Onsite information preprocessing method of remote cooperative diagnosis

Abstract

An onsite information preprocessing method of remote cooperative diagnosis includes an information collection step, a health state prediction step, a deep information processing step and a remote information transmission step. The information collection step collects working state information, control information, fault diagnosis information, working record information and working environment information. The health state prediction step predicates health state of equipment in one further period according to collection information and correspondingly conducting adjustment on an important monitoring point and monitoring frequency of the state monitoring in advance. The deep information processing step excavates fault sign information of relative time periods of the important monitoring point and conducting effective information extraction on common health state information according to certain standard. The remote information transmission step uploads preprocessing results. The onsite information preprocessing method compresses and extracts onsite original data of the equipment, reasonably expresses health state information of the equipment and converts the health state information into the knowledge expression mode required by an expert system or other decision making systems according to actual health state of the equipment.

Description

technical field [0001] The invention relates to an on-site information intelligent processing technology suitable for a front end of remote collaborative diagnosis of complex equipment, in particular to a field information preprocessing method for remote collaborative diagnosis. Background technique [0002] At present, with the development of micro-nano technology, extreme and precision manufacturing, etc., the equipment structure is becoming more and more complex, the scale is getting larger and larger, and the degree of multi-disciplinary integration, multi-field coupling, mechatronics and multi-manufacturer collaborative manufacturing is increasing. High; correspondingly, equipment fault diagnosis is more complicated. For these complex equipment, there is often a complex nonlinear and unstructured relationship between faults and features. Usually, there are many ways of fault propagation and concurrent propagation, chain reaction and mutual influence will occur. Theref...

AI Technical Summary

Problems solved by technology

[0008] In the field: (1) To realize the off-site transmission and sharing of equipment health status information among heterogeneous networks such as fieldbus networks and local area networks, information integration needs to be carried out through gateway software, but there is no unified standard for information integration, only general There are nearly 10 types of fieldbus, which makes the design of gateway software more difficult

(2) The amount of real-time sampling information of equipment is usually very large, and it is difficult to directly transmit through the network without any processing or the transmission efficiency is low

(3) The on-site self-diagnosis system of some equipment can only provide rough fault alarm prompt information, lack of comprehensive fault mechanism research, and most of them are not equipped with health status prediction function, or only simple prediction

These make the RCFD center sometimes have no time to take into account the timely and special processing of information on the health status of a certain equipment, thus delaying the diagnosis process

(2) Due to the reality of current network transmission, network congestion and information loss are very serious at certain moments, resulting in poor real-time performance of the information received by the RCFD center

[0010] It can be seen that remote diagnosis is difficult to completely replace on-site diagnosis, but should be an integration of the two

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