WO2006105930A1 - Systeme de diagnostic pour etablir une liste ponderee d'elements eventuellement defectueux a partir de donnees d'un vehicule et d'indications d'un client - Google Patents

Systeme de diagnostic pour etablir une liste ponderee d'elements eventuellement defectueux a partir de donnees d'un vehicule et d'indications d'un client Download PDF

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Publication number
WO2006105930A1
WO2006105930A1 PCT/EP2006/003049 EP2006003049W WO2006105930A1 WO 2006105930 A1 WO2006105930 A1 WO 2006105930A1 EP 2006003049 W EP2006003049 W EP 2006003049W WO 2006105930 A1 WO2006105930 A1 WO 2006105930A1
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WIPO (PCT)
Prior art keywords
error
diagnostic
diagnostic system
focus
components
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PCT/EP2006/003049
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German (de)
English (en)
Inventor
Martin Konieczny
Harald Renninger
Moritz SCHULÈ
Marc Schuller
Darko Tislaric
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Daimlerchrysler Ag
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Application filed by Daimlerchrysler Ag filed Critical Daimlerchrysler Ag
Publication of WO2006105930A1 publication Critical patent/WO2006105930A1/fr

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278—Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Definitions

  • the invention relates to a computer-aided diagnostic system that generates a weighted list of possibly defective motor vehicle components with the aid of a diagnostic program from vehicle data and customer information.
  • the identification of the possible error candidates takes place via an evaluation of a rule table reflecting the diagnostic knowledge.
  • the additional evaluation of vehicle functions possibly affected by the error candidates also extends the troubleshooting space.
  • the service technician can restrict troubleshooting to selected fault codes or functions by setting a focus within the determined troubleshooting space. Only the possible candidates for the selected error codes or functions will then be considered.
  • the error candidates belonging to this focus set are weighted by offsetting several error probabilities for error codes, components and affected functions or error symptoms.
  • known bugs which are coupled error codes, possibly also symptoms that always occur together, can be used for the billing.
  • the characteristic of the system diagnosis is the mapping of the system to be diagnosed into at least one physical-mathematical model that can be implemented and processed with computer assistance.
  • the modeling comprises a structural model and an impact model, which is often referred to as a behavioral model.
  • the structure model depicts the physical relationships of the individual components of the technical system, and the behavioral model maps the functions of the individual components of the system.
  • a knowledge base which is essentially a rule table from If / then conditions, which in turn can be mapped to data tuples, the diagnostic knowledge relevant for the system diagnostics is stored. With the system diagnostics a fault detection and by recourse to the knowledge base a computer-aided troubleshooting can be carried out.
  • System diagnostics has two major disadvantages.
  • the modeling is extremely expensive for larger technical systems, such as a motor vehicle, if all possible causes of faults are to be controlled by the system.
  • Even more difficult to handle in system diagnostics are ambiguous system states, eg if a recorded error code can have several causes that can not be further processed by the system diagnostics due to the lack of sufficient error environment data or insufficient information about the current system state.
  • the system diagnostics then stops at this point without diagnostic result.
  • Another disadvantage of the system diagnosis is its basic unsuitability for the processing of experience of the service technician. Nor can Customer information on defective functions or on intact functions in the diagnostic process.
  • Diagnostic systems of the aforementioned type have the further disadvantage that they very quickly become very complex and the necessary modeling effort, calculation effort and calculation effort for larger technical systems increases exponentially with the number of error possibilities of the individual components of the overall system.
  • all possible checks must be mapped into a static audit trail for the diagnosis.
  • in reality in systems with multiple interdependent components, there are a plethora of ways in which individual sub-checks of individual components can be performed. With 5 components already theoretically 5 faculties result in different test procedures, which would all have to be represented by a static test tree. The efficiency of the diagnostic methods therefore decreases drastically with the number of possible errors.
  • the solution succeeds mainly with an interactively operating diagnostic program, in which the service technician can set a focus for the further, automated troubleshooting by the diagnostic program within a troubleshooting space, which is initially defined by the diagnostic program, of the possibly identified components or functions.
  • Focusing can be done by limiting it to an error code or by restricting it to an impaired function or error symptom. After setting the focus becomes a limited focus amount, which is the selected focus possible error candidates selected.
  • the individual error candidates hereby - by offsetting different probabilities for the occurrence of an error code, for the probability of failure of a component or function and possibly for the presence of an error image - a weighting.
  • the diagnostic system has the additional possibility of processing error images.
  • Fault images here are combinations of several fault codes that are specific to the failure of a particular component or a small amount of components and so can provide a direct indication of the defective component (s).
  • the error images can be formed from a combination of active and inactive error codes and symptoms.
  • the non-active error codes can provide particularly valuable information on non-defective components and thus limit the number of possible error candidates.
  • a new focus can be set by the service technician and thus a new focus set with weighted error candidates can be generated.
  • the symptoms and error codes affected by this component can be inferred for the presence of a multiple error. Again, this can be done by setting the focus again On the post-declared symptoms or error codes the search will be restarted.
  • a new focus can also be offered very specifically to the service technician.
  • neighborhood relationships of cause sets or candidate sets e.g. of error codes, be exploited.
  • the search can therefore be extended to other neighboring causes.
  • candidate sets that were not explained by a found error may be suggested as a new focus.
  • the knowledge base of the diagnostic system can be expanded with field experience from the operation of motor vehicles in order to optimize the diagnostic process.
  • the error weights g (Kj) can be adapted.
  • more error images FB can be detected and added via field data evaluation, which can then be used immediately in a subsequent diagnostic session application.
  • the service technician is given an indication of the presence of a phantom error.
  • a reliability variable for example P (FC
  • the service technician By weighting the error candidates within the focus set, the service technician is given a prioritization that gives him an indication of which of the possible components is most likely to be defective. This provides the service technician with information about which components he should first check in order to actually find a defective component as quickly as possible.
  • the system automatically offers at least one check for each component of the candidate list.
  • Fig. 1 A computerized diagnostic system for a
  • FIG. 2 shows a modular block diagram of the diagnostic system according to the invention with data flow relationships between the individual program modules and the input and output interfaces of the diagnostic system;
  • Figure 1 a situation is shown schematically, as it is known today in motor vehicle workshops.
  • a computer-aided diagnostic tester 1 is connected via a standardized diagnostic interface 2 to the communication network 3 for the control units 4 in the motor vehicle.
  • Known diagnostic testers are z.
  • the DAS system from DaimlerChrysler or the BMW DIS system.
  • the control units 4 installed in the motor vehicle are in communication with each other, for example via a data bus.
  • a common data bus in motor vehicles is the so-called CAN bus (for Controller Area Network).
  • CAN bus for Controller Area Network
  • error memory In the context of the self-diagnosis of the control units errors identified in coded form as so-called error codes by the control unit software in specially reserved memory areas, so-called error memory, with the help of the diagnostic routine in the control units.
  • error memory In the schematic representation of FIG. 1, these reserved, non-volatile memory areas are designated FS (for error memory).
  • FS for error memory
  • the standard for the Keyword Protocol 2000 includes two different application options. On the one hand, the standard stipulates that the communication between the diagnostic tester and the control units is effected via a gateway 5, which is eg. B. binds the motor vehicle CAN bus to the diagnostic interface 2, or takes place, as usual, the error memory of the control units via the so-called. K and L lines and read via the normalized diagnostic interface 2 directly into the diagnostic tester and stored can be.
  • a gateway 5 which is eg. B. binds the motor vehicle CAN bus to the diagnostic interface 2, or takes place, as usual, the error memory of the control units via the so-called.
  • K and L lines and read via the normalized diagnostic interface 2 directly into the diagnostic tester and stored can be.
  • FIG. 1 shows the more modern form of access via a CAN bus and thus via a gateway.
  • the invention is of concern only that there is at least one way to be able to read the error memory of the control units with a diagnostic tester.
  • the transmitted contents of the control device memory, in particular error codes and status data of the control devices are further processed in a diagnostic session with an implemented diagnostic program.
  • the diagnostic program also includes the option of manually inputting further information that is important for a diagnosis via a computer workstation as a human-machine interface.
  • FIG. 2 shows a block diagram of the most important program modules and realized with these program modules Functionally a diagnostic system according to the invention.
  • the individual program modules are integrated into a higher-level sequence control of the entire diagnostic system. This sequence control takes over the call of the individual program modules at the respectively necessary time.
  • the diagnostic system processes error codes FC and inputs by a service technician as input variables.
  • the service technician makes his inputs from a VDU workstation 200, which is typically equipped with a screen and a computer keyboard, each connected to the computer system 201 of the diagnostic system. Via a further interface 202, the computer system can be connected to the motor vehicle to be diagnosed. About the OBD socket (On Board Diagnosis), the control units contained in the motor vehicle can be addressed.
  • OBD socket On Board Diagnosis
  • the self-diagnosis routines of the control units can be started and thereby functional test of the individual control units are started and it can be accessed and read current system state data from the motor vehicle.
  • One possibility of the technical realization was discussed in connection with FIG.
  • the diagnostic program implemented on the computer system is characterized among other things by a modular structure.
  • the programming and the configuration of the diagnostic system are structured.
  • a first program module 210 according to its function called rule table evaluation, retrieved from the motor vehicle data, such as error codes and system status data to the individual components installed in the motor vehicle, read and processed.
  • the further processing includes checking of rule tables stored in a knowledge base 211.
  • the rule tables contain the diagnostic knowledge relevant for the technical system to be diagnosed. This knowledge is stored, for example, in compressed form in data tuples.
  • the data tuples depict the relationships between the information contained in them.
  • a data tuple is stored for each diagnostic rule.
  • a data tuple consists in each case of a component identifier Ki, an error code FCi, a symptom sympi as an indication of an affected technical function or for the possible fault effect observed by the driver, and a system status Stat.
  • the rule table evaluation then takes place in such a way that in the totality of all stored data tuples it is checked which data tuples contain the read code (s) and which components Ki and functions / error symptoms Sympi are named in the identified data tuples and thus can be affected by the observed error FCi.
  • the component identifications found in this way are recorded and combined into a first quantity of error candidates and stored.
  • the troubleshooting space formed by the first candidate set is further developed.
  • the possible sources of error are now extended by the relevant functions that may be involved in the motor vehicle.
  • the rule tables are searched again, this time not according to detected error codes, but according to the possibly already affected by the error codes components Ki.
  • the components that are to be affected are the possibly affected Sympi functions. These two quantities do not have to be identical. Because it is possible that an error code refers to a component that is relevant for several functions.
  • the result of this second pass through the knowledge base is a supplemented candidate list 214, which now also contains possibly faulty functions in addition to the possibly faulty components.
  • On-screen workstation 200 performed a query 215 and displayed whether for further processing, the already determined error codes or the determined possibly affected functions to be displayed. About the difference is related below with the Described description of Figure 3 in more detail.
  • the service technician is offered the opportunity to set a focus for the further diagnostic procedure. Depending on the selected display, the focus is set by either selecting a displayed error code or a displayed, suspicious function Sympi by means of graphical menu control, and using it for further processing by the diagnostic program. If the focus is set, further data processing is restricted to this focus. This means that not all detected error codes, suspicious candidates or suspicious functions are considered, but only those that fall under the chosen focus.
  • the individual error candidates are subjected to a weighting in a further program module or method step 217.
  • the probabilities of the error codes FCi For the weighting, the probabilities of the error codes FCi, the probability of the occurrence of sympi and possibly the probability of the occurrence of error images must be calculated. For this purpose, probabilities must be provided which specify with which certainty a defective component or a candidate Ki an error code (P (FCi
  • the relative error weighting g (Kj) of a component itself is needed. This information is needed to calculate the prioritized or weighted candidate list.
  • the conditional probabilities are easy to estimate. Usually they are set to "1.” However, insecure symptoms or error codes can sometimes assume values of less than 1.
  • the error weights g (Kj) can be derived from experience eg can be selected between one and one hundred and represent a relative failure characteristic.
  • the current field events can also be taken into account via these error weights g (Kj) by adapting these weights by calculating error frequencies.
  • All probabilities and error weights are stored in the database of the diagnostic system 218. Appropriately, these can be stored and fed together with the component list, the function or sympotom list and the error image list. These lists are created in the construction of a motor vehicle and therefore need only be supplemented by the experience with regard to the conditional Wahrscheointechniken and the error weights. Expediently, the data is model-specific. However, cross-product databases can also be created and used. For cross-database databases, however, the possibility of a series-specific selection, e.g. be kept in the form of an upstream master table.
  • G is a scaling quantity and is defined in a preparation step or by a calculation, eg as the sum of all weights g (KJ).
  • the calculation of a prioritized or weighted candidate list 219 can be initiated and finally displayed on the display of the Computer workstation 200 are output.
  • the a posteriori error probability or priority Prio (Ki) of a component Ki results from the following product:
  • This priority is still not standardized and can alternatively be normalized by dividing by the sum of all candidate priorities.
  • the data type is -double- to use because of the possibility that the prioritization value of a candidate can take a very small floating-point value. It must be checked after each calculation that the prioritization value of a candidate within the focus set does not become 0. Should this nevertheless occur, the smallest, possible, positive numerical value must be used for the relevant prioritization value for the data format double.
  • the calculation of the weighted candidate list can be run through several times within a diagnostic session. This is e.g. necessary if the review of the candidates from the first focus quantity by the service technician has not led to a positive result. In this case, the service technician must be able to create a different candidate list by choosing a different focus. The same applies to assumptions of multiple errors.
  • a short test 310 is first started. With this short test, the self-diagnostic routines of the control units installed in the motor vehicle are started and then, in a following method step 311, the error memories of the control units are read out and a list of all actively set error codes possibly generated with the associated error environment data. Subsequently, in a further method step 312, a rule is selected by means of a master table which is valid for the diagnosis of the motor vehicle to be examined.
  • the identification of the vehicle and the identification of the valid control tables can in this case, for example, via the vehicle identification number respectively.
  • the possibly affected components, further functions and error patterns are determined for the reported error codes and for the reported malfunctions.
  • a decision step 315 the service technician is given the opportunity to continue the diagnostic session with an error code-based display or a function-based display, after the error codes already determined and the malfunctions identified have been displayed to him.
  • the function-based method of operation has particular advantages if the service technician intends to include customer information on functioning and non-functioning subsystems in the diagnostic process.
  • the function-based representation in particular allows the processing of only symptomatic known malfunctions, as is usually the case with customer complaint.
  • the rules to be evaluated which fired in the runs of the rules table evaluation according to steps 313 and 314, ie containing either the observed error code or an observed error symptom, may be compressed in an alternative further method step for further calculations .
  • syntax constituents and semantic constituents of the diagnostic rules can be derived from the knowledge base eliminated and the diagnostic rules are compressed into number tuples.
  • the possibly affected defect images can be determined for the fault codes or fault symptoms that are in focus and included in the further calculation.
  • the diagnostic flow proceeds to step 319 where the error probabilities for components and thus the prioritization or weighting of the suspected components are calculated. If the prioritization is fixed, the prioritized error candidates are displayed to the service technician along with their prioritization. The service technician then checks the individual components or candidates at his option. The result of its check decides in a further query step 321 whether the diagnostic procedure and thus the diagnostic program jump back to decision step 315 or not. If the error was found, the diagnostic session ends. If no error has been found, the diagnostic session is continued and the service technician has the option to set a different focus in the next run.
  • a function tree is displayed in the next step 322 in which the suspect functions are optically highlighted become.
  • the service technician can also use the function-based representation in a following method step 323 set a focus for the further diagnostic procedure.
  • the control tables of the diagnostic system are evaluated a second time after setting the focus in the following method step 324. This is necessary in order to supplement the troubleshooting space for the suspicious components and to build them up as completely as possible. In one function, several components and their interaction are usually used.
  • the components were only determined using the error codes. Operation via function-based focussing also allows the troubleshooting space to be extended to those components that can be identified by the function and that have not previously been identified by an error code.
  • the diagnostic program may then continue with the alternative data compression method step 317 or with the error determination procedure step 318.

Abstract

L'invention concerne un système de diagnostic informatisé qui permet d'établir une liste pondérée d'éléments d'un véhicule éventuellement défectueux au moyen d'un programme de diagnostic et à partir de données d'un véhicule et d'indications d'un client. Les candidats éventuellement défectueux sont identifiés par interprétation d'un tableau de règles illustrant les connaissances en matière de diagnostic. Le champ de recherche de défectuosités est étendu par l'évaluation supplémentaire de fonctions du véhicule éventuellement touchées par les éléments défectueux. Le technicien de service après-vente peut limiter la recherche de défectuosités à des codes de défectuosités sélectionnés ou à des fonctions sélectionnés par l'application d'une focalisation à l'intérieur du champ de recherche de défectuosités déterminé. Seuls les candidats éventuels correspondant aux codes de défectuosités ou aux fonctions sélectionnés sont alors pris en considération. Les candidats défectueux faisant partie du groupe de focalisation font l'objet d'une pondération par le calcul de plusieurs probabilités de défectuosités pour des codes de défectuosités, des composants et des fonctions concernées. Il est également possible d'utiliser, pour ce calcul, des schémas de défectuosités connus, à savoir des codes de défectuosités couplés qui apparaissent toujours ensemble.
PCT/EP2006/003049 2005-04-06 2006-04-04 Systeme de diagnostic pour etablir une liste ponderee d'elements eventuellement defectueux a partir de donnees d'un vehicule et d'indications d'un client WO2006105930A1 (fr)

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DE102005015664.9 2005-04-06
DE200510015664 DE102005015664A1 (de) 2005-04-06 2005-04-06 Diagnosesystem zur Bestimmung einer gewichteten Liste möglicherweise fehlerhafter Komponenten aus Fahrzeugdaten und Kundenangaben

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010091903A1 (fr) * 2009-02-16 2010-08-19 Robert Bosch Gmbh Procédé et dispositif de relevé et de transfert de données de fonctionnement d'un moteur à combustion interne
EP2284631A1 (fr) * 2009-07-17 2011-02-16 Siemens Aktiengesellschaft Procédé de fonctionnement d'un système de diagnostic de véhicule, programme de commande et système de diagnostic de véhicule
EP2369435A1 (fr) * 2010-03-19 2011-09-28 Hamilton Sundstrand Corporation Approche bayésienne pour identifier une défaillance d'un sous-module
CN102393732A (zh) * 2011-10-24 2012-03-28 力帆实业(集团)股份有限公司 车辆故障诊断方法
US20120116631A1 (en) * 2010-11-09 2012-05-10 Kia Motors Corporation Scheduled vehicle management system and method
WO2013152826A1 (fr) * 2012-04-12 2013-10-17 Audi Ag Procédé pour faire fonctionner un système de diagnostic et système de diagnostic
EP3569999A1 (fr) * 2018-05-14 2019-11-20 CLAAS Selbstfahrende Erntemaschinen GmbH Unité de diagnostic pour maintenir des systèmes d'entraînement pour entraîner des machines de travail agricoles
EP3741196A1 (fr) * 2019-05-14 2020-11-25 CLAAS Selbstfahrende Erntemaschinen GmbH Procédé de détermination d'une cause de défaut dans une machine de travail agricole
US11403895B2 (en) 2016-08-12 2022-08-02 Snap-On Incorporated Method and system for providing diagnostic filter lists
US11887413B2 (en) 2016-08-12 2024-01-30 Snap-On Incorporated Method and system for displaying PIDs based on a PID filter list

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102006018831A1 (de) * 2006-04-22 2007-10-25 Daimlerchrysler Ag Kraftfahrzeugdiagnose und Fahrzeugannahme
DE102007010978A1 (de) 2007-03-05 2008-09-11 Volkswagen Ag Verfahren und Vorrichtung zur Unterstützung einer Diagnose eines elektrischen Systems mittels wahrscheinlichkeitsbasierter Fehlerkandidatenermittlung
DE102007015140A1 (de) * 2007-03-29 2008-10-02 Volkswagen Ag Diagnosevorrichtung und Diagnoseverfahren zum Ausführen einer Diagnose eines mechatronischen Systems
DE102007018732A1 (de) * 2007-04-20 2008-10-23 Volkswagen Ag Diagnosesystem und Verfahren zum Erstellen eines Prüfablaufs für eine Diagnose eines mechatronischen Gesamtsystems
DE102007045255B4 (de) 2007-09-21 2021-11-18 Volkswagen Ag Verfahren zur Herstellung eines Diagnosesystems, insbesondere für ein Kraftfahrzeug
DE102008051016A1 (de) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Verfahren zur Unterstützung bei der Ausbildung an Fahrzeugen bzw. Fahrzeugsystemen mit und ohne Waffensysteme
DE102008058545A1 (de) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Verfahren zur Steigerung der Effizienz von Fahrzeugen bzw. Fahrzeugsystemen mit und ohne Waffensysteme
DE102008051017A1 (de) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Verfahren zur Steigerung der Effizienz von Fahrzeugen bzw. Fahrzeugsystemen mit und ohne Waffensysteme

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5442555A (en) * 1992-05-18 1995-08-15 Argonne National Laboratory Combined expert system/neural networks method for process fault diagnosis
DE19523483A1 (de) * 1995-06-28 1997-01-02 Daimler Benz Ag Rechnergestützte Fehlerdiagnoseeinrichtung für ein komplexes technisches System
DE10307365A1 (de) * 2003-02-21 2004-09-09 Volkswagen Ag Vorrichtung und Verfahren zur Fehlerdiagnose bei Fahrzeugen

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
SE9803088L (sv) * 1998-09-10 1999-12-20 Mecel Ab Metod och system för diagnosticering av sammansatta distribuerade system, företrädesvis implementerade i fordon
GB2350443A (en) * 1999-05-22 2000-11-29 Luk Getriebe Systeme Gmbh Diagnostic system, particularly for motor vehicles
DE10315344B8 (de) * 2003-04-03 2010-02-11 Audi Ag Verfahren und Vorrichtung zur Erkennung fehlerhafter Komponenten in Fahrzeugen
DE10323384A1 (de) * 2003-05-23 2004-12-16 Daimlerchrysler Ag Diagnosesystem

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5442555A (en) * 1992-05-18 1995-08-15 Argonne National Laboratory Combined expert system/neural networks method for process fault diagnosis
DE19523483A1 (de) * 1995-06-28 1997-01-02 Daimler Benz Ag Rechnergestützte Fehlerdiagnoseeinrichtung für ein komplexes technisches System
DE10307365A1 (de) * 2003-02-21 2004-09-09 Volkswagen Ag Vorrichtung und Verfahren zur Fehlerdiagnose bei Fahrzeugen

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
LAUBER J ET AL: "AUTONOMOUS AGENTS FOR ONLINE DIAGNOSIS OF A SAFETY-CRITICAL SYSTEM BASED ON PROBABILISTIC CAUSAL REASONING", PROCEEDINGS. ISADS. INTERNATIONAL SYMPOSIUM ON AUTONOMOUS DECENTRALIZED SYSTEMS, 1999, pages 213 - 219, XP000949345 *
WALESCHKOWSKI N ET AL: "EIN WISSENSBASIERTES FAHRZEUG-DIAGNOSESYSTEM FUER DEN EINSATZ IN DER KFZ-WERKSTATT", GRUNDLAGEN UND ANWENDUNGEN DER KUENSTLICHEN INTELLIGENZ, September 1993 (1993-09-01), pages 277 - 291, XP002065987 *
WALESCHKOWSKI N ET AL: "WISSENSMODELLIERUNG UND WISSENSERWERB AM BEISPIEL DER FAHRZEUGDIAGNOSE", KUENSTLICHE INTELLIGENZ, BRAUNSCHWEIG, DE, January 1995 (1995-01-01), pages 55 - 61, XP002065986, ISSN: 0940-0699 *

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8612125B2 (en) 2009-02-16 2013-12-17 Robert Bosch Gmbh Method and device for acquiring and transmitting operating data of an internal combustion engine
WO2010091903A1 (fr) * 2009-02-16 2010-08-19 Robert Bosch Gmbh Procédé et dispositif de relevé et de transfert de données de fonctionnement d'un moteur à combustion interne
EP2284631A1 (fr) * 2009-07-17 2011-02-16 Siemens Aktiengesellschaft Procédé de fonctionnement d'un système de diagnostic de véhicule, programme de commande et système de diagnostic de véhicule
EP2369435A1 (fr) * 2010-03-19 2011-09-28 Hamilton Sundstrand Corporation Approche bayésienne pour identifier une défaillance d'un sous-module
JP2011199867A (ja) * 2010-03-19 2011-10-06 Hamilton Sundstrand Corp サブモジュールの故障を特定するベイズ法
US8458525B2 (en) 2010-03-19 2013-06-04 Hamilton Sundstrand Space Systems International, Inc. Bayesian approach to identifying sub-module failure
US20120116631A1 (en) * 2010-11-09 2012-05-10 Kia Motors Corporation Scheduled vehicle management system and method
CN102393732A (zh) * 2011-10-24 2012-03-28 力帆实业(集团)股份有限公司 车辆故障诊断方法
CN102393732B (zh) * 2011-10-24 2013-05-22 力帆实业(集团)股份有限公司 车辆故障诊断方法
WO2013152826A1 (fr) * 2012-04-12 2013-10-17 Audi Ag Procédé pour faire fonctionner un système de diagnostic et système de diagnostic
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US11403893B2 (en) * 2016-08-12 2022-08-02 Snap-On Incorporated Method and system for providing diagnostic filter lists
US11694491B2 (en) 2016-08-12 2023-07-04 Snap-On Incorporated Method and system for providing diagnostic filter lists
US11887413B2 (en) 2016-08-12 2024-01-30 Snap-On Incorporated Method and system for displaying PIDs based on a PID filter list
EP3569999A1 (fr) * 2018-05-14 2019-11-20 CLAAS Selbstfahrende Erntemaschinen GmbH Unité de diagnostic pour maintenir des systèmes d'entraînement pour entraîner des machines de travail agricoles
EP3741196A1 (fr) * 2019-05-14 2020-11-25 CLAAS Selbstfahrende Erntemaschinen GmbH Procédé de détermination d'une cause de défaut dans une machine de travail agricole

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