DE102005015664A1 - Diagnostic system for determining a weighted list of potentially defective components from vehicle data and customer information - Google Patents

Diagnostic system for determining a weighted list of potentially defective components from vehicle data and customer information

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Publication number
DE102005015664A1
DE102005015664A1 DE200510015664 DE102005015664A DE102005015664A1 DE 102005015664 A1 DE102005015664 A1 DE 102005015664A1 DE 200510015664 DE200510015664 DE 200510015664 DE 102005015664 A DE102005015664 A DE 102005015664A DE 102005015664 A1 DE102005015664 A1 DE 102005015664A1
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DE
Germany
Prior art keywords
error
diagnostic
diagnostic system
focus
system according
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Application number
DE200510015664
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German (de)
Inventor
Martin Dipl.-Ing. Konieczny
Harald Dipl.-Math. Renninger
Moritz Dipl.-Inf. Schule
Marc Schuller
Darko Dipl.-Ing. Tislaric
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Daimler AG
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DaimlerChrysler AG
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Priority to DE200510015664 priority Critical patent/DE102005015664A1/en
Publication of DE102005015664A1 publication Critical patent/DE102005015664A1/en
Application status is Withdrawn legal-status Critical

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Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Abstract

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. Alternatively, still known error images, which are coupled error codes that always occur together, can be used for the billing.

Description

  • The The invention relates to a computer-aided diagnostic system that with Help of a diagnostic program from vehicle data and customer information a weighted list of possibly created faulty motor vehicle components. The identification the possible Error candidates take place over an evaluation of a rule table reflecting the diagnostic knowledge. By the additional Evaluation of possibly also affected by the error candidates Vehicle features will expand the troubleshooting space. The service technician can by setting a focus within the determined troubleshooting space, troubleshooting on selected Restrict error codes or functions. It will be only the to the selected ones Error codes or functions possible Contestants further considered. The error candidates belonging to this focus set are calculated by calculating several error probabilities for error codes, Weighted components and affected functions or error symptoms. Alternatively you can for the Compute still known error images, these are coupled error codes, possibly synonymous symptoms that always occur together, consulted become.
  • An example of a system diagnosis is in the German patent application DE 195 23 483 A1 disclosed. 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. In the DE 195 23 483 A1 modeling involves a structural model and an impact model, 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. In 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 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.
  • The System diagnostics has two major disadvantages. The modeling is for larger technical systems, such as. a motor vehicle extremely expensive, if all possible Causes of errors to be controlled by the system. Even more difficult In system diagnostics, ambiguous system states are to be handled when e.g. a recorded error code can have multiple causes in the absence of sufficient error environment data or insufficient information about the current system status, from the system diagnostics not further can be processed. The system diagnostics will then break at this point without diagnostic result from. Another disadvantage of system diagnostics is their principle Unsuitability for the processing of experience of the service technician. As well Customer information is limited to defective functions or to intact functions in the diagnostic process incorporated.
  • diagnostic systems of the aforementioned type have the further disadvantage that they are very quickly become very complex and the necessary modeling effort, Computing effort and calculation effort for larger technical systems exponential with the number of error possibilities of the individual components of the overall system increases. Also, for the diagnosis all possible exams into a static test step tree be imaged. In reality results in systems with several interdependent components a plethora of possibilities in which order individual partial tests of individual components carried out can be. With 5 components there are already theoretically 5 faculty different Test procedures, the all through a static test tree would have to be pictured. The efficiency of the diagnostic procedures therefore decreases with the number of possible errors drastically.
  • you therefore has more efficient options sought to build a diagnostic system.
  • One way to improve the diagnostic process is in the European patent specification EP 1 069 487 B1 described. In parallel with the repair progress, knowledge saved by a service technician at crucial points of the test step tree, known as evidence, can be queried and included in the diagnostic system. This eliminates the need to calculate all possible errors and test options. The diagnostic method can become more efficient the more queries are provided at the appropriate point of the diagnostic procedure on the system side. The input of the evident knowledge takes place via a user interface, which is formed by a display and an input menu.
  • The cost effectiveness of the tests to be performed is desirable for troubleshooting future workshops with diagnostic systems. A quick and efficient test procedure is therefore a good idea worthwhile specification for these future diagnostic systems.
  • Task according to the invention It is therefore a diagnostic system to indicate that a meaningful reduction allows troubleshooting and that is also capable of providing an economically meaningful exam sequence for troubleshooting and repair of the to be tested, technical system.
  • The Task is solved with a diagnostic system and a diagnostic method according to claim 1. Further advantageous embodiments are in the subclaims and included in the following description.
  • The solution succeeds mainly with an interactive diagnostic program, in which the service technician, within a troubleshooting space initially opened by the diagnostic program as possibly Defective identified components or functions, a focus for the set further, automated troubleshooting by the diagnostic program can. The setting of the focus can be limited by this an error code or by restriction to an impaired one Function or error symptom. After setting the focus becomes a limited Focus quantity corresponding to the selected Focus possible Error candidate selected. The individual error candidates learn here - by offsetting different Probabilities for the occurrence of an error code, for the probability of default a component or function and, if applicable, its presence of a defect image - one Weighting.
  • In an advantageous embodiment the diagnostic system according to the invention has the diagnostic system over the extra possibility To process error images. Error pictures are combinations here multiple error codes that are specific to the failure of a particular one Component or a small amount of components and so a direct Can supply information on the defective component (s). The error pictures can hereby a combination of active and inactive error codes and symptoms are formed. The non-active error codes can be used here provide particularly valuable information on non-defective components and so the amount of possible Restrict error candidates.
  • In a further advantageous embodiment of the invention, if the review of Candidates in the focus set revealed that none of the examined Components was broken, a new focus by the service technician and thus a new focus set with weighted error candidates be generated.
  • In a further advantageous embodiment of the invention can according to Finding a defective component by clarifying the Symptoms and DTCs affected by this component Multiple error can be closed. Also in this case can through resetting focus on the post-declared symptoms or error codes the search will be restarted.
  • In a further advantageous embodiment of the invention can e.g. in case no error was found, a new focus as well very specifically offered to the service technician. This can be neighborhood relations of cause quantities, e.g. of error codes, be exploited. So the search can target other neighbors Causes quantities are extended. In the case of multiple errors, candidate quantities, that were not explained by a found bug as a new focus be proposed.
  • In a further advantageous embodiment of the diagnostic system can provide the knowledge base of the diagnostic system with field experiences be extended to the operation of motor vehicles, thus the diagnostic process to optimize. about Field experience, e.g. Error rates, can the error weights g (Kj) are adapted. Furthermore, via field data evaluation further error images FB can be detected and added, which then immediately can be used in a subsequent diagnostic session.
  • In a further advantageous embodiment of the diagnostic system, the service technician is given an indication of the presence of a phantom error. For this, a reliability variable -for example P (FC | ⁣ not Kj) - must be provided for error codes, error images and symptoms, for example in the form of a bit or a further probability. This reliability indicates whether the error code in question (as well as fault pattern, symptom) can also occur without a physical reason for the error. Then, if further error checking does not find an error in the focus, then the reliabilities of the one for the prioritized candidate list are computed Sizes tested. If all the information used in this sense is not reliable or safe, there may be a phantom error.
  • With the invention mainly the following advantages are achieved:
    Due to the interactive design of the diagnostic system, it is possible to incorporate the experience of service technicians during the repair process in the repair and diagnostic process. By setting a focus within a spanned troubleshooting space, the information to be processed is drastically reduced for further diagnostics. As a result, even for complex systems, a further, automated diagnostic procedure is possible, which leads to a reusable result in a workshop environment in acceptable process times.
  • By Weighting of the error candidates within the focus amount is the Service technician given a prioritization to the hand, with the giving him an indication, whichever of the possible components is most likely is defective. This will alert the service technician which components he should check first, to a defective component as possible fast indeed find. The system automatically offers at least one exam for every Component of the candidate list.
  • in the The following is the computer-aided Diagnostic system explained in more detail with reference to graphical representations.
  • there demonstrate:
  • 1 A computerized diagnostic system for a motor vehicle as is well known and established in the art;
  • 2 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;
  • 3 A flow chart for the diagnostic program according to the invention;
  • In 1 a situation is schematically illustrated, as it is known today in motor vehicle workshops. For the diagnosis of a motor vehicle is a computer-aided diagnostic tester 1 via a standardized diagnostic interface 2 to the communication network 3 for the control units 4 connected in the motor vehicle. Known diagnostic testers are, for example, the DAS system from DaimlerChrysler or the BMW-DIS system. The control units installed in the motor vehicle 4 For example, they are in communication with each other via a data bus. A common data bus in motor vehicles is the so-called CAN bus (for Controller Area Network). Each of the installed control units in the motor vehicle has the ability to self-diagnose in addition to the communication interfaces. 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 fault memory, are written with the aid of the diagnostic routine in the control units. In the schematic representation of 1 For example, these reserved, non-volatile memory areas are referred to as FS (for error memory). For the communication and for the data exchange between a diagnostic tester and the control units installed in the motor vehicle, a standard has been established, known under the name Keyword Protocol 2000, whose specification and standardization can be found in ISO standard 14 230-3. With the control commands and data formats agreed upon in the Keyword Protocol 2000, it is possible to use the diagnostic interface to read out the codified contents of the fault memories of the individual control devices with the aid of the diagnostic tester and to transfer them to the computing system of the diagnostic tester. The standard for the keyword protocol 2000 comprises two different application options. On the one hand, the standard stipulates that the communication between the diagnostic tester and ECUs is via a gateway 5 , for example, the motor vehicle CAN bus to the diagnostic interface 2 binds, takes place or that, as was customary in the past, the fault memory of the control units via the so-called K and L lines and the standardized diagnostic interface 2 can be read out and stored directly in the diagnostic tester. In the schematic representation of 1 is the more modern form of access via a CAN bus and thus represented by a gateway. For 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. In the diagnostic tester, the transmitted contents of the control unit memory become error codes and status data in particular the control units processed with an implemented diagnostic program in a diagnostic session. The diagnostic program also includes the option of manually entering additional information that is important for a diagnosis via a computer workstation as a human-machine interface.
  • 2 shows as a block diagram the most important program modules and realized with these program modules functions of 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 input from a computer workstation 200 , which is typically equipped with a screen and a computer keyboard, each to the computer system 201 connected to the diagnostic system. About another 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. It can be read out the error memory of the control units, 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 technical realization was related to 1 discussed.
  • However, the processing of the system data and the course of the diagnostic program deviate significantly in the invention from the known prior art. The most important differences here are the interactive course of the diagnostic program and the associated possibility of forming targeted diagnostic focuses, in which one or more focal points, referred to hereinafter as foci, can be set for debugging, thus improving both the diagnostic quality and the duration of the diagnosis can. The program implementation will be described in more detail below:
    The diagnostic program implemented on the computer system is characterized among other things by a modular structure. As a result, among other things, the programming and the configuration of the diagnostic system are structured. With 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 for each component installed in the motor vehicle, read and processed. Further processing involves checking in a knowledge base 211 saved rule tables. 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.
  • These Component identifiers Ki give an indication of which component or component also which function of the technical system for the observed error code or for the observed error symptom can be the cause. Result This first scouring of the knowledge base is a first set suspicious components, the over due to the identification the error codes FCi were determined.
  • In a further processing step or program module 213 the troubleshooting space formed by the first candidate set is further developed. In a second pass through the knowledge base, the possible sources of error are now extended by the relevant functions that may be involved in the motor vehicle. For this purpose, 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.
  • Arrived at this point, now begins the possibility of interaction in the further course of Di agnoseprogramms. First, on the screen workstation 200 a query 215 performed and displayed whether the already determined error codes or the determined possibly affected functions should be displayed for further processing. About the difference will be discussed below in connection with the description 3 discussed in more detail. In both cases, in a further process step 216 The service technician had 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.
  • For the components Ki which are still suspect within the focus, the individual error candidates are identified in a further program module or method step 217 subjected to a weighting.
  • For the weighting have to the probabilities of error codes FCi, the probability for the Occurrence of sympi and possibly the probability for the existence be calculated from defect images. This requires probabilities which indicate with what security a defective component or a candidate Ki an error code (P (FCi|⁣Kj)), a malfunction (P (Sympi|⁣Kj)) or an error image (P (FBi|⁣Kj)), cause. Furthermore becomes the relative error weighting g (Kj) of a component itself needed. This information will be for the calculation of the prioritized or weighted candidate list needed. The conditional probabilities are easy to estimate. Most of time they are set to "l". Uncertain symptoms or error codes can but sometimes accept values less than 1. The error weights g (Kj) can from experience, e.g. be chosen between one and a hundred and represent a relative failure characteristic. In a below explained advantageous embodiment can also over these error weights g (Kj) take into account the current field occurrence be by putting these weights over Offsetting of error frequencies be adapted.
  • All the probabilities and error weights are stored in the database when the diagnostic system is defined 218 stored. 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 Wahrscheoinlichkeiten and the error weights. Expediently, the data is model-specific. However, cross-product databases can also be created and used. In the case of cross-database databases, however, the possibility of a series-specific selection, eg in the form of an upstream master table, must then be maintained.
  • From the data explained above, the individual variables are calculated as follows:
    Figure 00140001
  • The become three calculated sizes to prepare the candidate prioritization, below. G is a normalization size and will in a preparation step or by means of e.g. as the sum of all Weights g (KJ) determined.
  • After the probabilities of the error codes P (FCi), the error images P (FBi) and the malfunctions P (Sympi) have been calculated and the focus quantity of the error candidates is determined, the calculation of a prioritized or weighted candidate list can be performed 219 and finally on the screen of the workstation 200 be issued.
  • The a posteriori error probability or priority Prio (Ki) of a component Ki results from the following product:
    Figure 00150001
  • In which applies: P (FCi|⁣K) = P (FCi) if the error code FCi is independent of a component K. and analogously P (Sympk|⁣Ki) = P (Sympk) and P (FBl|⁣Ki) = P (FBl) at independence from the respective component.
  • These priority is still not standardized and can alternatively be normalized by divided by the sum of all candidate priorities.
  • The following conditions apply to the individual calculations:
    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 be that the prioritization value of a candidate within the Focus amount does not become 0. Should this nevertheless occur, then for the concerned Prioritization value for the data format double smallest, possible, positive numerical value to use.
  • The Calculation of the weighted candidate list can be done within a Diagnostic session are repeated several times. This is e.g. necessary, if the review of Candidates from the first focus set by the service technician led to no positive findings Has. In this case, the service technician must have the opportunity have, by choosing a different focus, a different candidate list to create. something similar applies to multiple errors.
  • After the before described again with reference to the flowchart of 3 the diagnostic program implemented in the diagnostic system. At the beginning of a diagnostic session in the presence of at least one error code, a malfunction or an error symptom Symp is first a short test 310 started. With this short test, the self-diagnostic routines of the control units installed in the motor vehicle are started and then in a subsequent method step 311 , read out the error memory of the control units and generates a list of all active error codes possibly with the associated error environment data. Subsequently, in a further process step 312 by means of a master table which selects control tables valid for the motor vehicle to be examined for the diagnosis. The identification of the vehicle and the identification of the valid control tables can take place here, for example, via the vehicle identification number. In two further steps of the rule table evaluation 313 and the identification of relevant functions 314 For the reported error codes and the reported malfunctions, the possibly affected components, further functions and error images are determined.
  • In 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 fault 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.
  • Does he choose the error code based representation, ie in 3 the left branch of the flowchart, it becomes in the following step 316 given the opportunity to select from the error codes one of his experience suitable error code and thereby set a focus for the further diagnostic session. For the further calculations during the diagnostic session, the rules to be evaluated in the runs of the rule table evaluation according to the method steps 313 and 314 have fired, ie either the observed error code or an observed error symptom, are compressed in an alternative further process step for further calculations. During compression, syntax components and semantic components of the diagnostic rules from the knowledge base can be omitted and the diagnostic rules compressed into number tuples.
  • Also alternatively, in a further process step 318 for the fault codes or error symptoms in focus, the possibly affected faulty images are determined and included in the further calculation.
  • The diagnostic procedure continues with the procedure step 319 in which the error probabilities for components and thus the prioritization or weighting of the components suspected as being faulty 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 his review decides in another query step 321 Whether the diagnostic procedure and thus the diagnostic program return to the decision step 315 jump back 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.
  • The service technician selects the function-based representation in the decision step 315 So he chooses the right branch in the flowchart 3 , it will be in an alternative version of the diagnostic program in the next step 322 a function tree displayed, in which the suspect functions are highlighted. By selecting a suspected function, the service technician can also use the function-based representation in a subsequent method step 323 set a focus for the further diagnostic procedure. In the function-based operation of the diagnostic system are after setting the focus in the following process step 324 the control tables of the diagnostic system evaluated a second time. 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. In the previous steps, however, 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 can then use the alternative method step 317 the data compression or with the method step 318 continue the error image determination.

Claims (16)

  1. Computer-aided diagnosis system ( 1 ) for technical devices with an executable diagnostic program, which - with the implemented diagnostic program detects error codes or error symptoms (FCi, Sympi) of the technical device to be analyzed, - which with the diagnostic program has a knowledge base ( 211 ), is stored in the rule-based diagnostic knowledge about the technical device to be analyzed, searched for the detected error codes or error symptoms and determined from the rules involved the components, functions or error images and summarized in an error candidate set and stores, characterized in that the further course of the diagnostic program can be interactively influenced by setting a focus, wherein the setting of the focus is carried out either by selecting at least one error code (FCi) or by selecting at least one error symptom (Sympi).
  2. Diagnostic system according to claim 1, characterized that after setting the focus, the amount of error candidate on the elements still in focus are reduced to a focus amount and the components of the focus set according to their error probability be weighted.
  3. Diagnostic system according to claim 1 or 2, characterized that the amount of error candidate by multiple searches of the Knowledge base for error codes for the first and for error symptoms for another is formed.
  4. Diagnostic system according to one of claims 1 to 3, characterized in that for setting the focus either an error code based representation or an error symptom based Presentation interactive selectable is.
  5. Diagnostic system according to one of claims 1 to 4, characterized in that the weighting of the components in the focus set by offsetting relative error weights g (Kj), of conditional probabilities for the cause-effect relationships (P (FCi|⁣Kj), P (Sympi|⁣Kj) P (FBi|⁣Kj)), divided by a total weight G, yields.
  6. Diagnostic system according to one of claims 1 to 5, characterized in that the diagnostic program is constructed recursively and set a different focus each time the diagnostic program can be.
  7. Diagnostic system according to one of claims 1 to 6, characterized in that in the knowledge base error images are included, the error images from a combination of several Error codes exist that always appear together and in theirs Commonality characteristic of are a specific mistake.
  8. Diagnostic system according to one of claims 7, characterized marked that for the weighting of the components in the focus set, the defect images be consulted with.
  9. Diagnostic system according to one of claims 1 to 7, characterized in that of error codes via the detour via error causes (Candidates) on possible impaired Functions or other symptoms can be closed.
  10. Diagnostic system according to one of claims 1 to 9, characterized in that thus targeted for other symptoms asked back can or the service technician immediately other functions check yourself can.
  11. Diagnostic system according to one of claims 1 to 10 that candidates in the absence of error codes or symptoms can be relieved.
  12. Diagnostic system according to one of claims 1 to 11, characterized in that multiple errors by Nacherklären all Symptoms and error codes detected after a diagnosis and can then be treated further.
  13. Diagnostic system according to one of claims 1 to 12, characterized in that e.g. in the event that no error A new focus was also found specifically for the service technician can be offered.
  14. Diagnostic system according to one of claims 1 to 13, characterized in that the knowledge base continues to error setting conditions of error codes and other test requirements can be enriched.
  15. Diagnostic system according to one of claims 1 to 14, characterized in that the knowledge base around field experience is expandable.
  16. Diagnostic system according to one of claims 1 to 15, characterized in that phantom errors are detected.
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102006018831A1 (en) * 2006-04-22 2007-10-25 Daimlerchrysler Ag Vehicle diagnosis and vehicle acceptance
DE102007010978A1 (en) 2007-03-05 2008-09-11 Volkswagen Ag Electrical system's diagnosis supporting device for use in motor vehicle, has evaluation unit to produce list of incorrect components that are sorted based on dependence value, and output/supply unit to display or provide list
DE102007015140A1 (en) * 2007-03-29 2008-10-02 Volkswagen Ag Diagnosis device for implementing diagnosis of mechatronical system, has evaluation unit including analysis unit and test proposing unit that determines and proposes implementable diagnostic examination
DE102007018732A1 (en) * 2007-04-20 2008-10-23 Volkswagen Ag Diagnosis system for mechatronic overall system i.e. motor vehicle, has selecting unit selecting and combining generic tests from quantity of generic tests to test sequence, and converting tests into testing instructions
DE102007045255A1 (en) 2007-09-21 2009-04-02 Volkswagen Ag Diagnosis system producing method for e.g. car, involves determining symptom influencing repairing measures when static connection between symptom and repairing measures is probability of error, and guiding symptom to repairing measures
EP2175424A2 (en) 2008-10-13 2010-04-14 Rheinmetall Landsysteme GmbH Method for improving the efficiency of vehicles or vehicle systems with and without weapon systems
EP2175423A2 (en) 2008-10-13 2010-04-14 Rheinmetall Landsysteme GmbH Method for supporting training for vehicles or vehicle systems with and without weapon systems
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Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102009000871A1 (en) * 2009-02-16 2010-08-19 Robert Bosch Gmbh Method and device for receiving and transmitting operating data of an internal combustion engine
EP2284631A1 (en) * 2009-07-17 2011-02-16 Siemens Aktiengesellschaft Method for operating a vehicle diagnosis system, control program and vehicle diagnosis system
US8458525B2 (en) * 2010-03-19 2013-06-04 Hamilton Sundstrand Space Systems International, Inc. Bayesian approach to identifying sub-module failure
KR20120049672A (en) * 2010-11-09 2012-05-17 기아자동차주식회사 Scheduled vehicle management system and method of the same
CN102393732B (en) * 2011-10-24 2013-05-22 力帆实业(集团)股份有限公司 Vehicle fault diagnosis method
DE102012007321A1 (en) * 2012-04-12 2013-10-17 Audi Ag Method for operating a diagnostic system and diagnostic system
DE102018111385A1 (en) * 2018-05-14 2019-11-14 Claas Selbstfahrende Erntemaschinen Gmbh Diagnostic device for the maintenance of drive systems intended for driving agricultural machines

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19523483A1 (en) * 1995-06-28 1997-01-02 Daimler Benz Ag Computer-aided fault diagnosis apparatus for a complex technical system
DE10024190A1 (en) * 1999-05-22 2001-01-18 Luk Lamellen & Kupplungsbau diagnostic device
DE19983537T1 (en) * 1998-09-10 2001-08-16 Mecel Ab Aamaal Method and system for diagnosis of complex composite systems in vehicles
DE10323384A1 (en) * 2003-05-23 2004-12-16 Daimlerchrysler Ag diagnostic system
DE10315344A1 (en) * 2003-04-03 2004-12-30 Audi Ag Defective car component detection procedure uses subsystem component identification and failure description modules to select and implement test sequence

Family Cites Families (2)

* 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
DE10307365B4 (en) * 2003-02-21 2005-08-11 Audi Ag Device and method for fault diagnosis in vehicles

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19523483A1 (en) * 1995-06-28 1997-01-02 Daimler Benz Ag Computer-aided fault diagnosis apparatus for a complex technical system
DE19983537T1 (en) * 1998-09-10 2001-08-16 Mecel Ab Aamaal Method and system for diagnosis of complex composite systems in vehicles
DE10024190A1 (en) * 1999-05-22 2001-01-18 Luk Lamellen & Kupplungsbau diagnostic device
DE10315344A1 (en) * 2003-04-03 2004-12-30 Audi Ag Defective car component detection procedure uses subsystem component identification and failure description modules to select and implement test sequence
DE10323384A1 (en) * 2003-05-23 2004-12-16 Daimlerchrysler Ag diagnostic system

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102006018831A1 (en) * 2006-04-22 2007-10-25 Daimlerchrysler Ag Vehicle diagnosis and vehicle acceptance
DE102007010978A1 (en) 2007-03-05 2008-09-11 Volkswagen Ag Electrical system's diagnosis supporting device for use in motor vehicle, has evaluation unit to produce list of incorrect components that are sorted based on dependence value, and output/supply unit to display or provide list
DE102007015140A1 (en) * 2007-03-29 2008-10-02 Volkswagen Ag Diagnosis device for implementing diagnosis of mechatronical system, has evaluation unit including analysis unit and test proposing unit that determines and proposes implementable diagnostic examination
DE102007018732A1 (en) * 2007-04-20 2008-10-23 Volkswagen Ag Diagnosis system for mechatronic overall system i.e. motor vehicle, has selecting unit selecting and combining generic tests from quantity of generic tests to test sequence, and converting tests into testing instructions
DE102007045255A1 (en) 2007-09-21 2009-04-02 Volkswagen Ag Diagnosis system producing method for e.g. car, involves determining symptom influencing repairing measures when static connection between symptom and repairing measures is probability of error, and guiding symptom to repairing measures
EP2175424A2 (en) 2008-10-13 2010-04-14 Rheinmetall Landsysteme GmbH Method for improving the efficiency of vehicles or vehicle systems with and without weapon systems
EP2175423A2 (en) 2008-10-13 2010-04-14 Rheinmetall Landsysteme GmbH Method for supporting training for vehicles or vehicle systems with and without weapon systems
EP2175334A2 (en) 2008-10-13 2010-04-14 Rheinmetall Landsysteme GmbH Method for improving the efficiency of vehicles or vehicle systems with and without weapon systems
DE102008051016A1 (en) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Method for assisting with training on vehicles or vehicle systems with and without weapon systems
DE102008051017A1 (en) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Method for increasing the efficiency of vehicles or vehicle systems with and without weapon systems
DE102008058545A1 (en) 2008-10-13 2010-04-15 Rheinmetall Landsysteme Gmbh Method for increasing the efficiency of vehicles or vehicle systems with and without weapon systems

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