Failure analysis and diagnosis method and system

Abstract

The invention discloses a method for analyzing and diagnosing failure. The method comprises the following steps: acquiring failure diagnosing information and data information of the adopted analysis method, wherein the failure diagnosing information comprises a diagnosing object and a failure reason; providing the failure diagnosing information for a maintenance terminal, and receiving feedback information determining whether the failure diagnosing information is correct from the maintenance terminal; and according to the feedback information, counting and storing the data information comprising the analysis method and the failure diagnosing information. In addition, the invention also discloses a system for analyzing and diagnosing the failure. The technical proposal can improve the efficiency of analyzing and diagnosing the failure.

Description

technical field [0001] The invention relates to the field of mechanical maintenance, in particular to a fault analysis and diagnosis method and system. Background technique [0002] In order to optimize mechanical performance and reduce downtime due to failures, it is necessary to continuously maintain mechanical equipment and analyze and count various data. In order to have an accurate and comprehensive understanding of the current mechanical equipment, the mechanical equipment analysis process usually includes: understanding the data and related prior knowledge of various aspects of the mechanical equipment; selecting a set of relevant data of the concerned aspects from a variety of data sources; using appropriate The selected data is analyzed by the method; according to the data analysis results, the information of various aspects of the mechanical equipment is obtained. [0003] In general, in order to obtain relevant information on various aspects of physical propertie...

AI Technical Summary

Problems solved by technology

Most of the behaviors in the analysis and diagnosis process can only rely on personal prior knowledge and experience accumulation, even if some diagnosis systems provide some automatic diagnosis function modules based on pre-set databases or models The automatic diagnosis function module set based on the specific fault problem and expression mode is often not enough when the signal mode is manifested, so that it cannot be diagnosed when the mechanical equipment fails

In addition, some diagnostic systems provide a platform for users to conduct video conferences and real-time discussions. Multiple users can diagnose mechanical faults and exchange their opinions and diagnostic results. The intermediate results and related information cannot be stored and used as a reference for future analysis and diagnosis

[0005] It can be seen that in the prior art, there is no effective method and system to realize fault analysis and diagnosis, such as tracking the current state of data analysis and mechanical fault diagnosis, saving relevant intermediate results, summarizing diagnosis conclusions and collecting maintenance personnel's opinions on diagnosis conclusions. Feedback, etc.; there is no real multi-person participation user-customizable platform for fault analysis and diagnosis of the same mechanical equipment to collect and save accumulated experience and provide support for future diagnosis, thus making fault analysis and low efficiency in diagnosing

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