actual system (including the piston speed signal value of the hydraulic cylinder)And the pressure signal value p of two cavities of the hydraulic cylinder+And p-Composed output vectorAnd the observer output vectorSubtracting to obtain an output residual vector
A fault vector estimation module: the fault vector estimation module is composed of a neural network, does not work when the residual error is less than or equal to the threshold value, and is activated only when the residual error is greater than the threshold value so as to carry out fault estimation.
The above-mentioned matrices T, M, G, N and L are the system parameter matrices to be designed, and the matrices A, B, C and D are the system parameter matrices obtained in step 3);
the online fault detection, estimation and positioning method of the valve control cylinder electro-hydraulic servo system is characterized in that the error estimation function calculated in the step 6) is as follows: j (t) ═ rT(t) hr (t), where H is a weighted diagonal function;
fault detection is carried out according to the following rules:
in the formula, lambda (t) is an adaptive threshold value, the adaptive threshold value is composed of two parts, one part is a steady-state threshold value, the other part is a transient threshold value, the switching is carried out according to the acceleration value of a hydraulic cylinder piston, the normal fluctuation of system parameters is taken into consideration when the threshold value is set, the threshold value is calculated on line based on a statistical method, in addition, the data calculation amount and the storage space are reduced by carrying out a segmented weighting mode on a residual sequence, meanwhile, certain robustness is ensured, and the specific implementation process comprises the following steps:
a: substituting the parameter variation range of the system obtained by the identification model in the step 2) during normal operation into a fault detection observer to obtain a steady state threshold value fluctuation range, and taking the upper and lower limits of fluctuation as a steady state threshold value lambdao-，λo+；
b: carrying out difference on the obtained piston velocity values or carrying out twice difference on the position values to obtain a piston motion acceleration value aP(t)；
c: respectively obtaining a residual error r with the length of Si(k) Sequence pair and piston acceleration ai(k) Wherein i ═ k-1) S/l +1, …, (k-1) S/l + S, and calculating the piston mean a of the acceleration sequence of this S datap(k)；
d: residual error sequence r of S data lengthi(k) Dividing into one part, calculating the mean value mu of each part with S/l residual datap(k) Then, the weighted mean μ is calculated according to the following formular(k) Sum variance σr 2(k)；
Wherein wpAre assigned good weight coefficients, and
e: determining an adaptive threshold λ (k) from the following equation;
where ε is the bandwidth factor, caIs a critical value of the acceleration;
f: and repeating the steps and calculating the threshold lambda in real time.
The method for detecting, estimating and positioning the online fault of the valve cylinder electrohydraulic servo system is characterized in that the implementation process of the fault vector estimation module in the step 7) is as follows:
setting a reasonable neural network structure, wherein the number of network input nodes, hidden layer nodes and output nodes is n + m, s and n respectively, wherein n and m are the state quantity and the input quantity of the fault diagnosis observer, the number of hidden layers is determined offline, the input quantity of the neural network is the estimated value of the system state quantity and the input voltage of a servo valve/proportional valve, and establishing the neural networkWherein W is the output weight coefficient matrix of the neural network to be designed,is a neural network basis function;
obtaining state estimators of fault diagnosis observer in real timeAnd the output residual vector rn(t) real-time adjustment of the neural network output weight coefficients according to the following equationWhere the parameter matrix η is a positive constant, P is a positive constant matrix, and u is the input voltage of the servo valve/proportional valve;
recording the neural network output at that timeThe value is obtained as the current fault vector estimated value f (t) ═ fnn(t)；
Obtaining an observer estimated output vector after starting a neural network fault vector estimation moduleAnd obtaining an output residualWhere y (t) is the actual output vector;
detecting the output residual rn(t) if rn(t)＞λn(t) returning to step 6) if rn(t)≤λn(t) proceeding to the next step, wherein lambdan(t) determining an adaptive threshold for the fault estimation;
the estimated value of the output fault vector is f (t) ═ f1f2f3]T。
The method for detecting, estimating and positioning the online fault of the valve cylinder electrohydraulic servo system is characterized in that the fault type and position in the step 8) are judged as follows:
based on the fault estimation vector f (t) ═ f1f2f3]TThe fault positioning method comprises the following steps:
when, | f1＞δ1，|f2|＜δ2，|f3|＜δ3Or,when, | f1|＜δ1，|f2|＞δ2，|f3|＜δ3Judging that the system oil supply pressure is abnormal, and checking the hydraulic pump and the pump outlet overflow valve;
when, if | f1|＜δ1，|f2|＞δ2，|f3|＜δ3Or,when, | f1|＞δ1，|f2|＜δ2，|f3|＜δ3Judging that the system oil return pressure is abnormal, and checking whether a loop pipeline is blocked;
if | f1|＞δ1，|f2|＞δ2，|f3|＜δ3Judging that the hydraulic cylinder has a leakage fault, and checking the hydraulic cylinder;
if | f1|＜δ1，|f2|＜δ2，|f3|＞δ3Judging that the servo valve/proportional valve is in fault, and checking the valve;
wherein each fault determination value delta1,δ2,δ3Are all constants.
The invention has the beneficial effects that:
1) the method can monitor the running state of the system in real time under the condition that unknown time-varying external load, nonlinearity and uncertain parameters exist in the valve control cylinder system, effectively judge whether the system has faults on line, and further estimate the position and the size of the fault, thereby being more beneficial to acquiring fault information, rapidly analyzing and processing the faults and reducing economic loss;
2) the problem of space and cost caused by the fact that an extra sensor is needed to be added to measure the external load force in the traditional method is solved, the problem that the accuracy of fault diagnosis is influenced due to inaccuracy caused by measurement and estimation of the external load force is also solved, the integrated process of online detection, positioning and estimation of system faults is realized, an online fault diagnosis system of the valve control cylinder electro-hydraulic servo system is established, and early diagnosis of the system faults is facilitated;
3) according to the method, the time-varying external load force is measured without installing an additional sensor or estimating the time-varying external load force in advance, and the time-varying external load is decoupled by a mathematical analysis method, so that the cost is saved, the installation trouble is avoided, and the diagnosis accuracy is improved.
4) The method can reduce the sample training amount, does not need to construct a plurality of observers for fault detection and positioning estimation, can realize the fault detection and the judgment of the occurrence position and the type and the estimation of the size by only adopting one fault diagnosis observer, is not influenced by time-varying external loads, has stronger robustness, small online calculation amount and convenient use.
Drawings
FIG. 1 is a schematic structural diagram of a valve-controlled cylinder electro-hydraulic servo system of the present invention;
FIG. 2 is a flow chart of the operation of the fault detection observer of the present invention;
FIG. 3 is an overall flow chart of the present invention;
FIG. 4 is a diagram of a fault detection observer embodying the present invention;
in the figure: 1-hydraulic pump, 2-servo valve/proportional valve, 3-hydraulic cylinder, 4-piston, 5-sensor and 6-controller.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
As shown in fig. 1-4, the valve-controlled cylinder electro-hydraulic servo system includes a hydraulic pump 1, a servo valve/proportional valve 2, a hydraulic cylinder 3 (which may also be a double-rod cylinder), a piston 4, a sensor 5, and a controller 6. A servo valve/proportional valve 2 is connected with the hydraulic cylinder 3, a hydraulic pump 1 is connected with the servo valve/proportional valve 2, and liquidA sensor 5 is arranged on a piston 4 of the pressure cylinder 3, the sensor 5 is connected with a controller 6 through a circuit, and the controller 6 is connected with the servo valve/proportional valve 2 through a circuit; the external load f of the system becomes unknown in time. Inputting a command displacement or speed, outputting an adjusting voltage u to the servo valve/proportional valve 2 by the controller 6 according to the current displacement or speed acquired by the sensor, and generating a valve core displacement x by the servo valve/proportional valve 2vAt a system oil supply pressure of ps+Lower, flow rate q+The pressure p is generated by the servo/proportional valve 2 and then into the left chamber of the hydraulic cylinder 3+By means of the piston 4 (effective area a)+) The load (resulting effective mass m) is pushed to the right. Correspondingly, the flow rate q-Is pushed out of the right cavity of the hydraulic cylinder 3 to generate pressure p-Then via the return line (pressure p)s-) Returning to the tank, the reverse operation is similar, whereby closed loop control is performed to finally achieve the desired displacement or velocity of the piston 4.
The method for detecting, estimating and positioning the online fault of the valve control cylinder electro-hydraulic servo system comprises the following steps:
1) and (3) system nonlinear modeling: establishing a mathematical model of a valve control cylinder electro-hydraulic servo system; selecting a system state variable; establishing a nonlinear state equation of the system;
firstly, carrying out equivalence on each link of the valve control cylinder electro-hydraulic servo system, establishing a flow equation of a servo valve/proportional valve, a dynamic equation of the servo valve/proportional valve, a flow continuity equation of a hydraulic cylinder and a motion force balance equation of a piston of the hydraulic cylinder, and expressing a mathematical model of the whole system by the four equations as follows:
flow equation for servo/proportional valves:
in the formula q±，p±Flow and pressure, p, of two chambers of the hydraulic cylinder, respectivelys+，ps-Supply and return pressure, x, respectivelyvAnd α are servo motorsThe displacement of the valve core of the servo valve/proportional valve deviating from the middle position and the positive covering quantity, k, of the valve corecIs the flow coefficient;
servo valve/proportional valve dynamic equation:
in the formula kvAnd τ is a gain and time coefficient describing the dynamic characteristics of the servo valve/proportional valve, and u is the input voltage;
flow continuity equation for hydraulic cylinder:
a±and V±Respectively the area and effective volume of two chambers of the hydraulic cylinder, ci,ceRespectively the internal and external leakage coefficients, x, of the hydraulic cylinderpFor cylinder piston displacement, βeFor effective bulk modulus, p+And p-The pressure of the left cavity and the right cavity of the hydraulic cylinder is used;
the motion force balance equation of the hydraulic cylinder piston is as follows:
where m is the total mass converted to load, bpFor viscous damping coefficient, f is the external load force acting on the piston, d is the variable load disturbance force, a+And a-The area of two cavities of the hydraulic cylinder;
selecting a system state variable: selecting the moving speed of the piston of the hydraulic cylinderLeft and right two-cavity pressure p of hydraulic cylinder+And p-And spool displacement x of servo valve/proportional valvevFor the state variables of the system, defining the state variables of the system as
Establishing a nonlinear state equation of the system: the voltage input into the servo valve/proportional valve is taken as input u, and the movement speed of the piston of the hydraulic cylinder is definedLeft and right two-cavity pressure p of hydraulic cylinder+And p-As an output vectorThe flow equation of the servo valve/proportional valve, the dynamic equation of the servo valve/proportional valve, the flow continuity equation of the hydraulic cylinder and the motion force balance equation of the hydraulic cylinder piston are subjected to form transformation, a state variable x and a nonlinear term g (x) in the four equations are extracted and converted into the following state equation form, and matrixes A, B, C and D are parameter matrixes of the system;
2) and (3) identifying normal parameters of the system: acquiring input and output historical data under different working conditions and environmental conditions when the system normally operates, inputting an identification model, and obtaining parameters and a variation range thereof when the system normally operates by using the identification model;
given continuously variable servo valve/proportional valve voltage input signal, collecting hydraulic cylinder piston displacement value xpAnd pressure values p of two chambers of the hydraulic cylinder+And p-；
Obtaining a linear equation set containing identification parameters by a nonlinear state equation of the system:
Φθ＝Γ，
θ＝[βe -1cicekq]Tas the parameter to be identified, kq＝kc·kv，
A parameter matrix containing system state quantities, wherein k is 1,2, 3;
substituting the acquired data into the equation set, and identifying the unknown parameter theta in the equation set by adopting a least square method; and substituting the system parameters obtained by identification into a nonlinear state equation of the system, comparing and correcting the obtained output with the actual system output, and finally obtaining the parameter values and the variation range of the system in normal operation.
3) Substituting the data obtained in the step 2) during normal operation of the system into the nonlinear state equation of the system in the step 1) to obtain a normal system parameter matrix and an expression of the nonlinear state equation of the system;
4) acquiring relevant input and output parameters of a system in real time;
5) fault detection and estimation under variable load: establishing a fault detection observer, wherein the fault detection observer comprises an external load force decoupling module, a fault dominant module, a nonlinear module, a stability module and a fault vector estimation module, inputting collected module signals into the observer to obtain estimated output of the observer, and obtaining an output residual error by making a difference value with the output of an actual system;
external load force decoupling module: the method mainly realizes the function that the change of the external interference force does not influence the residual error for fault judgment, and comprises the following steps: is provided withThe parameter matrix of the observer, T ═ D (CD)++Y[I-(CD)(CD)+]Wherein (CD)+＝((CD)T(CD))-1(CD)TY is a parameter matrix to be set and is obtained in the stability module, C, D is a system parameter matrix obtained in the step 3), and I is an identity matrix;
a non-linear module: obtaining the non-linear expression g (x) of the original system to observe the state quantityThe original state quantity x is replaced, linear simplification is not needed, and the state quantity x is directly used for processing of a stability module;
a stability module: the method mainly realizes the quick and effective convergence of the observer, and comprises the following steps:
a: obtaining a positive definite symmetric matrix P by solving the following linear matrix inequality>0, and two matricesWherein P is1＝P(I+TaC),Ta＝-D(CD)+,Tb＝I-(CD)(CD)+γ is a normal number:
b: the matrix Y and the matrix K are obtained by calculation,and
c: obtaining other observer parameter matrixes, wherein G is MB, N is MA-KC, and L is K-NT;
a residual generation module: output signals of the actual system (including the piston speed signal value of the hydraulic cylinder)And the pressure signal value p of two cavities of the hydraulic cylinder+And p-Composed output vectorAnd the observer output vectorSubtracting to obtain an output residual vector
A fault vector estimation module: the fault vector estimation module is composed of a neural network, does not work when the residual error is less than or equal to the threshold value, and is activated only when the residual error is greater than the threshold value so as to carry out fault estimation.
The above-mentioned matrices T, M, G, N and L are the system parameter matrices to be designed, and the matrices A, B, C and D are the system parameter matrices obtained in step 3);
6) and (3) robust fault decision: inputting the output residual error obtained in the step 3) into an error estimation function, and diagnosing whether the system has a fault or not by combining a self-adaptive threshold value calculated in real time;
the error estimation function is calculated as: j (t) ═ rT(t) hr (t), where H is a weighted diagonal function; fault detection is carried out according to the following rules:
in the formula, lambda (t) is an adaptive threshold value, the adaptive threshold value is composed of two parts, one part is a steady-state threshold value, the other part is a transient threshold value, the switching is carried out according to the acceleration value of a hydraulic cylinder piston, the normal fluctuation of system parameters is taken into consideration when the threshold value is set, the threshold value is calculated on line based on a statistical method, in addition, the data calculation amount and the storage space are reduced by carrying out a segmented weighting mode on a residual sequence, meanwhile, certain robustness is ensured, and the specific implementation process comprises the following steps:
a: substituting the parameter variation range obtained by the identification model in the step) 2 during normal operation of the system into a fault detection and estimation observer to obtain a steady state threshold value fluctuation range, and taking the upper and lower limits of fluctuation as a steady state threshold value lambdao-，λo+；
b: carrying out difference on the obtained piston velocity values or carrying out twice difference on the position values to obtain a piston motion acceleration value aP(t)；
c: respectively obtaining a residual error r with the length of Si(k) Sequence pair and piston acceleration ai(k) Wherein i ═ k-1) S/l +1, …, (k-1) S/l + S, and calculating the piston mean a of the acceleration sequence of this S datap(k)；
d: residual error sequence r of S data lengthi(k) Dividing into one part, calculating the mean value mu of each part with S/l residual datap(k) Then, the weighted mean μ is calculated according to the following formular(k) Sum variance σr 2(k)；
Wherein wpAre assigned good weight coefficients, and
e: determining an adaptive threshold λ (k) from the following equation;
where ε is the bandwidth factor, caIs a critical value of the acceleration;
f: and repeating the steps and calculating the threshold lambda in real time.
7) Starting a fault vector estimation module in the step 5) of the fault detection observer, and carrying out real-time adjustment on a network weight coefficient by using a residual error value output by the observer and an actual system to finally obtain a fault vector estimation value;
the fault vector estimation module is implemented by the following specific processes: setting a reasonable neural network structure, wherein the number of network input nodes, hidden layer nodes and output nodes is n + m, s and n respectively, wherein n and m are the state quantity and the input quantity of the fault diagnosis observer, the number of hidden layers is determined offline, the input quantity of the neural network is the estimated value of the system state quantity and the input voltage of a servo valve/proportional valve, and establishing the neural networkWherein W is the output weight coefficient matrix of the neural network to be designed,is a neural network basis function;
obtaining state estimators of fault diagnosis observer in real timeAnd the output residual vector rn(t) real-time adjustment of the neural network output weight coefficients according to the following equationWhere the parameter matrix η is a positive constant, P is a positive constant matrix, and u is the input voltage of the servo valve/proportional valve;
recording the output value of the neural network at the moment as the current fault vector estimated value f (t) ═ fnn(t)；
Obtaining an observer estimated output vector after starting a neural network fault vector estimation moduleAnd obtaining an output residualWhere y (t) is the actual output vector;
detecting the output residual rn(t) if rn(t)＞λn(t) returning to step 6) if rn(t)≤λn(t) proceeding to the next step, wherein lambdan(t) determining an adaptive threshold for the fault estimation;
the estimated value of the output fault vector is f (t) ═ f1f2f3]T。
8) Fault isolation and positioning: and (4) judging the type and position of the possible fault by combining the fault vector estimated value and the motion direction of the hydraulic cylinder piston, and outputting a diagnosis result.
Based on the fault estimation vector f (t) ═ f1f2f3]TThe fault positioning method comprises the following steps:
when, | f1＞δ1，|f2|＜δ2，|f3|＜δ3Or,when, | f1|＜δ1，|f2|＞δ2，|f3|＜δ3Judging that the system oil supply pressure is abnormal, and checking the hydraulic pump and the pump outlet overflow valve;
when, if | f1|＜δ1，|f2|＞δ2，f3|＜δ3Or,when, | f1|＞δ1，|f2|＜δ2，|f3|＜δ3Judging that the system oil return pressure is abnormal, and checking whether a loop pipeline is blocked;
if | f1|＞δ1，|f2|＞δ2，|f3|＜δ3Judging that the hydraulic cylinder has a leakage fault, and checking the hydraulic cylinder;
if | f1|＜δ1，|f2|＜δ2，|f3|＞δ3Judging that the servo valve/proportional valve is in fault, and checking the valve;
wherein each fault determination value delta1,δ2,δ3Are all constants.
By the method, the running state of the system is effectively judged under the condition of not needing to measure or estimate the external load force, the existing fault is detected, the size of the fault can be estimated, the position and the type of the fault are judged, and the method is very economical, simple and convenient for practical application and high in reliability.
The invention discloses a fault detection observer which is a key point in construction and comprises an external load force decoupling module, a fault dominant module, a nonlinear module, a stability module, a residual error generation module and a fault vector estimation module. The external load force decoupling module is used for effectively decoupling an unknown time-varying external load, so that the unknown time-varying external load does not influence residual errors for fault judgment; the fault dominant module is used for reflecting system fault information in residual errors so as to judge faults; the nonlinear module is mainly used for processing the nonlinear relation of the system; the stability module is used for realizing the quick and effective convergence of the fault detection observer; the residual error generating module is used for generating a residual error for fault judgment; the fault vector estimation module is composed of a neural network, does not work when the residual error is less than or equal to the threshold value, and is activated only when the residual error is greater than the threshold value so as to carry out fault estimation. Through the cooperation of the modules, the time-varying external load and the system nonlinearity can be effectively processed, and the accuracy of fault detection and estimation is improved.
The invention has the advantages that the time-varying external load force is decoupled by a mathematical analysis method without installing an additional sensor to measure the magnitude of the time-varying external load force or estimating the magnitude of the time-varying external load force in advance, so that the cost is saved, the installation trouble is avoided, and the diagnosis accuracy is improved. Meanwhile, the invention can reduce the sample training amount, does not need to construct a plurality of observers for fault detection and positioning estimation, can realize the fault detection, the judgment of the occurrence position and the type and the size estimation by only adopting one fault diagnosis observer, is not influenced by time-varying external loads, has stronger robustness, small online calculation amount and convenient use.
Claims (7)
1. The invention relates to an on-line fault detection, estimation and positioning method of a valve control cylinder electro-hydraulic servo system, which is based on the valve control cylinder electro-hydraulic servo system, wherein the valve control cylinder electro-hydraulic servo system comprises a hydraulic cylinder, a servo valve/a proportional valve connected with the hydraulic cylinder and a hydraulic pump connected with the servo valve/the proportional valve, a sensor is arranged on a piston of the hydraulic cylinder, the sensor is connected with a controller through a circuit, and the controller is connected with the servo valve/the proportional valve through a circuit;
the method is characterized by comprising the following steps:
1) and (3) system nonlinear modeling: establishing a mathematical model of a valve control cylinder electro-hydraulic servo system; selecting a system state variable; establishing a nonlinear state equation of the system;
2) and (3) identifying normal parameters of the system: acquiring input and output historical data under different working conditions and environmental conditions when the system normally operates, inputting an identification model, and obtaining parameters and a variation range of the parameters when the system normally operates by using the identification model;
3) substituting the data obtained in the step 2) during normal operation of the system into the nonlinear state equation of the system in the step 1) to obtain a normal system parameter matrix and an expression of the nonlinear state equation of the system;
4) acquiring relevant input and output parameters of a system in real time;
5) fault detection and estimation under variable load: establishing a fault detection observer, wherein the fault detection observer comprises an external load force decoupling module, a fault dominant module, a nonlinear module, a stability module and a fault vector estimation module, inputting collected module signals into the observer to obtain estimated output of the observer, and obtaining an output residual error by making a difference value with the output of an actual system;
6) and (3) robust fault decision: inputting the output residual error obtained in the step 3) into a calculation error estimation function, and diagnosing whether the system has a fault or not by combining a self-adaptive threshold value calculated in real time;
7) if no fault exists in the step 6), returning to the step 4); if the fault occurs, starting a fault vector estimation module of the fault detection observer in the step 5), and obtaining an output residual error value by the observer and an actual system to carry out real-time adjustment on a network weight coefficient so as to finally obtain a fault vector estimation value;
8) fault isolation and positioning: and (4) judging the type and position of the possible fault by combining the fault vector estimated value in the step 7) and the motion direction of the hydraulic cylinder piston, and outputting a diagnosis result.
2. The method for detecting, estimating and positioning the online fault of the valve control cylinder electro-hydraulic servo system according to claim 1, wherein a mathematical model of the valve control cylinder electro-hydraulic servo system is established in the step 1): firstly, carrying out equivalence on each link of the valve control cylinder electro-hydraulic servo system, establishing a flow equation of a servo valve/proportional valve, a dynamic equation of the servo valve/proportional valve, a flow continuity equation of a hydraulic cylinder and a motion force balance equation of a piston of the hydraulic cylinder, and expressing a mathematical model of the whole system by the four equations as follows:
flow equation for servo/proportional valves:
in the formula q±，p±Flow and pressure, p, of two chambers of the hydraulic cylinder, respectivelys+，ps-Supply and return pressure, x, respectivelyvAnd α are respectively the displacement of the servo valve/proportional valve core from the neutral position and the positive covering quantity, k of the valve corecIs the flow coefficient;
servo valve/proportional valve dynamic equation:
in the formula kvAnd τ is a gain and time coefficient describing the dynamic characteristics of the servo valve/proportional valve, and u is the input voltage;
flow continuity equation for hydraulic cylinder:
a±and V±Respectively the area and effective volume of two chambers of the hydraulic cylinder, ci,ceRespectively the internal and external leakage coefficients, x, of the hydraulic cylinderpFor cylinder piston displacement, βeFor effective bulk modulus, p+And p-The pressure of the left cavity and the right cavity of the hydraulic cylinder is used;
the motion force balance equation of the hydraulic cylinder piston is as follows:
where m is the total mass converted to load, bpFor viscous damping coefficient, f is the external load force acting on the piston, d is the variable load disturbance force, a+And a-The area of two cavities of the hydraulic cylinder;
selecting a system state variable: selecting the moving speed of the piston of the hydraulic cylinderLeft and right two-cavity pressure p of hydraulic cylinder+And p-And spool displacement x of servo valve/proportional valvevFor the state variables of the system, defining the state variables of the system as
Establishing a nonlinear state equation of the system: the voltage input into the servo valve/proportional valve is taken as input u, and the movement speed of the piston of the hydraulic cylinder is definedLeft and right two-cavity pressure p of hydraulic cylinder+And p-As an output vectorThe flow equation of the servo valve/proportional valve, the dynamic equation of the servo valve/proportional valve, the flow continuity equation of the hydraulic cylinder and the motion force balance equation of the hydraulic cylinder piston are subjected to form transformation, a state variable x and a nonlinear term g (x) in the four equations are extracted and converted into the following state equation form, and matrixes A, B, C and D are parameter matrixes of the system;
3. the valve controlled cylinder electric according to claim 1The online fault detection, estimation and positioning method of the liquid servo system is characterized in that input and output historical data under different working conditions and environmental conditions in normal operation of the system are acquired in the step 2): given continuously variable servo valve/proportional valve voltage input signal, collecting hydraulic cylinder piston displacement value xpAnd pressure values p of two chambers of the hydraulic cylinder+And p-；
Identifying the model: obtaining a linear equation set containing identification parameters by a nonlinear state equation of the system:
Φθ＝Γ，
θ＝[βe -1cicekq]Tas the parameter to be identified, kq＝kc·kv，
A parameter matrix containing system state quantities, wherein k is 1,2, 3;
substituting the acquired data into the equation set, and identifying the unknown parameter theta in the equation set by adopting a least square method; and substituting the system parameters obtained by identification into a nonlinear state equation of the system, comparing and correcting the obtained output with the actual system output, and finally obtaining the parameter values and the variation range of the system in normal operation.
4. The on-line fault detection, estimation and positioning method of the valve control cylinder electro-hydraulic servo system under the variable load according to claim 1, characterized in that in the step 5), an external load force decoupling module: the method mainly realizes the function that the change of the external interference force does not influence the residual error for fault judgment, and comprises the following steps: setting the parameter matrix T ═ D (CD) of the observer++Y[I-(CD)(CD)+]Wherein (CD)+＝((CD)T(CD))-1(CD)TY is a parameter matrix to be setObtained in the stability module, C, D is the system parameter matrix obtained in step 3), I is the identity matrix;
a fault dominant module: the method mainly realizes the function that once a fault occurs in the system, the residual error for fault judgment is influenced, and the method comprises the following steps: set parameter matrix M ═ I + TC, and MFfNot equal to 0, wherein FfIs a fault matrix expressed as Ff＝[e1e2e3]，ei＝[0 ei1ei2ei3]T，
A non-linear module: obtaining the non-linear expression g (x) of the original system to observe the state quantityThe original state quantity x is replaced, linear simplification is not needed, and the state quantity x is directly used for processing of a stability module;
a stability module: the method mainly realizes the quick and effective convergence of the observer, and comprises the following steps:
a: obtaining a positive definite symmetric matrix P by solving the following linear matrix inequality>0, and two matricesWherein P is1＝P(I+TaC),Ta＝-D(CD)+,Tb＝I-(CD)(CD)+γ is a normal number:
b: the matrix Y and the matrix K are obtained by calculation,and
c: obtaining other observer parameter matrixes, wherein G is MB, N is MA-KC, and L is K-NT;
a residual generation module: output signals of the actual system (including the piston speed signal value of the hydraulic cylinder)And the pressure signal value p of two cavities of the hydraulic cylinder+And p-Composed output vectorAnd the observer output vectorSubtracting to obtain an output residual vector
A fault vector estimation module: the fault vector estimation module is composed of a neural network, does not work when the residual error is less than or equal to a threshold value, and is activated only when the residual error is greater than the threshold value so as to carry out fault estimation;
the above-mentioned matrices T, M, G, N and L are the system parameter matrices to be designed, and the matrices A, B, C and D are the system parameter matrices obtained in step 3).
5. The method for detecting, estimating and positioning the online fault of the valve control cylinder electro-hydraulic servo system according to claim 1, wherein the error estimation function calculated in the step 6) is as follows: j (t) ═ rT(t) hr (t), where H is a weighted diagonal function;
fault detection is carried out according to the following rules:
in the formula, lambda (t) is an adaptive threshold value, the adaptive threshold value is composed of two parts, one part is a steady-state threshold value, the other part is a transient threshold value, the switching is carried out according to the acceleration value of a hydraulic cylinder piston, the normal fluctuation of system parameters is taken into consideration when the threshold value is set, the threshold value is calculated on line based on a statistical method, in addition, the data calculation amount and the storage space are reduced by carrying out a segmented weighting mode on a residual sequence, meanwhile, certain robustness is ensured, and the specific implementation process comprises the following steps:
a: substituting the parameter variation range of the system obtained by the identification model in the step 2) during normal operation into a fault detection observer to obtain a steady state threshold value fluctuation range, and taking the upper and lower limits of fluctuation as a steady state threshold value lambdao-，λo+；
b: carrying out difference on the obtained piston velocity values or carrying out twice difference on the position values to obtain a piston motion acceleration value aP(t)；
c: respectively obtaining a residual error r with the length of Si(k) Sequence pair and piston acceleration ai(k) Wherein i ═ k-1) S/l +1, …, (k-1) S/l + S, and calculating the piston mean a of the acceleration sequence of this S datap(k)；
d: residual error sequence r of S data lengthi(k) Dividing into one part, calculating the mean value mu of each part with S/l residual datap(k) Then, the weighted mean μ is calculated according to the following formular(k) Sum variance σr 2(k)；
Wherein wpAre assigned good weight coefficients, and
e: determining an adaptive threshold λ (k) from the following equation;
where ε is the bandwidth factor, caIs a critical value of the acceleration;
f: and repeating the steps and calculating the threshold lambda in real time.
6. The method for detecting, estimating and positioning the online fault of the valve-controlled cylinder electro-hydraulic servo system according to claim 1, wherein the fault vector estimation module in the step 7) is implemented by:
setting a reasonable neural network structure, wherein the number of network input nodes, hidden layer nodes and output nodes is n + m, s and n respectively, wherein n and m are the state quantity and the input quantity of the fault diagnosis observer, the number of hidden layers is determined offline, the input quantity of the neural network is the estimated value of the system state quantity and the input voltage of a servo valve/proportional valve, and establishing the neural networkWherein W is the output weight coefficient matrix of the neural network to be designed,is a neural network basis function;
obtaining state estimators of fault diagnosis observer in real timeAnd the output residual vector rn(t) real-time adjustment of the neural network output weight coefficients according to the following equationWhere the parameter matrix η is a positive constant, P is a positive constant matrix, and u is the input voltage of the servo valve/proportional valve;
recording the nerve at that timeThe network output value is used as the current fault vector estimated value f (t) ═ fnn(t)；
Obtaining an observer estimated output vector after starting a neural network fault vector estimation moduleAnd obtaining an output residualWhere y (t) is the actual output vector;
detecting the output residual rn(t) if rn(t)＞λn(t) returning to step 6) if rn(t)≤λn(t) proceeding to the next step, wherein lambdan(t) determining an adaptive threshold for the fault estimation;
the estimated value of the output fault vector is f (t) ═ f1f2f3]T。
7. The method for detecting, estimating and positioning the online fault of the valve-controlled cylinder electro-hydraulic servo system according to claim 1, wherein the fault type and position in the step 8) are judged as follows:
based on the fault estimation vector f (t) ═ f1f2f3]TThe fault positioning method comprises the following steps:
when, | f1＞δ1，|f2|＜δ2，|f3|＜δ3Or,when, | f1|＜δ1，|f2|＞δ2，|f3|＜δ3Judging that the system oil supply pressure is abnormal, and checking the hydraulic pump and the pump outlet overflow valve;
when, if | f1|＜δ1，|f2|＞δ2，|f3|＜δ3Or,when, | f1|＞δ1，|f2|＜δ2，|f3|＜δ3Judging that the system oil return pressure is abnormal, and checking whether a loop pipeline is blocked;
if | f1|＞δ1，|f2|＞δ2，|f3|＜δ3Judging that the hydraulic cylinder has a leakage fault, and checking the hydraulic cylinder;
if | f1|＜δ1，|f2|＜δ2，|f3|＞δ3Judging that the servo valve/proportional valve is in fault, and checking the valve; wherein each fault determination value delta1，δ2，δ3Are all constants.
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