JPS63101731A - Fault diagnosing apparatus for vehicle - Google Patents

Abstract

PURPOSE:To pursuit the true cause quickly with the examination on troubles sequentially starting from the least difficulty in inspection, by memorizing rules (Pi, Ti, Zi and Yi) as the combination of candidate-causes Yi with a high possibility of true cause among causes of troubles X and difficulty Ti in inspection when a specified result Pi is obtained for a specified inspection Zi. CONSTITUTION:When a symptom A is set, trouble information cause corresponding to X=A is retrieved from among trouble information cause (X,[Yi]) stored in a knowledge data section 9 to find a cause list [B1, B2 and B3]. Then, hearing information rules 1, 2 and 3 are retrieved for the cause list from the knowledge data section 9 and with difficulty in inspection taken into account, the cause list is rearranged sequentially from the least difficulty Ti in inspection to obtain a cause list as [B1, B3 and B2]. Then, items and the difficulty Ti in inspection arranged sequentially from the least degree thereof are displayed and a diagnosing person is ordered to select a specific item.

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention relates to a vehicle failure diagnosis device as a so-called expert system.

[Description of Prior Art] Examples of expert systems include mycin (
There is something called MYCi N).

MYCi N has a rule: [If X, do Y]
This is a typical example of a so-called production system that has an if~then~ rule of the form. This is aimed at diagnosing blood infections, so specifically if
The infection is primary bloodemia, ■ the culture medium is non-productive,
Furthermore, if the gastrointestinal tract is suspected as the point of entry of bacteria, there is a high probability that it is Bacteroides (with a probability of 0.7)" - Nikkei Computer 83.6.27> By applying these rules and repeating interviews with the user, a predetermined diagnosis is made.

By the way, when considering the application of such a production system to vehicle failure diagnosis, there are many cause candidates Y (Y+, Y2) for symptom X.

Y3...Yi...) exists, each cause candidate Y
It is conceivable to pursue the true cause by conducting interviews regarding i one by one.

However, in the case of vehicle failure diagnosis devices considered in this way, inspections are often required during vehicle interviews, so it takes a lot of time and effort to find the true cause. There was a problem.

[Purpose of the Invention] This invention improves the above-mentioned problems and provides a vehicle fault diagnosis 1 that can more easily and quickly find the true cause.
! The purpose is to provide a Fi device.

[Summary of the Invention 1 To achieve the above object, the present invention, as shown in FIG.
[Yi] ), and inquiry information in a form specifying that if a predetermined inspection result Pi is obtained for a predetermined inspection Z1, there is a high possibility that the cause candidate Yi is the true cause. rule (Pi.

(Ti, Zi, Yi); a symptom input means 3 for inputting symptoms; and an inference means 4 for searching the failure information to find the cause of the input symptoms.
An interview means 5 that searches the interview information and prompts the cause candidates in the inference process to be inspected in descending order of difficulty of inspection, an interview content informing means 6 that notifies the contents of the interview, and an inspection result that inputs the inspection results. It is configured to include an input means 7 and an inference result notifying means 8 for notifying an inference result, so that interviews that are easy to inspect are given priority over other questions.

[Example] Hereinafter, the present invention will be described in detail using the accompanying drawings.

FIG. 2 is a block diagram showing the hardware configuration of a vehicle failure diagnosis device according to an embodiment of the present invention.

The vehicle fault diagnosis device includes a knowledge data section 9, an inference section 10 composed of a computer, a keyboard 11 and a CR.
The inference unit 10 is configured with an interface 13 equipped with Tl2, and the user can communicate with the inference unit 10 via the interface 13.

In relation to FIG. 1, the knowledge data section 9 forms the failure information storage means 1 and the inquiry information storage means 2,
forms the reasoning means 4 and the questioning means 5, and the keyboard 11
is checked with symptom input means 3.

The CRTl 2 forms a result input means 7, and the CRTl 2 forms an interview content detection means 6 and an inference result notification means 8.

The knowledge data unit 9 contains failure information cause (X.

[Yi]).

cause 1 (A, [B+, B2,
B3]) cause 2 (B+, [C+
, C2, 03] ) cause 3 (82, [C3
, C4, C5] ) cause 4 (B3, [
Ca, Cy] ) cause 5 (C4, [D
+, D2, D3]) Failure information cause
The specific details regarding 1 are as follows.

Cause 1 (Distribution failure, [lower cap withstand voltage, poor rotor mounting angle, center carbon wear]) A failure tree formed from these failure information is shown in FIG. 3.

In addition, the knowledge data unit 9 creates an inquiry information rule (Pi,
Ti, Zi, Yi).

rule 1 (P+, T+, Z+, B+) rule
2 (P2, T2, Z2, B2)ru
le 3 (P3, T3, Z3, B3
)rulel, 2.3 is as follows.

ruleel (Leak marks on the cap, 0.15 hours.

Visually inspect the cap for leak marks.

Decrease in cap withstand voltage) Rule 2 (0-Use an interference cloth for the evening and cap, and check for interference between the rotor and cap for 0.25 hours.

(Improper rotor installation angle) rule 3 (center carbon wear, 0.2 hours.

Inspection of Center Carbon Wear, Center Carbon Wear) A diagnosis example of the vehicle failure diagnosis device having the above configuration is shown in FIG.

In step 401, it is assumed that "distribution computer is good" (A) is set as symptom X.

In step 402, failure information cause 1 is retrieved from the knowledge data section 9 for symptom A, and the cause list [B
+ , B2 , B3 ] are found.

In step 403, a cause list [B+, B2] is created.

Question information rule 1 from knowledge data department 9 for B11
．． Search for 2.3, and search for the medical interview information rulel, 2.3
Taking into account the difficulty of inspection, the cause list [B+, B2
.
+, 83.82].

In step 404, the rearranged cause list [8+
, 83.82 ], as shown in FIG.
The items are displayed in descending order and the diagnostician is instructed to select a predetermined item.

Here, the diagnostician can select desired items. However, the item display shown in FIG.
03, the inspection time is sorted in descending order. Therefore, in principle, the diagnostician can select the item that requires the least amount of inspection time by selecting the display item in the top row.

In step 404, it is assumed that item B1 shown in FIG. 5 has been selected.

In step 405, the inference unit searches for medical interview information rulei according to the selection of item B1, and in step 406, the inference unit searches for the sixth
As shown in the figure, inspection method z is applied to selected item B1.
1 is displayed.

Step 407 is to judge the diagnostician's inspection result, and if "YES", it is determined that the item B1 selected in step 404 is highly likely to be the true cause, and step 409
However, if it is rNOJ, item B1 is symptom A.
In step 408, the cause list [B
+ , 83.82] and remove item B1 from step 4.
Return to 04.

In step 409, item B1 is stored.

In step 410, item B1 is set as a new symptom X and the cause Y of this symptom X is searched for.

In step 411, it is determined whether the lowest layer of the fault tree shown in FIG. 3 has been reached, and if it is the lowest layer, step 4
The process moves to step 12 to display the diagnosis result, but if it is not the lowest layer, the process returns to step 401 in order to diagnose the lower layer. Note that in the searches from step 401 onward, A is converted into B, B into C, and so on.

According to the process shown in FIG. 4, for example, in step 404, item B+r cap withstand voltage drop is selected, and in step 1406, it is checked that there is a leak trace on the cap.
The true cause Ci (eg C+) is inferred in step 412 via steps 411.401.

Candidate cause Ci for symptom B1 (C+, C2.

C3) is also displayed in order of inspection time as shown in FIG.

As described above, according to the vehicle failure diagnosis apparatus shown in this example, as shown in FIG. It can be significantly shortened.

In the embodiments shown above, the inspection difficulty level Ti is set based on the time required for inspection work, but the difficulty level may also be defined based on the difficulty of the inspection work, or may be determined based on the time and difficulty of the work. It may be a newly set value.

Note that the present invention is not limited to the above-mentioned embodiments, but can be implemented in other embodiments by making appropriate design changes.

[Effects of the Invention] As described above, according to the vehicle fault diagnosis device according to the present invention, the diagnostician can take questions starting from the least difficult of inspections, and therefore can more easily and quickly determine the truth. The cause of this can be investigated.

[Brief explanation of the drawing]

Fig. 1 is a diagram showing an overview of the present invention, Fig. 2 and the following show embodiments of the invention, Fig. 2 is a block diagram showing the hardware configuration of a vehicle fault diagnosis device, and Fig. 3 is an explanation of a fault tree. 4 are flowcharts of the diagnostic processing, and FIGS. 5 and 6 are explanatory diagrams of display examples. 1...Failure information storage means 2...Interview information storage means 3...Symptom input means 4...Inference means 5...Interview means 6...Interview content notification means 7...Inspection result input Means 8...Inference result notification means Cause...Failure information rule...Interview information Ti...Difficulty level of inspection (time) Agent Patent attorney Yasuo Miyoshi Figure 1 Country 3121

Claims (1)

[Claims] A failure information storage means for storing failure information in the form of a list of cause candidates for failure symptoms, and a provision that specifies that if a predetermined inspection result is obtained for a predetermined inspection, there is a high possibility that the cause candidate is the true cause. an interview information storage means for storing the interview information in the form of a test and the difficulty level of the inspection; a symptom input means for inputting symptoms; an inference means for searching the failure information and pursuing the cause of the input symptoms; An inquiry means for searching the inquiry information and prompting the cause candidates in the inference process to be inspected in descending order of inspection difficulty; an inquiry content informing means for notifying the contents of the inquiry; and an inspection result inputting means for inputting the inspection results. , an inference result notification means for notifying an inference result;
A vehicle failure diagnosis device comprising: