CN101694182A - On-line failure diagnosis, prediction and feedback control method of small/medium size gas turbine and device thereof - Google Patents
On-line failure diagnosis, prediction and feedback control method of small/medium size gas turbine and device thereof Download PDFInfo
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Abstract
The invention discloses an on-line failure diagnosis, prediction and feedback control method of a small/medium size gas turbine and a device thereof, being used for carrying out on-line analysis on parameters representing running states of the gas turbine. The method comprises the following steps: adopting an artificial neural network (ANN) to analyze the operating characteristics of all working conditions of a gas turbine set; constructing an expert analysis database; adopting a fuzzy logic analysis block and combining a Kalman filtering module for failure isolation; constructing a multi-parameter analysis module to carry out on-line detection on the thermal performance and the running state of the gas turbine set; and finally, outputting the setting values of related control parameter by the on-line analysis on the parameters representing the running states of the gas turbine. A dynamic data processor (DSP) is adopted to cure the analysis means into a chip, and the invention can realize accurate evaluation of the states of parts in the gas turbine, improves the availability of equipment, prolongs time between overhaul, enhances the capability of preventing sudden failures and improves the operation level of the gas turbine on the basis of analysis technologies such as failure category, advanced failure analysis methods, failure experts and the like.
Description
Technical field
The present invention relates to On-line Fault diagnosis, prediction and the feedback control of the middle-size and small-size gas turbine engine systems in distributed generation system, mobile power station, aviation Push Technology, high power racing car and the racing boat, specifically, relate to a kind of in/small size gas turbine on-line fault diagnosis, prediction, feedback and device.
Background technique
In recent years, in the world after fully absorbing computer technology, adaptive control technology, novel technique of dynamic measurement, the advanced information processing technology, obtain great successes at gas turbine initial failure diagnosis and prediction technical elements, and aspect practical application, seen blank.Be mainly reflected in: aspect observation and control technology, adopt computer bus technology, the synchronous acquisition technique of multi-channel data, network data to transmit technology, mass data storage and fast recording technology, carry out dynamic acquisition and processing; On the measurement signal parser, extensively adopt advanced technologies such as artificial-intelligent, analysis expert system, dynamic data base, probability and data statistics theory, neuroid, multiple-objection optimization, fuzzy mathematics, wavelet analysis, constitute malfunction monitoring and the model analysis storehouse of estimating; Dynamically and the steady state measurement technical elements, error analysis and the treatment technology that employing high frequency sound sensory technique, noncontact measurement, virtual instrument test, spline-fit combine with least square, realized the purpose that High speed data acquisition and precision are taken into account.Thereby lay a solid foundation for the formation of gas turbine fault diagnosis and fault prediction technology of new generation.
Gas turbine, especially aeroengine are the integrated crystallizations of high technology, owing to be the embodiment of interdiscipline state-of-the-art technology, wherein four key technologies (combustion with reduced pollutants technology, the efficient cooling technology of turbine blade, observing and controlling and fault diagnosis technology are stablized in multistage compressor designing technique, firing chamber) are monopolized by the trans-corporation of west prosperity always, therefore from new notion, the online fault of the own intellectual property of formation China and the proposition of analytical technology are expected to break the blockade in this field.In supporting China's small size gas turbine technical development, play the integrated degree height of measurement and control unit, modular functionality is strong, the advanced analysis storehouse combines with quick fault treatment effect.On the basis of 2000-2009 nearly 200 pieces of papers of ASME meeting of comprehensive summing up and relevant patent report, find the advanced fault diagnosis of small size gas turbine, prediction and controlling method aspect very big innovative space in addition.This invention is based on this purpose proposition.
Summary of the invention
The objective of the invention is to provide a kind of in/small size gas turbine on-line fault diagnosis, prediction, feedback and device, with overcome present in/stable inadequately during the small size gas turbine operation, can't accurately grasp operating all kinds of fault message and the technical problem that causes fault to produce easily.
In order to achieve the above object, technological scheme of the present invention is as follows: in a kind of/and small size gas turbine on-line fault diagnosis, prediction, feedback, comprise the steps: to represent the parameter of gas turbine operation situation, comprise thermal parameter and vibration parameters by the contact measurement method collection; Parameter to described expression gas turbine operation situation is carried out on-line analysis, comprising: adopt the artificial neural network to analyze the roadability of the full operating mode of gas turbine group, move the framework that objective function is provided for performance optimization; The development trend of the system failure is judged in structure analysis expert storehouse, for the accurate differentiation of the service cycle of unit, the displacement of critical component provide policy-making parameter; Adopt the fuzzy logic analysis piece, and carry out Fault Isolation, be used for the diagnosis and the prediction of the inefficacy of fault uncertainty, variability and sensor test signal in conjunction with the Kalamn filtering module; Structure multi parameter analysis module is carried out online detection to thermal performance, the unit operation situation of unit, for setting, the historical data base of the feedback control parameters of unit are set up and the selection of operation optimization parameter lays the foundation; By on-line analysis to the parameter of described expression gas turbine operation situation, the setting valve of the relevant Control Parameter of output.
Correspondingly, a kind of in/small size gas turbine on-line fault diagnosis, prediction, feed back control system, comprising: the sensing unit of Xiang Lianing, adjustable gain amplifying unit, data processing unit and feedback control signal output unit successively; And the adjustable DC power source unit that links to each other respectively with described sensing unit, adjustable gain amplifying unit, data processing unit and feedback control signal output unit; Described data processing unit comprises: data capture and analog-to-digital conversion module, and the detected data of sensing unit are this data capture of input and analog-to-digital conversion module after the adjustable gain amplifying unit amplifies, and is converted to binary signal; The clock memory module writes down chronologically from the dynamic and steady-state signal of described data capture and analog-to-digital conversion module reception; Reception is from the data processing and the analysis module of the signal of record chronologically of described clock memory module, and this data processing and analysis module comprise that the artificial neural network analyzes submodule, analysis expert storehouse, fuzzy logic analysis piece and multi parameter analysis submodule; The failure modes module, according to thermomechanics, aeroelasticity, the mechanics of materials, rotor dynamics, Chemical Kinetics and combustion stability theory, with fault be divided into firing chamber unstability, gas compressor unstability, turbine unstability, blade broken fault, axle is that self-excitation vibrations, lubricating oil oil film lost efficacy and the sensor test deviation; Fault setting valve setting module according to the situation and the environment of gas turbine operation, is just set the threshold values of the feedback control unlatching of all kinds of faults before the unit operation; And the D/A converter module that connects described fault setting valve setting module, this D/A converter module data output connects described feedback control signal output unit.
The present invention realizes online collection and the analysis of finishing all kinds of fault messages, and will analyze accordingly and integrate, adopt Dynamic Data Processing device (DSP) that these analysis means are solidificated in the chip, on the basis of analysis technology such as failure modes, advanced failure analysis methods, fault expert, realize accurately assessing gas turbine component state, raising equipment availability, prolonging overhaul interval, strengthen prevention catastrophic failure ability; The effects such as behavioral characteristics of sequential record various types of signal are improved the gas turbine operation level thereby reach, and enhance system security, and improve overhaul efficiency.From trouble analysis, extract feedback control parameters, online elimination fault.
Description of drawings
Fig. 1 is gas turbine on-line fault diagnosis of the present invention, prediction, process of feedback schematic representation;
Fig. 2 is the hardware configuration of gas turbine on-line fault diagnosis of the present invention, prediction, feedback function.
Embodiment
According to Fig. 1 and Fig. 2, provide better embodiment of the present invention, and described in detail below, enable to understand better function of the present invention, characteristics.
Technological scheme of the present invention is based on the DSP technical foundation.According to shown in Figure 1, the function description of its each module is as follows:
A) design point of gas turbine operation or off design point mainly be by output power or thrust, combustor exit temperature, compressor intake pressure and flow, turbine inlet temperature, generating unit speed, lead/the stator blade established angle, parameter such as pollutant emission component, rotor oscillation frequency/amplitude, noise profile feature shows.
B) the test primary instrument of trouble analysis and sensor are based upon on advanced measuring technology and the system that the traditional test technology combines, and test method mainly is based upon on the contact measurement method.By being installed in the frequency and the pressure characteristic of the high frequency sound pressure transducer measurement rotor blade on the casing; The vibration of diagnosis blade fault, the acceleration transducer measurement axis system by being installed in bearing support; Measure the rotating speed of rotor by the photoelectric sensor that is installed in bearing; Go out temperature by being installed in combustor exit thermal resistor measurement combustion gas; Measure the burning concussion of firing chamber by the noise transducer that is installed in combustion chamber wall surface; Measure delivery temperature by the thermal resistor that is installed in exhaust outlet; Measure stagnation pressure, static pressure and the speed of exhaust by the stagnation pressure and the static probe that are installed in exhaust outlet.The chemical component of the chemical concentrations sensor measurement exhaust by being installed in exhaust outlet.Thermal parameter that sensor obtains and vibration parameters must pass through component balanced, and the model of rotor dynamics equilibrium equation structure fault experts database inside of mass balance, momentum balance, energy balance, chemical reaction, and the realization of types of functionality is to be based upon on the basis that measurement parameter is coupled.
C) all kinds of analysis modules: the function of this module is the analysis of dynamic and stable state image data, except the existing mature signal time-domain analysis in this laboratory at present, power spectrumanalysis, probability statistical analysis, signal correction analysis, multistage compressor dynamic analysis, wavelet analysis carry out integral body integrated, also must in analysis module, increase: 1) adopt artificial neural network (Artificial Neural Network) to analyze the roadability of the full operating mode of gas turbine group, move the framework that objective function is provided for performance optimization; 2) development trend of the system failure is judged in structure analysis expert storehouse (Expert Analysis System), for the accurate differentiation of the service cycle of unit, the displacement of critical component provide policy-making parameter; 3) adopt fuzzy logic analysis piece (Fuzzy LogicAnalysis Module), and carry out Fault Isolation in conjunction with the Kalamn filtering module, realize the diagnosis and the prediction of the inefficacy (Invalidation) of fault uncertainty (Uncertainty), variability (Anomaly) and sensor test signal; 4) structure multi parameter analysis module (Multivariable Analysis Module), thermal performance, unit operation situation to unit are carried out online detection, for setting, the historical data base of the feedback control parameters of unit are set up and the laying the foundation of the selection of operation optimization parameter, above-mentioned listed data analysis means all rely on the binary system assembler language, adopt the DSP technology to be cured.
D) all kinds of malfunctioning modules: according to thermomechanics, aeroelasticity, the mechanics of materials, rotor dynamics, Chemical Kinetics and combustion stability theory, the criterion that the structure fault diagnosis and fault prediction is differentiated.Through analysis and summary, extract following major failure factor: 1) firing chamber unstability; 2) gas compressor unstability; 3) turbine unstability; 4) blade broken fault; 5) axle is the self-excitation vibrations; 6) lubricating oil oil film lost efficacy; 7) sensor test deviation etc.And the weight of these faults analyzed function and effect according to failure analysis module, the character and the significance of inline diagnosis and all kinds of faults of prediction lay the foundation for forming optimum feedback control.
F) committed step is determined: the final purpose of On-line Fault diagnosis is to realize: 1) rely on the analysis of the historical data base of data capture, sum up the Changing Pattern of the major parameter of several critical components, reach rational Match performance and displacement parts, thereby reach working life that prolongs gas turbine and the purpose that reduces the overhaul number of times of unit; 2) because gas turbine group often is under varying environment and the different operating modes, so the coupling of the thermal performance of system is crucial, can be by the analysis and the trend discrimination of key parameter, on-line setup optimized operation scheme; 3) can set the break down distinguishing rule of tendency of some critical components according to the result of data analysis, for example: the minimum discharge of gas compressor; The maximum temperature of combustion chamber wall surface, combustion shock frequency etc. are for the feedback control design for scheme provides foundation.
G) key parameter feedback: by on-line analysis to relevant parameter, the setting valve of the relevant Control Parameter of output, for example: the 1) adjusting of compressor inlet stator established angle; 2) adjusting of gas compressor stator blade established angle; 3) rotational speed regulation of gas turbine; 4) adjusting of supply of fuel flow; 5) adjusting of turbine amount of cooling water; 6) quick shutdown etc.
Fig. 2 gas turbine on-line fault diagnosis, prediction, feedback function are realized hardware configuration.
Now the function to its Fig. 2 describes, and according to the description of Fig. 1 method, adopts the hardware configuration of Fig. 2, reaches the function of gas turbine on-line fault diagnosis, prediction, feedback control.
Sensing unit: be the integrated of contact type measurement sensing system, the test signal of sensor is that parallel transmission is in dsp chip.Pressure in the running state of gas turbine, temperature, vibration, rotating speed, noise level, chemical component, oil film thickness can be detected by this unit.
Adjustable DC power source unit: guarantee to support, reach the purpose that guarantees each unit energy stable operation for sensor, adjustable gain amplifying unit, DSP data processing unit, feedback control unit provide power supply.
Adjustable gain amplifying unit: because the kind difference of signal, yield value difference when analogue signal is amplified, for precision and the data resolution that guarantees data capture, it is the requirement that guarantees the trouble signal reliability between 3.5V-4.5V that signal is amplified to intermediate value.
The DSP data processing unit comprises 8 functions.
Data capture and analog-to-digital conversion module: finish multi-channel data acquisition, and finish the analog-to-digital conversion of trouble signal, the binary signal after the displacement can carry out numeric data to be handled.
Clock memory module: the acquisition time of set time (year, month, day, hour, min, second), and chronologically record gathered dynamically and steady-state signal, the Dynamic Signal here is this blade passing frequency that refers to, combustion chambers burn vibration frequency etc., the steady-state signal here refer to pressure under the gas turbine steady running condition, temperature, rotating speed, etc. signal, guarantee for the storage of historical data provides duration accurately, provide foundation accurately for defining the time that fault takes place.
Data processing and analysis module: comprise that the artificial neural network analyzes submodule, analysis expert storehouse, fuzzy logic analysis piece and multi parameter analysis submodule.These submodules method are in front described c) in all kinds of analysis modules advance to be worth assembler language by two and be cured in the dsp chip, bear the function of trouble analysis.Need be according to c) description write the submodule that needs the function that realizes exactly, promptly comprised which submodule in data processing and the analysis module, how association between these submodules.
Data memory module: all signals that will measure and the result after the data processing carry out classification and storage.
Usb data output: adopt the mode of USB flash disk that these data are stored, and can be off-line analysis the accurate data storehouse is provided.
The failure modes module: method is described d in front) in the character of all kinds of faults described carry out online classification, for feedback control provides setting valve accurately.
The fault module of adjusting:, just set the threshold values that the feedback control of all kinds of faults is opened before the unit operation according to the situation and the environment of gas turbine operation.
D/A converter module: according to the requirement of feedback control, finish the transformation of numerical quantities, mainly comprise control wave, control square signal and control 0-1 signal to analog amount.
5) feedback control signal output unit: these signals mainly are to provide control output for playing guard's valve, stator and stator blade stepper motor, fuel valve aperture.
Next with the example that is adjusted to of compressor inlet stator established angle, illustrate of the present invention in/the whole process of small size gas turbine on-line fault diagnosis, prediction, feedback and device.
The adjusting of compressor inlet stator established angle: because the operation down of the state of gas turbine under the variable working condition of being everlasting, every gas turbine all has a design point, and when the off-design state, efficient and stability must be affected.Most of stator established angle is fixed, and how the stator established angle self adaption under the design point is adjusted to the established angle of design point, and the angle of attack of movable vane import just is the key that improves unit operation efficient and improve stability.The process that this key parameter obtains and handles is: by being installed in total before the stator, static pressure stable state probe obtains the stagnation pressure and the static pressure of import incoming flow, pass through data acquistion system, these two parameters are transported in the DSP process chip, in chip, the Bernoulli's equation of compressible gas can be calculated the axial velocity of air-flow, the tach signal that obtains by rotating speed photoimpact sensor can calculate the tangential velocity under the mean radius, the vectorial combination of these two speed can obtain the air-flow reference angle before air-flow enters movable vane, the air-flow reference angle of this angle and design point is compared, can calculate the angle that stator should be adjusted, this signal is exported by square wave.Pass to the actuating motor of control stator established angle, adjust the stator established angle to setting valve.
Above-described, be preferred embodiment of the present invention only, be not in order to limit scope of the present invention.Though the present invention has only exemplified the adjusting of this concrete parameter of compressor inlet stator established angle; but the method according to this invention and device can similarly be adjusted parameters such as the adjusting of the adjusting of the rotational speed regulation of the adjusting of gas compressor stator blade established angle, gas turbine, supply of fuel flow, turbine amount of cooling water and quick shutdowns.Be that every simple, equivalence of doing according to the claims and the description of the present patent application changes and modification, all fall into the claim protection domain of patent of the present invention.
Claims (8)
1. in one kind/and small size gas turbine on-line fault diagnosis, prediction, feedback, comprise the steps:
Represent the parameter of gas turbine operation situation to comprise thermal parameter and vibration parameters by the contact measurement method collection;
Parameter to described expression gas turbine operation situation is carried out on-line analysis, comprising:
A) adopt the artificial neural network to analyze the roadability of the full operating mode of gas turbine group, move the framework that objective function is provided for performance optimization;
B) development trend of the system failure is judged in structure analysis expert storehouse, for the accurate differentiation of the service cycle of unit, the displacement of critical component provide policy-making parameter;
C) adopt the fuzzy logic analysis piece, and carry out Fault Isolation, be used for the diagnosis and the prediction of the inefficacy of fault uncertainty, variability and sensor test signal in conjunction with the Kalamn filtering module;
D) structure multi parameter analysis module is carried out online detection to thermal performance, the unit operation situation of unit, for setting, the historical data base of the feedback control parameters of unit are set up and the selection of operation optimization parameter lays the foundation;
By on-line analysis to the parameter of described expression gas turbine operation situation, the setting valve of the relevant Control Parameter of output.
2. in as claimed in claim 1/small size gas turbine on-line fault diagnosis, prediction, feedback, it is characterized in that, also comprise step: rely on the analysis of data capture, sum up the Changing Pattern of the parameter of described expression gas turbine operation situation to historical data base.
3. in as claimed in claim 1/and small size gas turbine on-line fault diagnosis, prediction, feedback, it is characterized in that, also comprise step: by analysis and trend discrimination to described thermal parameter, on-line setup optimized operation scheme.
4. in as claimed in claim 1/small size gas turbine on-line fault diagnosis, prediction, feedback, it is characterized in that, also comprise step: in can setting according to the result of data analysis/the break down distinguishing rule of tendency of parts in the small size gas turbine, for the feedback control design for scheme provides foundation.
5. in as claimed in claim 1/small size gas turbine on-line fault diagnosis, prediction, feedback, it is characterized in that, described thermal parameter and vibration parameters be component balanced by mass balance, momentum balance, energy balance, chemical reaction, and the rotor dynamics equilibrium equation construct the model of inside, described analysis expert storehouse.
6. in one kind/and small size gas turbine on-line fault diagnosis, prediction, feed back control system, it is characterized in that, comprising:
The sensing unit of Xiang Lianing, adjustable gain amplifying unit, data processing unit and feedback control signal output unit successively; And
The adjustable DC power source unit that links to each other respectively with described sensing unit, adjustable gain amplifying unit, data processing unit and feedback control signal output unit;
Described data processing unit comprises:
Data capture and analog-to-digital conversion module, the detected data of sensing unit are this data capture of input and analog-to-digital conversion module after the adjustable gain amplifying unit amplifies, and is converted to binary signal;
The clock memory module writes down chronologically from the dynamic and steady-state signal of described data capture and analog-to-digital conversion module reception;
Reception is from the data processing and the analysis module of the signal of record chronologically of described clock memory module, and this data processing and analysis module comprise that the artificial neural network analyzes submodule, analysis expert storehouse, fuzzy logic analysis piece and multi parameter analysis submodule;
The failure modes module, according to thermomechanics, aeroelasticity, the mechanics of materials, rotor dynamics, Chemical Kinetics and combustion stability theory, with fault be divided into firing chamber unstability, gas compressor unstability, turbine unstability, blade broken fault, axle is that self-excitation vibrations, lubricating oil oil film lost efficacy and the sensor test deviation;
Fault setting valve setting module according to the situation and the environment of gas turbine operation, is just set the threshold values of the feedback control unlatching of all kinds of faults before the unit operation; And
The D/A converter module that connects described fault setting valve setting module, this D/A converter module data output connects described feedback control signal output unit.
7. in as claimed in claim 6/small size gas turbine on-line fault diagnosis, prediction, feed back control system, it is characterized in that, described data processing and analysis module also are connected with a data memory module, and all signals that this data memory module will be measured and the result after the data processing carry out classification and storage.
8. in as claimed in claim 7/and small size gas turbine on-line fault diagnosis, prediction, feed back control system, it is characterized in that described data memory module is connected with a usb data output port.
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