CN203083829U - Automobile fault diagnosis system based on tail gas discharge detection adopting simple driving mode - Google Patents
Automobile fault diagnosis system based on tail gas discharge detection adopting simple driving mode Download PDFInfo
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- CN203083829U CN203083829U CN 201320057500 CN201320057500U CN203083829U CN 203083829 U CN203083829 U CN 203083829U CN 201320057500 CN201320057500 CN 201320057500 CN 201320057500 U CN201320057500 U CN 201320057500U CN 203083829 U CN203083829 U CN 203083829U
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Abstract
The utility model discloses an automobile fault diagnosis system based on tail gas discharge detection adopting a simple driving mode and belongs to the field of automobile maintenance and diagnosis. The automobile fault diagnosis system based on tail gas discharge detection adopting the simple driving mode includes a chassis dynamometer used for loading a to-be-detected automobile for simulating different road conditions; an automobile discharge measurement unit used for collecting automobile discharge tail gas data; and a data processing device used for realizing automobile discharge detection and fault diagnosis according data collected by the automobile discharge measurement unit. The automobile discharge measurement unit includes a waste gas analysis meter, a flowmeter and an electronic environment tester. The automobile fault diagnosis system based on tail gas discharge detection adopting the simple driving mode provided by the utility model can simulate states of the automobile under different working conditions precisely in a detection process, realizes detection of tail gas discharged by the automobile in the working conditions and makes preparation for following fault diagnosis. A method based on fuzzy inference is adopted for fault diagnosis, so that shortcomings of manual diagnosis are overcome, the diagnosis speed is high, the diagnosis accuracy is high, and convenience is made for maintenance and upgrade.
Description
Technical field
The utility model belongs to the automobile inspection field, particularly a kind of vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging.
Background technology
The continuous change with life style of improving constantly along with living standards of the people, motor vehicle has become the main vehicles of society, when it brought convenience to people's lives, the exhaust emission that it produced had also caused immeasurable infringement to environment and people healthy.The national pollution source census data of Chinese Ministry of Environmental Protection's communique shows that the primary arch-criminal of urban air pollution is exactly the toxic emission of motor vehicle.The fuel consumption that produces the motor vehicle correspondence of waste gas simultaneously also can increase.Country is in " 12 planning ", emphasis is clear and definite automotive energy-saving emission-reducing, and first motor vehicle CER project is included in national pollution source total amount and verified scope, owing to adopt to force to scrap and improve method such as oil quality to carry out the space of energy-saving and emission-reduction limited, the most important thing that therefore strengthen detecting, the pressure maintenance management just becomes the motor vehicle for saving energy and reducing emission mode.
At present China is scarcely out of swaddling-clothes in this respect, and for the simple relatively context of detection of management, environmental administration is through for many years test, perfect, adds that government constructs blank gradually in policy and financial support.But aspect maintenance, because the failure of fuel system of vehicle motor is closely related with the running status of subsystems such as lubricated, fuel feeding, exhaust, cooling, also maintain close ties with a plurality of minutes processes such as the conveying of fuel oil, heating, atomizing, injection, burnings, this make breakdown in the motor information be at random with uncertain, its fault presents multi-section position, many phenomenons, characteristics such as non-linear, so fault diagnosis difficulty comparatively.People also fail accurately to understand the mechanism that fault takes place at present, can not describe the engine failure system by enough precise analytic model.At present maintenance industry is still continued to use by rule of thumb, takes a chance or is relied on inefficient methodology such as adjuvant and keeps in repair.The model of automobile has thousands of, different engine operating conditions, environment for use all can cause various faults, and produces automobile exhaust gas, we can say that the reason of each automobile generation waste gas all may be different.By rule of thumb, take a chance or rely on the method for adjuvant, maintenance problem thorough, not in place appears easily, do not reach the purpose of administering tail gas.
Therefore, this artificial vehicle diagnosis mode of how can breaking away from by rule of thumb, to take a chance makes auto repair, especially carries out fault diagnosis by motor vehicle exhaust emission and realizes the intelligent technical matters that needs to be resolved hurrily that becomes.
The utility model content
Fundamental purpose of the present utility model is to overcome the shortcoming of prior art with not enough, a kind of vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging is provided, this system instructs the fault of judging that motor vehicle emission occurs according to all gases content in the motor vehicle emission tail gas, can be in testing process the state that under various operating modes, moves of simulated automotive accurately, then the motor vehicle emission tail gas that is under this operating mode is detected, thereby be the work that follow-up fault diagnosis is carried out data acquisition.The utility model is after adopting said mechanism to carry out data collection task, adopt following motor vehicle emission Detection and Diagnosis of Failures to diagnose based on fuzzy reasoning and self study, this method instructs the fault of judging that motor vehicle emission occurs according to all gases content in the motor vehicle emission tail gas, by fuzzy reasoning the fault diagnosis example of motor vehicle exhaust emission is learnt, from a large amount of samples, extract fault signature, then automobile to be detected is detected, determine failure cause apace and corresponding solution is provided according to fault signature, the accuracy in detection height, skill level dependence to operating personnel is not high, and easy and simple to handle.This method not only can improve the overhaul efficiency of automobile inspection industry, can guarantee that also the motor vehicle emission tail gas behind the automobile inspection can be up to standard simultaneously, and then reduces urban air pollution.
The purpose of this utility model realizes by following technical scheme: a kind of vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging comprises:
Be used for loading to simulate the chassis dynamometer of various operating modes to automobile to be detected;
Be used to gather the motor vehicle emission measuring unit of motor vehicle emission tail gas data, this unit comprise the concentration that is used for gathering each gas componant of motor vehicle emission tail gas exhaust-gas analyzer, be used to the electronic environment tester gathering the flowmeter of motor vehicle emission exhaust flow and be used to obtain current environmental temperature, humidity and atmospheric pressure;
Be used for carrying out the data processing equipment of motor vehicle emission detection and fault diagnosis according to the data that the motor vehicle emission measuring unit is gathered;
When detecting, automobile to be detected is positioned on the chassis dynamometer, and the motor vehicle emission measuring unit is arranged at auto exhaust mouth to be detected place, and the motor vehicle emission measuring unit is connected with the data processing equipment signal.
Preferably, described data processing equipment comprises singlechip chip and corresponding peripheral components, by the Current Control road simulation dynamometer of output, carries out data interaction with RS-232-C interface mode and exhaust-gas analyzer and flowmeter.
Preferably, described chassis dynamometer also links to each other with a feedback control unit, this feedback control unit comprises the loading force signal acquisition module that is used to measure current chassis dynamometer institute loading force signal, be used to measure the vehicle speed signal acquisition module of current vehicle speed, be used for chassis dynamometer being carried out the power loading unit and the feedback unit controller that is used for according to loading force signal and vehicle speed signal employing pid algorithm output feedback signal, loading force signal acquisition module that power loads according to feedback signal, the vehicle speed signal acquisition module is connected with the feedback unit controller respectively with the power loading unit.
Further, described feedback unit controller also is connected with the data processing equipment signal, is used for realizing FEEDBACK CONTROL by data processing equipment Control and Feedback cell controller.Thereby make one-piece construction simpler, save cost.
Preferably, described feedback unit controller is a single-chip microcomputer.
Diagnose in above-mentioned detection on the basis of mechanism, can finish fault detection and diagnosis by following device.
Device is examined in a kind of motor vehicle emission fault inspection based on fuzzy reasoning and self study, comprising:
Be used to export controlled variable to road simulation dynamometer, gather the data acquisition and the signal output module of exhaust-gas analyzer and flow meter data;
Be used for the control detection flow process, the detection control and the administration module that receive the motor vehicle emission data and data are carried out computing, correction;
Be used to store the data memory module in motor vehicle emission database, diagnosis and repair record storehouse, vehicle archive database, criterion limit value storehouse;
Be used for from the motor vehicle emission database of data memory module, reading testing result information, pass through Fuzzy Logic Reasoning Algorithm then, judge the degree of membership of this sample in the different faults reason according to the fuzzy diagnosis matrix, determine the corresponding failure cause of this sample possibility, export the fault diagnosis module of diagnostic result then according to failure cause degree of membership size;
Be used for that diagnostic result is belonged to correct checkup item record and write diagnosis and repair record storehouse, and the self study administration module that carries out self study according to historical sample, the self study administration module links to each other with data memory module.
Be used to provide the input/output module of man-machine interaction, input/output module also links to each other with data memory module.
Simultaneously, described detection control is connected with signal output module, data memory module with data acquisition respectively with administration module, and fault diagnosis module is connected with data memory module, self study administration module, input/output module respectively.
Preferably, described data acquisition and signal output module comprise singlechip chip and corresponding peripheral components, by the Current Control road simulation dynamometer of output, carry out data interaction with RS-232-C interface mode and exhaust-gas analyzer and flowmeter.
Preferably, described self study administration module extracts the historical sample of confirming through the expert and carries out self study from the motor vehicle emission database, further revise the fuzzy diagnosis matrix.
Preferably, described input/output module comprises keyboard input interface, liquid crystal display output interface, is used to provide input of detection information and detecting operation guide, testing result output and diagnostic result output.
Above-mentioned motor vehicle emission fault based on fuzzy reasoning and self study is examined the Detection and Diagnosis of Failures of examining device, may further comprise the steps:
(1) chassis dynamometer, exhaust-gas analyzer, flowmeter are returned to zero and initialization, write down the vehicle archive information of vehicle to be detected;
(2) detect beginning, gather each component content value, flow value in the vehicular discharge tail gas to be detected under each road conditions, make comparisons,, then directly enter step (4) if up to standard with standard value; If not up to standard,, judge the degree of membership of this group testing result in the different faults reason according to the fuzzy diagnosis matrix then by Fuzzy Logic Reasoning Algorithm, determine the corresponding failure cause of this vehicle possibility to be detected, export diagnostic result then, and enter step (3), write down this diagnostic result simultaneously;
(3) staff keeps in repair according to diagnostic result, carries out the detection of step (2) after the maintenance once more;
(4) maintenance is finished, and vehicle archive information, diagnostic result is belonged to correct failure diagnosis information correspondence be updated to database, is used for self study, regulates the fuzzy diagnosis matrix.
More specifically, may further comprise the steps:
(1) detects zeroing and the initial work that control and administration module are responsible for dispatching and finishing chassis dynamometer, waste-gas analysis instrument and flowmeter; The staff imports the vehicle archive information of vehicle to be checked by input/output module, and deposits the vehicle archive database in the data memory module in;
(2) after the detection beginning, detect control and administration module and gather the signal of chassis dynamometer, exhaust-gas analyzer, flowmeter by data acquisition and signal output module, and send control signal, the output flow process in accordance with regulations of control chassis dynamometer turbine is finished testing, and testing result is stored in the motor vehicle emission database in the data memory module;
(3) fault diagnosis module takes out testing result from data memory module, and the value in the criterion limit value storehouse in this testing result and the data memory module is compared, if reach standard, then enters step (5); If do not reach standard, then fault diagnosis module passes through Fuzzy Logic Reasoning Algorithm, judge the degree of membership of this sample in the different faults reason according to the fuzzy diagnosis matrix, determine the corresponding failure cause of this sample possibility, then according to failure cause degree of membership size output diagnostic result;
(4) staff keeps in repair according to diagnostic result, and the detection of reaching the standard grade once more after the maintenance reaches standard as testing result, then enters step (5); If the dissatisfied diagnostic result of then exporting according to fault diagnosis module keeps in repair once more,, enter step (5) then up to reaching standard;
(5) maintenance is finished, and diagnostic result is belonged to correct failure diagnosis information correspondence be updated to diagnosis and repair record storehouse in the data memory module, and the self study administration module carries out self study according to historical sample, regulates the fuzzy diagnosis matrix.
Preferably, in the described step (3), it is to use blurring mapping principle and maximum membership grade principle that the fault diagnosis module employing is carried out fault diagnosis based on the method for fuzzy reasoning, according to the cause-effect relationship in various degree between each failure cause and the failure symptom, taking all factors into consideration on the basis of all indications, the possible cause of diagnosing automobile to break down specifically may further comprise the steps:
(1) structure fuzzy diagnosis matrix: establish that all contingent various failure causes are the reason collection in the system, use vectorial Y={y
1, y
2..., y
nExpression, wherein, n represents the sum of system failure reason kind; If it is the sign collection that failure cause may cause various failure symptoms, use vectorial X={x
1, x
2..., x
mExpression, wherein, m represents the sum of failure symptom kind;
(2) to the failure cause y among the failure cause collection Y
j(j=l, 2 ..., n) do to be out of order judge, determine that this failure cause is to sign x
i(i=1,2 ..., degree of membership m) or generation symptom x
iThe time failure cause be y
jConfidence level r
IjThe evaluation collection of n corresponding m the sign of failure cause has just constituted fuzzy diagnosis matrix R, and is as follows:
Wherein, 0≤r
Ij≤ 1,1≤i≤m, 1≤j≤n, R have represented the fuzzy relation of failure symptom phenomenon X to the failure cause Y;
(3) through behind the fuzzy operation Y=XR, obtain failure cause fuzzy vector Y={y
1, y
2..., y
n, with y
jArranging from big to small, think most likely degree of membership maximum of target to be diagnosed, secondly is that degree of membership is taken second place, and the like, at last according to failure cause degree of membership size output diagnostic result.
r
IjReliability determined the quality and the success or failure of diagnostic result, its initial value can be rule of thumb and method synthesis evaluation such as expert statistics, then the modification and perfection progressively of the self study by the expert system study mechanism in using in real time.
Fault diagnosis expert system carries out self study to the historical sample of confirming through the expert, thereby further revises the fuzzy diagnosis matrix, makes it reflect the degree of correlation between the phenomenon of the failure and failure cause in each subsystem more accurately.Neuroid imitates the human brain function of neurons, has the direct processing power of powerful self-learning capability and data.Because the method that diagnostic system adopts is based on fuzzy diagnosis, so self study will be undertaken by corresponding with it fuzzy neural network.The main method of neuroid self study is: the iterative learning that comprises input and output vector sample data is provided, and network learning procedure is constantly adjusted weights exactly, makes network convergence, and error amount reaches minimum process.Specifically be that the concrete steps that described step (4) is carried out self study according to current diagnostic message are: with failure symptom phenomenon X={x
1, x
2... x
mAs the input of fuzzy neural network, neural network obtains actual output Y={y by compose operation
1, y
2..., y
n, its operational formula is:
Wherein, 0≤r
Ij≤ 1,1≤i≤m, 1≤j≤n, r
IjBe each weights between input pattern and the output mode in the network, promptly phenomenon of the failure is to the degree of membership value of failure cause, and the weights adjustment process is exactly the adjustment process of degree of membership value.The basic thought of weights adjustment is to utilize the desired output of neural network and the reference that the deviation between the actual output is adjusted as the connection weights, and finally reduces this deviation, and concrete adjustment process is:
Make b
j=(y
jThe y of) '-
j, y in the formula
jBe desired output, (y
jThe actual output of) ' be, b
jThe expression output error, the formula below adopting is asked for r
Ij.:
r
ij(t+1)=r
ij(t)-ab
jx
i；
Wherein, r
Ij(t) weights of expression moment t, r
Ij(t+1) the new weights that obtain after the weights correction once of expression to moment t, a is a scale factor, satisfies 0≤a≤1, adopts the finally total energy convergence of above-mentioned method, thereby finishes each weights r
Ij, i.e. the adjustment of degree of membership value reaches the effect of self study.
The utility model compared with prior art has following advantage and beneficial effect:
1, the utility model is based on the operating condition method detection, eddy current motor effect by chassis dynamometer, produce the true surface resistance of analog machine motor-car when road traveling, the discharging that makes motor vehicle is near the situation when road traveling, and gather ten multinomial detection data in its process, thereby guarantee science, the accuracy of data.For fault diagnosis provides data effectively reliably.
3, also be provided with feedback control unit in the utility model, feedback control unit internal PID algoritic module, chassis dynamometer institute loading force signal and vehicle speed signal are gathered in real time and calculated and control by feedback mechanism, thereby guarantee the accuracy of chassis dynamometer power that automobile to be detected loads.
3, fault diagnosis is a fundamental construction fuzzy diagnosis matrix with the maintenance items probability storehouse that the U.S. administers motor vehicle emission all contaminations correspondence more than ten years, further propose to adopt expert system based on fuzzy reasoning and self study, diagnosis speed is fast, and the accuracy of diagnosis height is convenient to safeguard and upgrading.Expert system is carried out self study by neural network to the historical sample of confirming through the expert, thereby further revises the fuzzy diagnosis matrix.Thereby overcome by rule of thumb, this artificial vehicle diagnosis mode of taking a chance, make auto repair, especially carrying out fault diagnosis by motor vehicle exhaust emission realizes intelligent, and pass through self-learning function, can make the whole fuzzy diagnosis matrix of foundation accurate further, to follow-up automobile component improve, the formulation of industry standard etc. all can provide reference value.
Description of drawings
Fig. 1 is the fundamental diagram of the utility model device;
Fig. 2 is that the signal of each module in the utility model data processing equipment moves towards synoptic diagram;
Fig. 3 is the process flow diagram that the utility model data processing equipment carries out the method for fault detection and diagnosis employing.
Embodiment
Below in conjunction with embodiment and accompanying drawing the utility model is described in further detail, but embodiment of the present utility model is not limited thereto.
Embodiment 1
As shown in Figure 1, present embodiment discloses a kind of vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging, comprising:
Be used for loading to simulate the chassis dynamometer of various road conditions to automobile to be detected;
Be used to gather the motor vehicle emission measuring unit of motor vehicle emission tail gas data, this unit comprise the concentration that is used for gathering each gas componant of motor vehicle emission tail gas exhaust-gas analyzer, be used to the electronic environment tester gathering the flowmeter of motor vehicle emission exhaust flow and be used to obtain current environmental temperature, humidity and atmospheric pressure;
Be used for carrying out the data processing equipment of motor vehicle emission detection and fault diagnosis according to the data that the motor vehicle emission measuring unit is gathered;
When detecting, automobile to be detected is positioned on the chassis dynamometer, and the motor vehicle emission measuring unit is arranged at auto exhaust mouth to be detected place, and the motor vehicle emission measuring unit is connected with the data processing equipment signal.
In the present embodiment, the power that loads on the chassis dynamometer is controlled by a feedback control unit, this feedback control unit comprises the loading force signal acquisition module that is used to measure current chassis dynamometer institute loading force signal, be used to measure the vehicle speed signal acquisition module of current vehicle speed, be used for chassis dynamometer being carried out power loading unit and the feedback unit controller that power loads according to feedback signal, the loading force signal acquisition module, the vehicle speed signal acquisition module is connected with the feedback unit controller respectively with the power loading unit, in actual applications, the feedback control procedure of this feedback control unit can independently be finished by single-chip microcomputer, also can link to each other with data processing equipment, realize FEEDBACK CONTROL by data processing equipment Control and Feedback cell controller, feedback procedure specifically adopts pid algorithm to finish.
Data processing equipment described in the present embodiment comprises singlechip chip and corresponding peripheral components, Current Control road simulation dynamometer by output carries out data interaction with exhaust-gas analyzer in RS-232-C interface mode and the motor vehicle emission measuring unit and flowmeter.
Device is examined in a kind of motor vehicle emission fault inspection based on fuzzy reasoning and self study, comprises chassis dynamometer, exhaust-gas analyzer, flowmeter, is used to realize that motor vehicle emission detects and the computer system of discharging fault diagnosis.Computer system comprises that again detecting control exports (CO) module, data storage (DS) module, fault diagnosis (FD) module, self study management (MM) module and input and output (IO) module with management (CM) module, data acquisition and signal.Data acquisition links to each other with chassis dynamometer, waste gas instrument, flowmeter with signal output module, is used to export controlled variable to road simulation dynamometer, gathers exhaust-gas analyzer and flow meter data; Detect control and be used for the control detection flow process, receive the motor vehicle emission data and data are carried out computing, correction with administration module; Data memory module is used to store data such as motor vehicle emission database, diagnosis and repair record storehouse, vehicle archive database, criterion limit value storehouse; Fault diagnosis module is used for by Fuzzy Logic Reasoning Algorithm, judges the degree of membership of this sample in the different faults reason according to the fuzzy diagnosis matrix, determines the corresponding failure cause of this sample possibility, then according to failure cause degree of membership size output diagnostic result; The self study administration module is used for that diagnostic result is belonged to correct checkup item record and writes diagnosis and repair record storehouse, and carries out self study according to historical sample; Input/output module is used to provide man-machine interaction.Described detection control is connected with signal output module, data memory module with data acquisition respectively with administration module, and fault diagnosis module is connected with data memory module, self study administration module, input/output module respectively.
In the present embodiment, described data acquisition and signal output module comprise singlechip chip and corresponding peripheral components, by the Current Control road simulation dynamometer of output, carry out data interaction with RS-232-C interface mode and exhaust-gas analyzer and flowmeter.Described input/output module comprises keyboard input interface, liquid crystal display output interface, is used to provide input of detection information and detecting operation guide, testing result output and diagnostic result output.
Fig. 2 is that present embodiment is examined the Device Testing method flow based on the motor vehicle emission fault inspection of fuzzy reasoning and self study, specifically may further comprise the steps:
(1) detects zeroing and the initial work that control and administration module are responsible for dispatching and finishing chassis dynamometer, waste-gas analysis instrument and flowmeter; The staff imports the vehicle archive information of vehicle to be checked by input/output module, and deposits the vehicle archive database in the data memory module in;
(2) after the detection beginning, detect control and administration module and gather the signal of chassis dynamometer, exhaust-gas analyzer, flowmeter by data acquisition and signal output module, and send control signal, the output flow process in accordance with regulations of control chassis dynamometer turbine is finished testing, and testing result is stored in the motor vehicle emission database in the data memory module;
(3) fault diagnosis module takes out testing result from data memory module, and the value in the criterion limit value storehouse in this testing result and the data memory module is compared, if reach standard, then enters step (5); If do not reach standard, then fault diagnosis module passes through Fuzzy Logic Reasoning Algorithm, judge the degree of membership of this sample in the different faults reason according to the fuzzy diagnosis matrix, determine the corresponding failure cause of this sample possibility, then according to failure cause degree of membership size output diagnostic result;
(4) staff keeps in repair according to diagnostic result, and the detection of reaching the standard grade once more after the maintenance reaches standard as testing result, then enters step (5); If the dissatisfied diagnostic result of then exporting according to fault diagnosis module keeps in repair once more,, enter step (5) then up to reaching standard;
(5) maintenance is finished, and diagnostic result is belonged to correct failure diagnosis information correspondence be updated to diagnosis and repair record storehouse in the data memory module, and the self study administration module carries out self study according to historical sample, regulates the fuzzy diagnosis matrix.
Wherein, in the described step (3), fault diagnosis module adopts and carries out fault diagnosis based on the method for fuzzy reasoning, automobile engine failure diagnosis based on fuzzy reasoning is to use blurring mapping principle and maximum membership grade principle, according to the cause-effect relationship in various degree between each failure cause and the failure symptom, taking all factors into consideration on the basis of all indications the possible cause of diagnosing automobile to break down.The problem that fuzzy diagnosis need solve is: the 1. structure of fuzzy diagnosis matrix; 2. degree of membership (confidence level) determines; 3. the establishment of fuzzy diagnosis algorithm and principle.
Reason collection: establish with a set and define all contingent various failure causes in the system (motor car engine or certain subsystem).As ternary catalyzing unit fault, lambda sensor fault, ignition failure, waste gas circulating valve fault, vacuum tube fault or the like.Its available vectorial Y={y
1, y
2..., y
nExpression.Wherein, n represents the sum of engine or certain subsystem fault reason kind.
The sign collection: these failure causes may cause various failure symptoms, exceed standard as CO discharging, and the HC discharging exceeds standard or the like, is defined as a set, and with a vector representation X={x
1, x
2..., x
m, wherein, m represents the sum of engine failure sign kind.
The fuzzy diagnosis matrix: exist complicated fuzzy relation between the reason of engine and the sign, with a kind of failure symptom, may be caused by the various faults reason, same failure cause may cause the various faults sign again.To the failure cause y among the failure cause collection Y
j(j=l, 2 ..., n) do to be out of order judge, determine that this failure cause is to sign x
i(i=1,2 ..., symptom x (or takes place in degree of membership m)
iThe time failure cause be y
jConfidence level) r
IjThe evaluation collection of n corresponding m the sign of failure cause just constitutes fuzzy diagnosis matrix R like this, and is as follows:
Wherein, 0≤r
Ij≤ 1,1≤i≤m, 1≤j≤n, R have represented the fuzzy relation of failure symptom phenomenon X to the failure cause Y.Fuzzy diagnosis matrix R is that m * n ties up matrix, and wherein the line display failure symptom is tabulated and shown failure cause.r
IjExpression failure symptom phenomenon x
iWith failure cause y
jSymptom x promptly takes place in the quantification fuzzy value of degree of correlation
iThe time failure cause be y
jConfidence level.r
IjBig more, failure cause y is described
jFor the sign phenomenon x that breaks down
iThe effect of being played is big more, and promptly both degrees of correlation are just big more.The reliability of this value has determined the quality and the success or failure of diagnostic result, and its initial value can be rule of thumb and method synthesis evaluation such as expert statistics, then the modification and perfection progressively of the self study by the expert system study mechanism in using in real time.
The fuzzy reasoning method of fault diagnosis is exactly a degree of membership of obtaining various failure causes by the fuzzy diagnosis matrix between the degree of membership of phenomenon of the failure and failure symptom vector and the failure cause vector.
Assumed fault sign fuzzy vector X={x
1, x
2..., x
m, behind fuzzy operation Y=XR, obtain failure cause fuzzy vector Y={y
1, y
2..., y
n, with y
jArranging from big to small, think most likely degree of membership maximum of target to be diagnosed, secondly is that degree of membership is taken second place, and the like.At last according to failure cause degree of membership size output diagnostic result.
The concrete steps that described step (4) is carried out self study according to current diagnostic message are: with failure symptom phenomenon X={x
1, x
2... x
m, as the input of fuzzy neural network, neural network obtains actual output Y={y by compose operation
1, y
2..., y
n, its operational formula is:
Wherein, 0≤r
Ij≤ 1,1≤i≤m, 1≤j≤n, r
IjBe each weights between input pattern and the output mode in the network, be the degree of membership value of phenomenon of the failure to failure cause, the weights adjustment process is exactly the adjustment process of degree of membership value, the basic thought of weights adjustment is to utilize the desired output of neural network and the reference that the deviation between the actual output is adjusted as the connection weights, and finally reduce this deviation, concrete adjustment process is:
Make b
j=(y
jThe y of) '-
j, y in the formula
jBe desired output, (y
jThe actual output of) ' be, b
jThe expression output error, the formula below adopting is asked for r
Ij.
r
ij(t+1)=r
ij(t)-ab
jx
i；
Wherein, r
Ij(t) weights of expression moment t, r
Ij(t+1) the new weights that obtain after the weights correction once of expression to moment t, a is a scale factor, satisfies 0≤a≤1, adopts the finally total energy convergence of above-mentioned method, thereby finishes each weights r
Ij, i.e. the adjustment of degree of membership value reaches the effect of self study.
The foregoing description is the utility model preferred implementation; but embodiment of the present utility model is not restricted to the described embodiments; other any do not deviate from change, the modification done under spirit of the present utility model and the principle, substitutes, combination, simplify; all should be the substitute mode of equivalence, be included within the protection domain of the present utility model.
Claims (5)
1. the vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging is characterized in that, comprising:
Be used for loading to simulate the chassis dynamometer of various operating modes to automobile to be detected;
Be used to gather the motor vehicle emission measuring unit of motor vehicle emission tail gas data, this unit comprise the concentration that is used for gathering each gas componant of motor vehicle emission tail gas exhaust-gas analyzer, be used to the electronic environment tester gathering the flowmeter of motor vehicle emission exhaust flow and be used to obtain current environmental temperature, humidity and atmospheric pressure;
Be used for carrying out the data processing equipment of motor vehicle emission detection and fault diagnosis according to the data that the motor vehicle emission measuring unit is gathered;
When detecting, automobile to be detected is positioned on the chassis dynamometer, and the motor vehicle emission measuring unit is arranged at auto exhaust mouth to be detected place, and the motor vehicle emission measuring unit is connected with the data processing equipment signal.
2. the vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging according to claim 1, it is characterized in that, described data processing equipment comprises singlechip chip and corresponding peripheral components, by the Current Control road simulation dynamometer of output, carry out data interaction with RS-232-C interface mode and exhaust-gas analyzer and flowmeter.
3. the vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging according to claim 1, it is characterized in that, described chassis dynamometer also links to each other with a feedback control unit, this feedback control unit comprises the loading force signal acquisition module that is used to measure current chassis dynamometer institute loading force signal, be used to measure the vehicle speed signal acquisition module of current vehicle speed, be used for chassis dynamometer being carried out the power loading unit and the feedback unit controller that is used for according to loading force signal and vehicle speed signal employing pid algorithm output feedback signal, loading force signal acquisition module that power loads according to feedback signal, the vehicle speed signal acquisition module is connected with the feedback unit controller respectively with the power loading unit.
4. the vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging according to claim 3, it is characterized in that, described feedback unit controller also is connected with the data processing equipment signal, is used for realizing FEEDBACK CONTROL by data processing equipment Control and Feedback cell controller.
5. the vehicle fault diagnosis system that detects based on simple and easy operating condition method tail gas discharging according to claim 4 is characterized in that described feedback unit controller is a single-chip microcomputer.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104501862A (en) * | 2014-12-09 | 2015-04-08 | 清华大学 | Vehicle-mounted emission testing system of non-road mobile machinery |
| CN105556275A (en) * | 2013-09-24 | 2016-05-04 | 株式会社堀场制作所 | Driving mode display device, driving mode display program, and vehicle test system |
| CN108801644A (en) * | 2017-09-27 | 2018-11-13 | 广东泓胜科技股份有限公司 | A kind of automobile safety testing system |
| WO2018218533A1 (en) * | 2017-05-31 | 2018-12-06 | 深圳市爱夫卡科技股份有限公司 | Diagnosis method and diagnosis device for src exhaust gas aftertreatment system |
| CN109445408A (en) * | 2018-10-22 | 2019-03-08 | 重庆长安汽车股份有限公司 | A method of flow is desorbed in measurement car carbon tank in real time |
| CN110273738A (en) * | 2019-03-14 | 2019-09-24 | 吉林大学 | A kind of heavy-duty engine discharge diagnostic test system |
| CN114754923A (en) * | 2022-04-20 | 2022-07-15 | 浙江省计量科学研究院 | Wireless rotating speed detection and fault diagnosis device and method for chassis dynamometer |
| CN116050922A (en) * | 2023-02-03 | 2023-05-02 | 绥化学院 | Low-carbon environment-friendly automobile exhaust emission evaluation system and method |
-
2013
- 2013-01-31 CN CN 201320057500 patent/CN203083829U/en not_active Expired - Lifetime
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105556275A (en) * | 2013-09-24 | 2016-05-04 | 株式会社堀场制作所 | Driving mode display device, driving mode display program, and vehicle test system |
| CN104501862A (en) * | 2014-12-09 | 2015-04-08 | 清华大学 | Vehicle-mounted emission testing system of non-road mobile machinery |
| WO2018218533A1 (en) * | 2017-05-31 | 2018-12-06 | 深圳市爱夫卡科技股份有限公司 | Diagnosis method and diagnosis device for src exhaust gas aftertreatment system |
| CN108801644A (en) * | 2017-09-27 | 2018-11-13 | 广东泓胜科技股份有限公司 | A kind of automobile safety testing system |
| CN109445408A (en) * | 2018-10-22 | 2019-03-08 | 重庆长安汽车股份有限公司 | A method of flow is desorbed in measurement car carbon tank in real time |
| CN109445408B (en) * | 2018-10-22 | 2021-02-05 | 重庆长安汽车股份有限公司 | Method for measuring real-time desorption flow of automobile carbon canister |
| CN110273738A (en) * | 2019-03-14 | 2019-09-24 | 吉林大学 | A kind of heavy-duty engine discharge diagnostic test system |
| CN110273738B (en) * | 2019-03-14 | 2023-06-02 | 吉林大学 | Heavy engine emission diagnosis test system |
| CN114754923A (en) * | 2022-04-20 | 2022-07-15 | 浙江省计量科学研究院 | Wireless rotating speed detection and fault diagnosis device and method for chassis dynamometer |
| CN116050922A (en) * | 2023-02-03 | 2023-05-02 | 绥化学院 | Low-carbon environment-friendly automobile exhaust emission evaluation system and method |
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