EP2715624A1 - Procédé et système de diagnostic servant à assister la recherche d'erreur guidée dans des systèmes techniques - Google Patents

Procédé et système de diagnostic servant à assister la recherche d'erreur guidée dans des systèmes techniques

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Publication number
EP2715624A1
EP2715624A1 EP12718688.0A EP12718688A EP2715624A1 EP 2715624 A1 EP2715624 A1 EP 2715624A1 EP 12718688 A EP12718688 A EP 12718688A EP 2715624 A1 EP2715624 A1 EP 2715624A1
Authority
EP
European Patent Office
Prior art keywords
technical system
tests
component
elements
components
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP12718688.0A
Other languages
German (de)
English (en)
Inventor
Christian ERATH
Mirko Wagner
Andreas Buse
Martin Fritz
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP2715624A1 publication Critical patent/EP2715624A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00—Testing of vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00—Subject matter not provided for in other groups of this subclass

Definitions

  • the invention relates to a method and a diagnostic system for supporting the guided troubleshooting in technical systems, especially in motor vehicles.
  • the document DE 103 07 365 B4 discloses, for example, a diagnostic device for a vehicle in which state data of the vehicle are correlated in a computing device with a fault diagnosis model so that suggestions for measurements to be made and / or measurement data to be entered for the fault limitation can be determined.
  • Troubleshooting trees are a step-by-step troubleshooting strategy that uses simple decisions and decisions to narrow the set of causes of errors to a subset of possible causes of error that is congruent with the observations.
  • the quality of the guided troubleshooting is therefore largely determined by the quality of the troubleshooting trees.
  • the creation of troubleshooting trees is usually done manually based on the expertise of experts and requires a lot of time.
  • One way to perform guided troubleshooting is through dynamic debugging, where the available tests and tests are evaluated and prioritized during debugging of the technical system. In this case, an evaluation in the dynamic troubleshooting, as well as the determination of possible faulty components, after each test carried out anew.
  • a test domain which, for example, maps the assignments of available tests and possible faulty components to be checked, enables relevant tests to be determined automatically and evaluated by means of a program module.
  • the invention is based on the idea of creating a diagnostic system and a diagnostic system for a technical system with which the creation of troubleshooting trees can be automated on the basis of the expert knowledge already required for the manual creation of troubleshooting trees and the execution of guided troubleshooting can be supported.
  • an acquisition module is provided for the systematic acquisition of all relevant status, monitoring and / or measurement data of the technical system and a prioritization module for the prioritization of all relevant tests, tests or measurements in order to determine the weightings of the tests, tests or measurements depending on the state, observation and / or measurement data automatically create a troubleshooting tree, which can serve as a basis for a guided troubleshooting.
  • the relevant status, observation and / or measurement data can be provided in the acquisition module in the form of a structured ontology for the prioritization module, in which the ontology can then be processed accordingly.
  • the ontology can then be processed accordingly.
  • known diagnostic systems and methods are in the
  • Acquisition module only information from the domain of expert knowledge necessary without having to use physical models, Bayesian networks or similar test domains.
  • the present invention therefore provides, according to one embodiment, a method of assisting guided troubleshooting in a technical system, comprising the steps of detecting a set of observations on the technical system, the
  • Feature combination combinations of each of the set of possible tests of the technical system to be performed yields calculating a second prioritization of the set of possible tests to be performed by determining an average expected absolute reduction in the number of elements of the set of possible component errors of the technical system based on the determined absolute reduction of each Testing, and establishing a prioritized list of possible tests to be performed based on the first and second prioritizations.
  • a diagnostic system for supporting guided troubleshooting in a technical system comprising a detector adapted to detect a set of observations on the technical system and a set of potential defective components of the technical system and a set of possible ones
  • a determination device which is designed to determine a set of possible component errors, which is consistent with the set of observations
  • a computing device which is adapted to each a first absolute reduction of the number of elements of the set of possible Defective components of the technical system which, by considering each of the possible feature combination of each of the set of possible tests of the technical system to be performed when determining the amount of possible component errors, to determine a first prioritization of the amount of possible tests to be performed by determining a mean expected absolute reduction of the number of elements of the set of possible defective ones
  • the method according to the invention further comprises the steps of determining relevant for the technical system
  • Bayesian networks For example, having to resort to physical models, Bayesian networks, or other test domains provides a database of all component error-symptom and component-error feature dependency dependencies that underlie guided debugging.
  • the method comprises the steps of
  • Calculating a third prioritization of the set of possible tests to be performed by determining an average expected absolute reduction of the number of elements of the set of possible component errors of the selected component of the technical system being tested and establishing a prioritized list of possible tests to be performed for the selected component to be tested based on the third prioritization.
  • 1 is a schematic representation of a dependency graph according to a
  • FIG. 2 shows a schematic illustration of a method for assisting guided troubleshooting in a technical system according to a further embodiment of the invention
  • FIG. 3 is a schematic representation of a method for supporting the guided troubleshooting in a technical system according to another embodiment of the invention.
  • FIG. 4 shows a schematic representation of a method for supporting guided troubleshooting in a technical system according to a further embodiment of the invention.
  • FIG. 5 is a schematic representation of a diagnostic system for supporting guided troubleshooting in a technical system according to another embodiment of the invention.
  • Fig. 1 shows a schematic representation of a dependency graph 10.
  • Dependency graph 10 shows a schematic representation of the relations between tests, their characteristics and feature values, components and their
  • tests 1 1 a and 1 1 b which have features 12a and 12b and 12c.
  • Tests in the sense of the application are all tests, measurements or other observer interventions in a technical system, which as observed, tested and / or measured data provide information about features of the technical system.
  • a concrete example of a test is, for example, an exhaust gas test on a vehicle.
  • Characteristics in the sense of this application are all information entities whose observation, measurement or examination result in different feature characteristics which can occur as feature combination for each test.
  • a concrete feature in connection with the exemplary exhaust gas test on a vehicle is, for example, the amount of a gas constituent contained in the exhaust gas of a vehicle, such as carbon dioxide.
  • technical systems can include, for example, machines, production plants, robots, system installations, motor vehicles or other complex technical assemblies of functionally interdependent technical components.
  • the dependency graph further comprises components 15a, 15b and 15c of the technical system.
  • Components within the meaning of the application can be the smallest exchangeable units of a technical system, for example machine parts, vehicle parts or the like.
  • Each of the components 15a, 15b and 15c may include component errors 14a, 14b, 14c and 14d.
  • component 15a may have two different component errors 14a and 14b, while components 15b and 15c may only have one component error 14c and 14d, respectively.
  • Component errors in the sense of the application can represent all deviations from the standard state of the functionality of components, and in particular be perceptible by observations of the technical system.
  • component errors may be deviations in output or measured quantities of components.
  • Each of the component errors 14a, 14b, 14c and 14d are one or more
  • Feature outputs 13a, 13b, 13c, 13d assigned, that is, in the presence A set of feature values 13a, 13b, 13c, 13d may be deduced to be present or absent a component error 14a, 14b, 14c and 14d. For example, in the event of
  • Feature forms 13a and 13c of the two features 12a, 12b of the test 1 1 a be concluded that the component error 14a of the component 15a is present.
  • dependency graph 10 includes symptoms 16a and 16b, which are a set of observable malfunctions of components of a technical system and, in particular, may be associated with one or more component errors.
  • the symptom 16a manifests itself in component errors 14a and 14b
  • symptom 16b manifests itself in component errors 14c and 14d.
  • the symptoms may also include codes for the identification of malfunctions, so-called "Displayed Trouble Codes" (DTC), which can be recorded, stored and retrieved, for example, by control and diagnostic devices in vehicles.
  • DTC Display Trouble Codes
  • Fig. 2 shows a schematic representation of a method 20 for supporting the guided troubleshooting in a technical system.
  • the method 20 includes, in a first step 21, acquiring a set of observations on the technical system.
  • the amount of observations may include an amount of the characteristics and symptoms known at the beginning of the procedure.
  • Known features and symptoms can, for example, a
  • Dependency relationships are assigned to those component errors that are consistent with the known feature values and symptoms.
  • the consistent component errors can then be used to determine those components as possible defective components in which the consistent component errors can occur.
  • Possible defective components include all components of the technical
  • the aim may be to determine further observations or characteristic values by selecting or suggesting suitable further tests, which may restrict the amount of possible defective components to a subset in order ultimately to locate a defective component.
  • prioritization parameters rank (ti) and rank K KF (ti) can be determined, which permit a statement as to how helpful each test of the number of possible tests NT to be performed in reducing the number of tests
  • Elements of the set of possible defective components MDK can be.
  • a prioritization may, inter alia, also be made on the basis of the effort for the respective test and the probability of occurrence for a component error related to a symptom.
  • the prioritization parameter rank (ti) may, for example, specify an average expected reduction in the number of elements of the set of possible defective components MDK.
  • an exemplary method is given, with which this reduction, taking into account the probability of occurrence for a
  • Component error related to a symptom can be calculated.
  • the amount of KMK, of all consistent feature value combinations can be calculated.
  • the elements of KMK are feature-value combinations, that is, sets of feature values of the test t, which as a consequence of each element of a set of possible component errors, which are responsible for the set of observations may be able to occur.
  • the consistent feature value combination K ( k , i) of the quantity KMK, of all consistent feature values the
  • Unification amount BMA (k j) of all observed feature values with the consistent feature expression combination K (k j) can be determined. On the basis of the union BMA ( kj), the new set KKF ( kj) can be more consistent
  • Components MDK (k j) can be specified.
  • the determined first reduction r ( kj) can then be weighted with the occurrence probabilities for each consistent feature combination K ( kj).
  • the new set of consistent component errors KKF ( kj) can be used and for each combination of consistent component errors f ( kj) one
  • Occurrence probability p (k j) are given, which exceeds the amount of all
  • Total occurrence probability p can be summed.
  • the first absolute reduction r (k j) can then be multiplied by the total occurrence probability p i, to give a weighted absolute reduction r g (k j).
  • all weighted absolute reductions rg ( kj) for each of the consistent feature value combinations K ( kj) of the set KMK, of all consistent feature values can be summed and normalized to the number of elements of the set KMK, of all consistent feature values become.
  • Weighting parameters to weight which can reflect a time and / or cost-dependent diagnostic effort. In this case, it is possible to fall back on predetermined time values for special tests and measuring devices as well as possibly actual costs of a test.
  • the prioritization parameter rank (ti) thus gives for each test a measure which represents the benefit of the test with regard to a reduction in the number of elements of the set of possible defective components MDK.
  • the prioritization parameter rank K KF (ti) may also indicate an average expected reduction.
  • the prioritization parameter rank K KF (ti) depends on the absolute expected reduction r K K (k, i) of the number of elements of the set of consistent component errors KKF. This reduction or second reduction r K KF (kj) can be specified as an absolute difference of the number of elements of the existing amount of the components consistent error CCF and the new amount of the components consistent error KKF (k j).
  • the determined second reduction r K KF (k, i) may then be weighted by the probabilities of occurrence for each combination consistent feature quantity C (k j). For this, the new set of consistent component errors KKF ( kj) can be used and for each combination of consistent component errors f ( kj) one
  • Occurrence probability PKKF (kj) can be given, which over the set of all combinations of consistent component error f K KF (k, i) to a
  • Reduction r K KF (k, i) then with the total occurrence probability p K KFi to specify a weighted absolute reduction rg K KF (k, i) are multiplied.
  • the prioritization parameter K KF rank (ti) can all weighted absolute reductions rg K KF (k, i) for each of the consistent feature quantity combinations K (k j) of the amount KMK summed all consistent characteristic values and the number of elements of the set KMK , of all consistent characteristic values. Furthermore, it is optionally possible to weight the prioritization parameter rank K KF (ti) with the effort parameter specified above.
  • a third step 23 it is checked whether the number of elements of the amount of possible defective components is greater than one. Should only one possible defective component remain, in step 23a the remaining component can be output as the defective component.
  • step 23a it may be stated in step 23a that the observations in the model are not plausible. If the number of elements of the set of possible defective components is greater than one, it is checked in a fourth step 24 whether the number of elements of the set of possible tests to be performed is greater than zero, that is, if there are any tests still in progress can not and have not yet been carried out. If no further test is possible, this can be displayed to a user in step 24a. At the same time, in step 24a, the previous list of all possible defective components can be output as a list of suspect components.
  • a prioritized list of all possible tests NT to be performed which can be displayed to a user can then be determined in step 25.
  • the user can then select and perform one of the suggested tests and supplement the set of observations with the results of the test performed.
  • the test with the highest priority can also be specified as the test to be performed by the user, who then has to carry out this test.
  • a step 26 the amount of observations obtained with the results of the test performed according to step 25 can then be supplemented. Furthermore, the amount of possible executable or to be performed tests can be updated. In addition, the prioritization parameters rank (ti) and rank K KF (ti) are recalculated on the basis of the new set of observations, for example using the methods given above. In steps 27 and 28, a check similar to steps 23 and 24 then takes place, this time checking on the basis of the new set of possible defective components or the new set of possible tests to be carried out. Steps 27a and 28a correspond to steps 23a and 24a.
  • step 29 the display of the prioritized list of possible tests to be performed may then be updated, if the number of elements of the set of possible defective components is greater than one and the number of elements of the set of possible tests to be performed is greater than zero.
  • the method can then be iterated from step 25 until one of the check criteria checked in steps 27 and 28 has been reached, or the user himself terminates the diagnostic procedure.
  • FIG. 3 shows a schematic representation of a method 30 for assisting guided troubleshooting in a technical system, for example in a vehicle to be diagnosed.
  • the method 30 in this case comprises the steps 31, 32, 33, 33 a, 34 and 34 a, which may correspond to the steps 21, 22, 23, 23 a, 24 and 24 a of the method 20 in FIG. 2.
  • a user may then select a component K from the set of possible defective components MDK that he believes may be defective, for example, or at which he may further
  • step 36 the set of all consistent component errors KKF_K relative to the component K selected in step 35 can be determined.
  • the set of all possible tests NT_K to be performed can then be determined on the basis of the set of all consistent component errors KKF_K.
  • step 38 a determination of a further prioritization parameter rank K (ti) can be determined which, in contrast to the prioritization parameter rank K KF (ti), of the absolute expected reduction r K KF (k, i ) of the number of elements of the set of consistent component error KKF_K of the selected component K.
  • the method for determining the prioritization parameter rank K (ti) can be carried out similarly to the above-explained method for determining the prioritization parameter rank K KF (ti), whereby in each case only those consistent component errors KKF_K are taken into account, which relate to the selected component K. Likewise, the occurrence probabilities PKKF ( kj ) and PKKFI are adjusted with respect to the selected component K. In step 39, the remaining possible tests to be performed can be determined based on the selection of component K. Based on the prioritization parameter rank K (ti), the tests can be evaluated specifically for the selected component K.
  • the prioritization parameter rank K (ti) can be used, for example, for the new weighting of the prioritized list created in step 40 using the prioritization parameters rank K KF (ti) and rank (ti).
  • a user can then select one of the suggested tests from the re-weighted prioritized list. Alternatively, the user can be given the highest prioritized test for execution.
  • step 41 similar to step 26 in FIG. 2, the amount of observations obtained from the results of the test performed in step 40 may be supplemented. Furthermore, the amount of possible executable or to be performed tests can be updated.
  • the prioritization parameters rank (ti) and rank K KF (ti) are recalculated based on the new set of observations, for example, using the above
  • step 44 it is further possible to check whether the selected component K is still under the new test by continuing the test determined amount of possible defective components is located. If this is not the case, it can be output in step 44a that the selected component K is not defective. The user may then be forwarded to step 35 to select another component K '. Should the selected component continue to be in the updated set of possible defective components, it may be checked in a step 45 whether further tests are possible for the selected component K. If this is not the case, the user can be forwarded to step 35 to select another component K '.
  • a new test may be taken from the updated prioritized list of possible ones
  • step 41 shows a schematic representation of a method 50 for supporting the guided troubleshooting in a technical system.
  • the method 50 can
  • a symptom to be processed is detected from a start node in the troubleshooting tree to be created or optimized.
  • the amount of possible defective components MDK and the amount of possible tests NT to be performed are determined on the basis of the amount of possible defective components MDK and the amount of tests NT to be performed .
  • prioritization parameters rank (ti) and rank K KF (ti) can be calculated in a similar manner as explained above.
  • step 53 the author may select one of the tests from the prioritized list of proposed tests to be performed according to the prioritization parameters rank (ti) and rank K KF (ti) to populate it into the troubleshooting tree.
  • step 54 the author may create a new branch or edit an existing branch for each possible combination of feature values of the selected test. After a selection of one of the nodes in step 55, in steps 56, 56a, 57 and 57a a check of termination criteria similar to steps 23, 23a, 24 and 24a in FIG. 2 can be made. As long as the number of elements of the set of possible defects
  • step 58 all branches can be completed until the branches can be terminated by abort criteria.
  • the method may be iterated from step 53 until the entire troubleshooting tree has been created or optimized. With the method 50, the author can gain clarity about which components are currently still being determined as possible defective components and which tests he can still carry out given the symptoms. Furthermore, the author receives
  • FIG. 5 shows a schematic representation of a diagnostic system 60 for supporting guided troubleshooting in a technical system.
  • a diagnostic system 60 for supporting guided troubleshooting in a technical system.
  • Diagnostic system designed to perform one of the methods 20, 30 or 50 in FIGS. 2, 3 and 4.
  • the diagnostic system 60 includes a detector 61 that is configured to acquire a set of observations on the technical system and to determine a set of potential defective components of the technical system and a set of possible tests of the technical system to be performed based on the set of observations ,
  • the diagnostic system 60 further includes a
  • Detection device 62 which is designed to be a set of possible
  • a calculator 63 is configured to provide an absolute reduction in the number of elements of the set of potential defective components of the technical system for each possible feature combination of each of the set of possible
  • a first prioritization of the amount of possible tests to be performed by determining an average expected absolute reduction of the number of elements of the set of possible defective components of the technical system on the basis of the determined technical tests to be performed on the basis of the number of possible component errors absolute reduction of each test to calculate an absolute reduction in the number of elements of the set of possible component errors of the technical system for each possible
  • the diagnostic system 60 further includes an output device 64 that is configured to create and output a prioritized list of possible tests to be performed based on the first and second prioritizations.
  • the diagnostic system 60 may include an optional acquisition module (not shown) configured to include components relevant to the technical system,

Abstract

L'invention concerne un procédé servant à assister la recherche d'erreur guidée dans un système technique. Ledit procédé comporte les étapes suivantes : la collecte d'une pluralité d'observations sur le système technique ; la détermination d'une pluralité de possibles composants défectueux du système technique et d'une pluralité d'essais possibles à effectuer du système technique sur la base de la pluralité d'observations ; la détermination d'une pluralité de possibles erreurs de composant, qui est cohérente avec la pluralité d'observations ; la détermination d'une réduction absolue du nombre des éléments de la pluralité de possibles composants défectueux du système technique pour chaque combinaison de caractère distinctif possible de chaque essai de la pluralité d'essais possibles à effectuer du système technique sur la base de la pluralité de possibles erreurs de composant ; le calcul d'une première priorisation de la pluralité d'essais possibles à effectuer en déterminant une réduction absolue, à attendre en moyenne, du nombre des éléments de la pluralité de possibles composants défectueux du système technique sur la base de la réduction absolue déterminée de chaque essai ; la détermination d'une réduction absolue du nombre des éléments de la pluralité de possibles erreurs de composant du système technique pour chaque combinaison de caractère distinctif possible de chaque essai de la pluralité d'essais possibles à effectuer du système technique ; le calcul d'une deuxième priorisation de la pluralité d'essais possibles à effectuer en déterminant une réduction absolue, à attendre en moyenne, du nombre des éléments de la pluralité de possibles erreurs de composants du système technique sur la base de la réduction absolue déterminée de chaque essai ; et la création d'une liste priorisée d'essais possibles à effectuer sur la base de la première et de la deuxième priorisation.
EP12718688.0A 2011-05-31 2012-05-08 Procédé et système de diagnostic servant à assister la recherche d'erreur guidée dans des systèmes techniques Withdrawn EP2715624A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
DE102011076766 2011-05-31
DE102011086352A DE102011086352A1 (de) 2011-05-31 2011-11-15 Verfahren und Diagnosesystem zur Unterstützung der geführten Fehlersuche in technischen Systemen
PCT/EP2012/058468 WO2012163634A1 (fr) 2011-05-31 2012-05-08 Procédé et système de diagnostic servant à assister la recherche d'erreur guidée dans des systèmes techniques

Publications (1)

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EP2715624A1 true EP2715624A1 (fr) 2014-04-09

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US (1) US20140188433A1 (fr)
EP (1) EP2715624A1 (fr)
CN (1) CN103608815B (fr)
DE (1) DE102011086352A1 (fr)
WO (1) WO2012163634A1 (fr)

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CN109800895A (zh) * 2019-01-18 2019-05-24 广东电网有限责任公司 一种基于增强现实技术在计量自动化流水线故障预警和维护的方法
CN110716528A (zh) * 2019-09-17 2020-01-21 湖州职业技术学院 基于专家系统的大型液压机远程故障诊断方法与装置

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DE102011086352A1 (de) 2012-12-06
US20140188433A1 (en) 2014-07-03
CN103608815B (zh) 2017-02-15
WO2012163634A1 (fr) 2012-12-06
CN103608815A (zh) 2014-02-26

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