Failure diagnosis method, failure diagnosis apparatus, conveyance device, image forming apparatus, program, and storage medium

• US 20050262394A1
• Filed: 02/23/2005
• Published: 11/24/2005
• Est. Priority Date: 04/21/2004
• Status: Active Grant

• Current Assignee: Fujifilm Business Innovation Corp. (Fujifilm Holdings Corporation)
• Original Assignee: Fuji Xerox Company Limited (Xerox Holdings Corp.)
• Inventors: Satonaga, Tetsuichi, Yasukawa, Kaoru, Nakagawa, Eigo, Yamada, Norikazu, Uwatoko, Kouki, Adachi, Kouji
• Granted Patent: US 8,132,049 B2
• Time in Patent Office: Days
• US Class Current: 714/23
• CPC Class Codes: G03G 15/5079 for maintenance
• CPC Class Codes: G03G 15/55 Self-diagnostics; Malfunction or lifetime display
• CPC Class Codes: G03G 15/553 Monitoring or warning means for exhaustion or lifetime end of consumables, e.g. indication of insufficient copy sheet quantity for a job
• CPC Class Codes: G06F 11/0733 in a data processing system embedded in an image processing device, e.g. printer, facsimile, scanner
• CPC Class Codes: G06F 11/0748 in a remote unit communicating with a single-box computer node experiencing an error/fault remote testing G06F11/2294
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36

Abstract

A failure diagnosis method diagnoses a failure occurring in a diagnosis target apparatus including a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member. The method includes automatically acquiring by a sensor an operation state signal indicating an operation state during the drive mechanism operating for a predetermined period; and analyzing the automatically acquired operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the diagnosis target apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism.

Claims

1. A failure diagnosis method for diagnosing a failure occurring in a diagnosis target apparatus including a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member, the method comprising:

automatically acquiring by a sensor an operation state signal indicating an operation state during the drive mechanism operating for a predetermined period; and

analyzing the automatically acquired operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the diagnosis target apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism.

2. The failure diagnosis method according to claim 1, wherein the failure probability model is a Bayesian network model.

3. The failure diagnosis method according to claim 1, further comprising:

dividing the drive mechanism into a plurality of blocks, wherein;

the failure diagnosis is executed with respect to each of the blocks.

4. The failure diagnosis method according to claim 3, wherein:

each of the blocks has a single motor as the drive member; and

the transmission member of each block transmits the drive force of the single motor within each of the blocks.

5. The failure diagnosis method according to claim 1, wherein the failure diagnosis is executed based on (a) a reference characteristic amount, which is obtained when the drive mechanism operates normally, and (b) an actual operation characteristic amount, which is obtained from the automatically acquired operation state signal.

6. A failure diagnosis apparatus for diagnosing a failure occurring in a diagnosis target apparatus including a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member, the failure diagnosis apparatus comprising:

a failure diagnosis section that analyzes an operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the diagnosis target apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism, wherein;

the operation state signal is automatically acquired in the diagnosis target apparatus; and

the operation state signal indicates an operation state during the drive mechanism operating for a predetermined period.

7. The failure diagnosis apparatus according to claim 6, wherein the failure probability model is a Bayesian network model.

8. The failure diagnosis apparatus according to claim 6, wherein:

the failure diagnosis section divides the drive mechanism into a plurality of blocks; and

the failure diagnosis section executes the failure diagnosis with respect to each of the blocks.

9. The failure diagnosis apparatus according to claim 8, wherein:

each of the blocks has a single motor as the drive member; and

the transmission member of each block transmits the drive force of the single motor within each of the blocks.

10. The failure diagnosis apparatus according to claim 6, wherein the failure diagnosis section executes the failure diagnosis based on (a) a reference characteristic amount, which is obtained when the drive mechanism operates normally, and (b) an actual operation characteristic amount, which is obtained from the acquired operation state signal.

11. The failure diagnosis apparatus according to claim 6, wherein the failure diagnosis section is connected to the diagnosis target apparatus via a communication line.

12. The failure diagnosis apparatus according to claim 6, wherein the failure diagnosis section adjusts the analyzing on a basis of degree of deviation of the operation state signal from a normal range, which is set for the operation state signal in advance.

13. The failure diagnosis apparatus according to claim 6, wherein:

the failure diagnosis section analyzes environment information based on the failure probability model to execute the failure diagnosis; and

the environment information is automatically acquired in the diagnosis target apparatus and relates to an operation of the drive mechanism.

14. The failure diagnosis apparatus according to claim 6, wherein:

the failure diagnosis section analyzes history information of the operation state signal based on the failure probability model to execute the failure diagnosis; and

the history information is stored in the diagnosis target apparatus.

15. The failure diagnosis apparatus according to claim 6, wherein:

the drive mechanism is used for a conveyance system that conveys a member to be conveyed; and

the failure diagnosis section analyzes based on the failure probability model the operation state signal indicating at least one of (x) a conveyance timing of the member to be conveyed and (y) a conveyance time of the member to be conveyed, to execute the failure diagnosis.

16. The failure diagnosis apparatus according to claim 14, wherein:

the failure diagnosis section connects a plurality of nodes in the failure probability model serially by an arc in a conveyance direction of the member to be conveyed;

the nodes indicate the operation state signal indicating the at least one of (x) the conveyance timing of the member to be conveyed and (y) the conveyance time of the member to be conveyed.

17. The failure diagnosis apparatus according to claim 6, wherein:

the failure diagnosis section comprises a failure prediction section that analyzes fluctuation history of the operation state signal based on the failure probability model to predict failure occurring in future.

18. A conveyance apparatus for conveying a member to be conveyed, comprising:

a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member;

an operation state signal acquisition section that acquires by a sensor an operation state signal indicating an operation state during the drive mechanism operating for a predetermined period; and

a failure diagnosis section that analyzes the acquired operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the conveyance apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism.

19. The conveyance apparatus according to claim 18, wherein the failure probability model is a Bayesian network model.

20. The conveyance apparatus according to claim 18, wherein:

the failure diagnosis section divides the drive mechanism into a plurality of blocks;

the failure diagnosis section executes the failure diagnosis with respect to each of the blocks.

21. The conveyance apparatus according to claim 20, wherein:

each of the blocks has a single motor as the drive member; and

the transmission member of each block transmits the drive force of the single motor within each of the blocks.

22. The conveyance apparatus according to claim 18, wherein the failure diagnosis section executes the failure diagnosis based on (a) a reference characteristic amount, which is obtained when the drive mechanism operates normally, and (b) an actual operation characteristic amount, which is obtained from the acquired operation state signal.

23. An image forming apparatus comprising:

a conveyance section that conveys a member to be conveyed and comprises a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member;

an image formation section that forms an image on the member to be conveyed that is conveyed by the conveyance section to a predetermined position;

an operation state signal acquisition section that acquires by a sensor an operation state signal indicating an operation state during the drive mechanism operating for a predetermined period; and

a failure diagnosis section that analyzes an operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the image forming apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism, wherein;

the operation state signal indicates at least one of (x) a conveyance timing of the member to be conveyed and (y) a conveyance time of the member to be conveyed.

24. The image forming apparatus according to claim 23, wherein the failure probability model is a Bayesian network model.

25. The image forming apparatus according to claim 23, wherein:

the failure diagnosis section divides the drive mechanism into a plurality of blocks; and

the failure diagnosis section executes the failure diagnosis with respect to each of the blocks.

26. The image forming apparatus according to claim 25, wherein:

each of the blocks has a single motor as the drive member; and

the transmission member of each block transmits the drive force of the single motor within each of the blocks.

27. The image forming apparatus according to claim 23, wherein the failure diagnosis section executes the failure diagnosis based on (a) a reference characteristic amount, which is obtained when the drive mechanism operates normally, and (b) an actual operation characteristic amount, which is obtained from the acquired operation state signal.

28. The image forming apparatus according to claim 23, wherein the failure diagnosis section adjusts the analyzing on a basis of degree of deviation of the operation state signal from a normal range, which is set for the operation state signal in advance.

29. The image forming apparatus according to claim 23, wherein the operation state signal acquisition section comprises a drive section operation current detection section that detects a signal indicating operation current flowing in the drive member as the operation state signal.

30. The image forming apparatus according to claim 23, wherein the operation state signal acquisition section comprises a drive mechanism vibration detection section that detects a signal indicating vibration of the drive mechanism as the operation state signal.

31. The image forming apparatus according to claim 23, further comprising:

an environment information acquisition section that acquires by the sensor environment information relating to an operation of the drive mechanism, wherein;

the failure diagnosis section analyzes the environment information based on the failure probability model to execute the failure diagnosis.

32. The image forming apparatus according to claim 31, wherein the environment information acquisition section acquires at least one of (s) peripheral temperature of the drive mechanism and (t) peripheral humidity of the drive mechanism as the environment information.

33. The image forming apparatus according to claim 23, further comprising:

a history storage section that stores history information of the operation state signal in the conveyance section, wherein;

the failure diagnosis section analyzes the history information stored in the history storage section based on the failure probability model to execute the failure diagnosis.

34. The image forming apparatus according to claim 33, wherein the history storage section stores as the history information number of conveyances of the member to be conveyed after one of new installation of the image forming apparatus, replacement of consumables, and replacement of a part.

35. A storage medium readable by a computer, the storage medium storing a program of instructions executed by the computer to perform a function for diagnosing a failure occurring in a diagnosis target apparatus including a drive mechanism having a drive member that receives power supply to operate and a power transmission member that transmits drive force of the drive member to another member, the function comprising:

receiving from the diagnosis target apparatus an operation state signal indicating an operation state during the drive mechanism operating for a predetermined period; and

analyzing the received operation state signal based on a failure probability model, which is obtained by modeling a cause of failure occurring in the diagnosis target apparatus with using probabilities, to execute failure diagnosis with respect to each of constituent members of the drive mechanism.

36. The storage medium according to claim 35, wherein the failure probability model is a Bayesian network model.

37. The storage medium according to claim 35, the function further comprising:

dividing the drive mechanism into a plurality of blocks, wherein;

the failure diagnosis is executed with respect to each of the blocks.

38. The storage medium according to claim 37, wherein:

each of the blocks has a single motor as the drive member; and

the transmission member of each block transmits the drive force of the single motor within each of the blocks.

39. The storage medium according to claim 35, wherein the failure diagnosis is executed based on (a) a reference characteristic amount, which is obtained when the drive mechanism operates normally, and (b) an actual operation characteristic amount, which is obtained from the automatically acquired operation state signal.