CN102628738A - State monitoring and failure diagnosis system for thick plate mill AGC servo valve - Google Patents
State monitoring and failure diagnosis system for thick plate mill AGC servo valve Download PDFInfo
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Abstract
The invention relates to a state monitoring and failure diagnosis system for a thick plate mill AGC servo valve. The system comprises a diagnosis operation module, a diagnosis result display module, an information input module, a historical data analysis module and a neural network training module, wherein the diagnosis operation module reads the text file to be tested, performs diagnosis and transmits the diagnosis result to the diagnosis result display module; the diagnosis result comprises the health degree tendency of the servo valve and the current operation state represented by the health degree; the information input module inputs the information of a new valve when the mill exchanges the new servo valve; the neural network training module is used for training the data of the new servo valve and inputting the result into a knowledge base; and the historical data analysis module can check the related information such as the historical operation state and the like of the selected valve. The system has the functions of automatically diagnosing state failure and storing and checking historical data and provides real-time guarantee for finding system failure and exchanging the servo valve timely so as to reduce loss caused by equipment failure to the maximum degree.
Description
Technical field
The present invention relates to a kind of rolling mill hydraulic AGC system, specifically is a kind of heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system.
Background technology
Thereby band mill is to make rolled piece produce a kind of stress metal processing machine of expection thick plates band through the roll with certain roll gap.In plate strip rolling process, the dimensional accuracy of thickness of slab is the most important quality index that must guarantee, and rolling mill hydraulic AGC system is the important means of modern strip-mill strip thickness of slab precision control, the control of plate shape.The AGC system is according to the actual measurement thickness of slab and require rolling thickness ratio than its deviation, and through the control of servo-valve system, the adjustment depress oil cylinder is to reach desired outlet thickness of slab.
Rolling mill hydraulic AGC system is that control is complicated, load force is big, disturbance concerns complicacy, control accuracy and the exigent equipment of response speed; And the raising day by day with milling train automatization level and board quality require requires also increasingly high to the rolling mill hydraulic AGC system control performance.The serviceability quality of hydraulic AGC system and reliability just directly influence the operate as normal of whole rolling, influence the quality of product.And electrohydraulic servo valve is the key element of hydraulic AGC system, and its property relationship also directly has influence on the reliability and the life-span of total system work to the control accuracy and the response speed of total system.
Electrohydraulic servo valve requires accurate, and cost is more expensive, and system requires high to the actuating medium cleanliness, and the management maintenance expense is bigger, is the position of breaking down the most easily in the electrohydraulic servo system, and its Performance And Reliability will directly influence the Performance And Reliability of system.The research of carrying out electrohydraulic servo valve intelligent fault diagnosis aspect can improve the reliability and the security of whole AGC system; Guarantee the normal good production order and product quality; In the serviceable life of prolongation equipment, reduce maintenance cost, the modernization of puopulsion equipment maintenance system and mode.Otherwise, if in a single day hydraulic AGC system breaks down, will cause shutdown or influence product quality, can bring enormous economic loss.
Electrohydraulic servo valve itself is to combine mechanical, electrical, three kinds of technology of liquid in the precision element of one, and its fault shows as the complicated coupling of mechanical fault, electric fault, hydraulic fault usually, and these bring certain degree of difficulty for relevant fault diagnosis work.Electrohydraulic servo valve is one of parts complicated with the most crucial in the hydraulic system, and electrohydraulic servo valve intelligent maintenance technology and level are the important reflections of hydraulic system maintenance technology and level.
Literature search through to prior art is found; Chinese patent (patent No. CN101183050) proposes a kind of electrohydraulic servo valve dynamic performance high precision measurement method based on displacement measurement; Adopt displacement transducer as no-load oil cylinder motion detection elements, displacement signal and current signal are tested electrohydraulic servo valve dynamic performance through processing and correlation analysis.Toshiba Corporation's patent (patent No. CN1519480) proposes a kind of servo valve control device that is used to control the servo-valve aperture; So that make the servo-valve aperture meet a target through importing the actual servo-valve aperture and the signal of servo-valve aperture desired value; This control device has a controller; It is configured to receive the difference signal between servo-valve aperture desired value and the actual servo valve opening, and produces the servo command signal that is used to drive this servo-valve.But the semaphore that above-mentioned patent adopts is more single, does not provide the current running status of servo-valve, and lacks the performance degradation prediction.
Summary of the invention
The present invention is directed to the deficiency of prior art; A kind of heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system is proposed; Make it possess status fault self diagnosis and history data store and look facility; Discovery to the system failure provides real-time guarantee with the timely servo-valve of changing, in the hope of farthest reducing the loss that equipment failure causes.
The present invention realizes through following technical scheme; The present invention includes following five modules: diagnostic operation module, diagnostic result display module, MIM message input module, historical data analysis module and neural metwork training module, before the operation of said system at first with the opening degree signal of the displacement of roll-force, transmission side and the fore side of sensor acquisition milling train and the servo-valve online text that is stored as also; Wherein:
Said MIM message input module carries out typing and preserves data new valve information when milling train exchanges new servo-valve for, for said diagnostic operation module invokes;
Said neural metwork training module adopts neural network that these data are trained the result is added knowledge base, and the data that will train supplies said diagnostic operation module invokes when new servo-valve data are arranged;
Said diagnostic operation module reads text to be tested, or/and the data of said MIM message input module and said neural metwork training module diagnose servo-valve, and sends to said diagnostic result display module to the result;
Said diagnostic result display module then shows date, valve number, location number, diagnostic result and the health degree information of servo-valve; Said health degree is the index that characterizes the servo-valve operating position, and its scope is 0～1,0 expression worst state, 1 expression optimum condition;
Said historical data analysis module provides the history run state information searching of a certain valve.
Said MIM message input module mainly is responsible for changing after the new servo-valve for the typing of new servo-valve information, can import machine time on the servo-valve, numbering and go up the machine location number, and preserve after according to the information of input valve being sorted.Through the relevant information that this module can be preserved used servo-valve, be convenient to the accurate judgement of diagnostic procedure, also can be provided with post analysis and use.
Said neural metwork training module comprises Data Update submodule and network training submodule; When new servo-valve data are arranged; Said network training submodule adopts neural network that these data are carried out network training; Result after said Data Update submodule will be trained is updated to knowledge base, supplies said diagnostic operation module invokes.The knowledge base of servo-valve presence is integrated in the system, filters out representative data through present existing data by the requirement of characteristic quantity.The representational quality of knowledge base data is closely related with the accuracy of diagnosis of system height and travelling speed speed.Knowledge base has the function of dilatation and upgrading, thereby has improved the adaptability of system and equipment working condition.
Said diagnostic operation module comprises data reading submodule and data diagnosis submodule, and said data reading submodule is used for choosing the text that needs test, the date of judgment data and will data transfer wherein show to diagnostic result in time variable; After handling, the data that said data diagnosis submodule reads the data reading submodule obtain characterizing the proper vector of servo-valve working condition.
Said diagnostic result display module comprises diagnostic result display sub-module and health degree curve display submodule, and the diagnostic result that said diagnostic result display sub-module shows comprises date demonstration, valve number demonstration, valve position number demonstration, health degree numerical value shows and the last diagnostic result shows; Said health degree curve display submodule shows the nearest 10 days health degree situation of this valve.Can see servo-valve health degree trend and current situation intuitively through said diagnostic result display module.
Said historical data analysis module comprises 1# valve data, 2# valve data, 3# valve data three sub-module; Select a certain valve data submodule; Then in the window that ejects, show servo-valve health degree curve, and show the location number, valve number of this valve at the title place and use commencement date and deadline with the broken line graph mode.
Compared with prior art; The present invention has following beneficial effect: the present invention combines artificial intelligence technology, knowledge base technology and computer technology; Realize servo-valve health degree state-detection and fault diagnosis generally, greatly reduced the occurrence frequency of fault, ensured equipment, product and related personnel's safety; Reduce maintenance workload and maintenance cost, thereby promoted the competitive power of manufacturing enterprise.
Description of drawings
Fig. 1 is heavy plate mill AGC alliance control principle figure;
Fig. 2 is the structured flowchart of one embodiment of the invention.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated: present embodiment provided detailed embodiment and process, but protection scope of the present invention is not limited to following embodiment being to implement under the prerequisite with technical scheme of the present invention.
Shown in accompanying drawing 1, be general thick plate mill AGC alliance control principle figure, system is according to the actual measurement thickness of slab and require rolling thickness ratio than its deviation, and through the control of servo-valve system, the adjustment depress oil cylinder is to reach desired outlet thickness of slab.
Before the operation of the said heavy plate mill AGC of present embodiment servo-valve condition monitoring and failure diagnosis system; At first to use the sensor acquisition signal data; Be respectively the piston side of depressing cylinder and HAD 3840 pressure transducers that the bar side is arranged like parts among Fig. 14 and 5, can detect the pressure changing of depressing in the cylinder thus.Possibly occur crookedly when rising because of the piston of depressing cylinder, for eliminating the crooked detection error that produces, two SONY HA-705-LK 907/MSS-976-R magnetic grids 6,7 are housed in the both sides of depressing cylinder, the mean value of fetch bit shifting signal is controlled.Adopt this method that the servo-valve data are gathered, and the online text that deposits in of while.
As shown in Figure 2, present embodiment provides a kind of heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system to comprise following five modules: diagnostic operation module, diagnostic result display module, MIM message input module, historical data analysis module and neural metwork training module.Wherein:
Said MIM message input module carries out typing and preserves data new valve information when milling train exchanges new servo-valve for, for said diagnostic operation module invokes;
Said neural metwork training module adopts neural network that these data are trained the result is added knowledge base, and the data that will train supplies said diagnostic operation module invokes when new servo-valve data are arranged;
The data text to be tested that said diagnostic operation module reads prior collection or/and the data of said MIM message input module and said neural metwork training module diagnose servo-valve, and sends to said diagnostic result display module to the result;
Said diagnostic result display module then shows date, valve number, location number, diagnostic result and the health degree information of servo-valve;
Said historical data analysis module provides the history run state information searching of a certain valve.
Below concrete realization of each module of present embodiment is elaborated:
1. diagnostic operation module, this is the main user's operating area of system, this module is delivered to data processing diagnosis back in the diagnostic result display module to diagnostic result information and shows.It comprises data reading submodule and data diagnosis submodule.
A) data reading submodule; Read button control through data, its role is to read the text of data to be tested, the data file of general every day reads 5; Constantly judge when reading that the vector that reads in data, date, valve number be whether identical and whether invalid data is arranged; And rolling number of times must not be less than 10 times in the file that requires at every turn to read, if above-mentioned situation then stops these data and reads.If reading of data is correct, then with all data transfer give in the data diagnosis submodule to dependent variable.
B) data diagnosis submodule, through the data diagnosis button control, its effect is that the data that read are handled, and judges its health status.Particularly be exactly to judge that at first the location number of valve is 1#, 2# or 3#, handle to transmission side and fore side respectively then, extract final characteristic quantity: the displacement difference average, opening degree average, peak value, several are several and pass through number of times greatly.
Said displacement difference average is meant that transmission side and fore side depress the mean value of difference in height in an operation of rolling, is characterizing the average case of steel rolling thickness difference;
The opening degree of said valve is meant valve core of servo valve displacement and maximum displacement ratio, and the corresponding opening degree was 1 when the spool positive-displacement was maximum, and when negative sense was maximum, the corresponding opening degree was-1.Its average and peak value characterize once the mean value and the maximal value of rolling middle spool relative displacement respectively.Through the lot of data analysis, find the threshold line of an opening degree, operation of rolling split shed degree surpasses counting of this threshold line and is big several numbers of opening degree, and the number of times that broken line graph passes threshold line is and passes through number of times, characterizes the fluctuation situation of opening degree.Carry out emulation with the neural network that trains after extracting characteristic quantity, draw the health degree value, use clustering algorithm to draw the last diagnostic result according to data cases a few days ago then.
2. diagnostic result display module, in servo-valve health degree state-detection process, system all can show at the diagnostic result display module process and result that the data that detect read, analyze and handle.It comprises diagnostic result display sub-module and health degree curve display submodule.The two moves simultaneously, and system works process and diagnostic result are fed back to the user intuitively.
A) diagnostic result display sub-module comprises that the demonstration of servo-valve work date, valve number demonstration, servo-valve location number show, health degree numerical value shows and the last diagnostic result shows.The last diagnostic result has three kinds of situation: normal, fault and undetermined.Normal expression servo-valve each side data presentation is normal, and a certain index of representation for fault servo-valve occurs unusual, and system breaks down, and valve is changed in suggestion.Undetermined be meant this diagnosis with last time the diagnosis differ bigger, can't judge servo-valve health degree state.
B) health degree curve display submodule is represented servo-valve health degree state with broken line graph, and horizontal ordinate is the use date (then all show if use the date to be less than ten days, then showed ten days more than ten days) of this valve, and ordinate is a health degree numerical value.Also have a threshold line among the figure, be the roughly separatrix of health degree numerical value.Transmission side and fore side health degree with the curve display of different colours in same figure.The user can see the tendency of servo-valve health degree curve very intuitively through this figure.
3. MIM message input module mainly is to prepare the data in early stage for diagnostic operation module and diagnostic result display module, after changing new servo-valve, needs the typing of relevant information, to make things convenient for calling and judge in the monitoring, diagnosing process.This module needs the information of typing to comprise: machine time, numbering and last machine location number on the servo-valve.Click after input finishes and preserve after preservation is then sorted valve according to the information of importing.
4. historical data analysis module; This module is to relatively lag behind and module independently; It is the health degree situation of using the valve of (comprise and using) in order to check; Mainly comprise 1# valve data, 2# valve data, three buttons of 3# valve data and corresponding drop-down menu, select in the window that ejects, to show servo-valve health degree curve behind a certain valve, and show the location number, valve number of this valve at the title place and use commencement date and deadline with the broken line graph mode.As: 2# transmission side 461 servo-valve health degree data, use date: 2009.10.1-200912.20.Can carry out associative operation to this data plot at toolbar, as preserving, amplify, dwindle etc.
5. the neural metwork training module is relevant with the upgrade function of system.The effect of neural metwork training is directly connected to the performance of system, so this module is a vital link in the system.
A) network training submodule; At first select typical data; The rolling situation of observation steel plate in data acquisition; Pick out the data that rolling situation is comparatively stable and break down, the failure cause of Dual Injector Baffle formula electrohydraulic servo valve has the demagnetization of little ball wear, permanent magnet, valve pocket seal wear, the wearing and tearing of main valve plug seamed edge, main valve plug gauge wear, the stuck clamping stagnation of main valve plug, spray nozzle clogging, throttle orifice obstruction, the obstruction of inner filter core and the interior electronic circuit fault of valve etc.Wherein topmost failure mode can reduce three major types, is respectively obstruction type fault, clamping stagnation type fault and leakage type fault in the servo-valve.Then these data that break down are analyzed; Extract the fault signature amount, comprise the displacement difference average, opening degree average, peak value, several numbers and pass through number of times greatly; Servo-valve to operate as normal also extracts same characteristic quantity simultaneously, adopts the BP neural network function to train then.
B) Data Update submodule is updated to knowledge base during with the fructufy of network training submodule, can make knowledge base constantly carry out dilatation and upgrading like this, thereby improve the adaptability of system and equipment working condition.Dilatation and upgrade function need under complete MATLAB environment, to accomplish.
In the present embodiment; Before the module operation, at first adopt sensor signal (mainly comprising roll-force, displacement difference, transmission side and fore side opening degree etc.) to be gathered and the online text that deposits in of while; In the diagnostic operation module, click ' reading of data ' button then; Read text data to be tested, read 5 files on the same day continuously, click then ' data diagnosis '; Diagnostic operation module operation finishes, and then shows its diagnostic result (net result and the nearest 10 days health degree situation of this valve of the date of test data, valve number, location number, diagnosis) at the diagnostic result display module.So constantly circulation is carried out, and just can test the health degree situation of every day.When milling train exchanges new servo-valve for, need click ' new valve on machine ' at MIM message input module new valve is carried out the information typing, comprise the location number of machine time, valve number and valve.Check the history run state of a certain valve when needs, then can click in the historical data analysis module related valves and check its relevant information.When the servo-valve operating mode changes or has new data to add knowledge base; Will carry out Data Update and carry out repeatedly neural metwork training in the neural metwork training module; Select the wherein final training result of the reasonable conduct of effect, to keep the accuracy of fault diagnosis.
System of the present invention possesses status fault diagnosis and early warning, warning function; Can judge the health degree state of servo-valve more accurately; To system stable operation real-time guarantee is provided; And to the discovery of fault with change servo-valve quick response is provided, greatly reduced the occurrence frequency of fault, ensured equipment, steel rolling product and related personnel's safety.
Although content of the present invention has been done detailed introduction through above-mentioned preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple modification of the present invention with to substitute all will be conspicuous.Therefore, protection scope of the present invention should be limited appended claim.
Claims (10)
1. a heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system is characterized in that, comprises following five modules: diagnostic operation module, diagnostic result display module, MIM message input module, historical data analysis module and neural metwork training module; The operation of said system is before at first with corresponding signal data of sensor acquisition and the online text that is stored as; Wherein:
Said MIM message input module carries out typing and preserves data new valve information when milling train exchanges new servo-valve for, for said diagnostic operation module invokes;
Said neural metwork training module adopts neural network that these data are trained the result is added knowledge base, and the data that will train supplies said diagnostic operation module invokes when new servo-valve data are arranged;
Said diagnostic operation module reads text to be tested, or/and the data of said MIM message input module and said neural metwork training module diagnose servo-valve, and sends to said diagnostic result display module to the result;
Said diagnostic result display module then shows date, valve number, location number, diagnostic result and the health degree information of servo-valve;
Said historical data analysis module provides the history run state information searching of a certain valve.
2. heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system according to claim 1; It is characterized in that; Said diagnostic operation module comprises data reading submodule and data diagnosis button submodule; Said data reading submodule is used for choosing the text that needs test, and the date of judgment data is also given the time variable in the diagnostic result display module with data transfer wherein; After handling, the data that said data diagnosis submodule reads the data reading submodule obtain characterizing the proper vector of servo-valve working condition.
3. heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system according to claim 1; It is characterized in that said data reading submodule reads the text of data to be tested, the data file of every day reads 5; Constantly judge when reading that the vector that reads in data, date, valve number be whether identical and whether invalid data is arranged; And rolling number of times must not be less than 10 times in the file that requires at every turn to read, if above-mentioned situation then stops these data and reads; If reading of data is correct, then give variable corresponding in the data diagnosis submodule with all data transfer;
Said data diagnosis submodule is handled the data that read; Judge its health status promptly: the location number of at first judging valve is 1#, 2# or 3#; Handle to transmission side and fore side respectively then; Extract final characteristic quantity: displacement difference average, opening degree average, peak value, several numbers and pass through number of times greatly.
4. according to each described heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system of claim 1-3; It is characterized in that; Said diagnostic result display module comprises diagnostic result display sub-module and health degree curve display submodule, and the diagnostic result that said diagnostic result display sub-module shows comprises date demonstration, valve number demonstration, valve position number demonstration, health degree numerical value shows and the last diagnostic result shows; Said health degree curve display submodule shows the nearest 10 days health degree situation of this valve; Can see servo-valve health degree trend and current situation intuitively through said diagnostic result display module.
5. heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system according to claim 4 is characterized in that, said diagnostic result display sub-module, and wherein last diagnostic result has three kinds of situation: normal, fault and undetermined; Normal expression servo-valve each side data presentation is normal, and a certain index of representation for fault servo-valve occurs unusual, and system breaks down, and valve is changed in suggestion; Undetermined be meant this diagnosis with last time the diagnosis differ bigger, can't judge servo-valve health degree state.
6. heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system according to claim 4; It is characterized in that; Said health degree curve display submodule is represented servo-valve health degree state with broken line graph, and horizontal ordinate is the use date of this valve; Then all show if use the date to be less than ten days, then showed ten days more than ten days; Ordinate is a health degree numerical value, and its scope is 0-1, and 0 for the poorest, and 1 is best; Also have a threshold line in the broken line graph, be the separatrix of health degree numerical value; Transmission side and fore side health degree with the curve display of different colours in same figure.
7. according to each described heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system of claim 1-3; It is characterized in that; Said MIM message input module mainly is responsible for changing after the new servo-valve typing for new servo-valve information; This module needs the information of typing to comprise on the input servo-valve machine time, numbering and goes up the machine location number, and preserves after according to the information of input valve being sorted; Through the relevant information that this module can be preserved used servo-valve, be convenient to the accurate judgement of diagnostic procedure, also can be provided with post analysis and use.
8. according to each described heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system of claim 1-3; It is characterized in that; Said neural metwork training module comprises Data Update submodule and network training submodule; Said Data Update submodule carries out Data Update when having new servo-valve data to add knowledge base; Said network training submodule adopts neural network that these data are carried out network training, and the data that will train supply said diagnostic operation module invokes; The knowledge base of servo-valve presence is integrated in the system, filters out representative data through present existing data by the requirement of characteristic quantity; Knowledge base has the function of dilatation and upgrading.
9. heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system according to claim 8; It is characterized in that; Said neural metwork training module is at first selected typical data; The rolling situation of observation steel plate in data acquisition; Pick out the data that rolling situation is comparatively stable and break down, the failure cause of Dual Injector Baffle formula electrohydraulic servo valve has the demagnetization of little ball wear, permanent magnet, valve pocket seal wear, the wearing and tearing of main valve plug seamed edge, main valve plug gauge wear, the stuck clamping stagnation of main valve plug, spray nozzle clogging, throttle orifice to stop up, inner filter core stops up and the interior electronic circuit fault of valve; Wherein topmost failure mode reduces four big types, is respectively electronic circuit fault, obstruction type fault, clamping stagnation type fault and leakage type fault in the servo-valve; Then these data that break down are analyzed; Extract the fault signature amount, comprise the displacement difference average, opening degree average, peak value, several numbers and pass through number of times greatly; Servo-valve to operate as normal also extracts same characteristic quantity simultaneously, adopts the BP neural network function to train then.
10. according to each described heavy plate mill AGC servo-valve condition monitoring and failure diagnosis system of claim 1-3; It is characterized in that; Said historical data analysis module comprises 1# valve data, 2# valve data, 3# valve data three sub-module; Select a certain valve data submodule, then in the window that ejects, show servo-valve health degree curve, and show the location number, valve number of this valve at the title place and use commencement date and deadline with the broken line graph mode.
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