Method and system for early warning and optimization of equipment failure based on similarity curve

Abstract

The invention discloses an equipment failure early warning and optimizing method and system based on a similarity curve. The method comprises the steps of: screening normal operation real-time history data from equipment operation real-time history data; generating a data state set based on the normal real-time history data and carrying out extraction according to the distribution of data groups in the data state set to establish a normal operation data model reflecting real operating principles of equipment; comparing the real-time state value group of the equipment which is in online operation with the value groups of each state point in the normal operation data model, and calculating to generate the similarity curve; calculating the data state set of the equipment in normal state on the basis of the normal operation data model, and defining equipment potential failure early warning and optimizing rules corresponding to the change of the similarity curve; and combining the equipment potential failure early warning and optimizing principles, analyzing the change of the similarity curve, distributing the equipment potential failure early warn, and generating the equipment optimization operation guidance.

Description

technical field [0001] The invention belongs to the technical field of equipment state detection and early warning, and relates to a method and system for early warning of equipment failure and equipment optimization, in particular to a method and system for early warning of equipment failure and equipment optimization based on similarity curves. Background technique [0002] With the rapid development of modern industry and science and technology, the modern process industry presents the characteristics of large scale, complex structure, strong coupling between production units, and large investment. At the same time, the possibility of malfunctions in the production process increases. Once this kind of system breaks down, it will not only cause huge loss of personnel and property, but also cause irreparable impact on the ecological environment. In order to improve the safety of industrial production process and control system, improve product quality and reduce production...

AI Technical Summary

Problems solved by technology

[0004] The traditional equipment data monitoring system is based on the equipment data acquisition system, which can only provide real-time data display and analysis of equipment measurement point parameters and equipment failure alarm and diagnosis after the event, and cannot provide effective early failure early detection of equipment accident signs. Pre-warning analysis also cannot provide advance guidance for equipment operation optimization by analyzing the mining results of equipment real-time historical data

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