An Intelligent Early Online Fault Diagnosis System for Mine Ventilators

Abstract

The invention discloses an intelligent early stage on-line fault diagnosis system of a mine fan, and belongs to the field of equipment early stage fault diagnosis. According to the importance of the mine fan on coal mine safety and the complexity of early stage fault diagnosis, accurate extraction of operating state features of the mine fan is achieved, and tiny change of the operating state of the mine fan can also be recognized. Due to the fact that only fault early warning can be achieved for a fault diagnosis device of an existing mine fan, early faults can not be diagnosed. According to the intelligent early stage on-line fault diagnosis system of the mine fan, the state information extracted by a sensor and a transmitter is preprocessed through a cluster and singular value decomposition method, the state features of the mine fan are extracted, and noise interference is avoided; on the aspect of fault identification and classification, a support vector machine model is utilized, meanwhile, data of each diagnosis are used for continuously enriching and updating a training and learning sample of a support vector machine, so that the model includes more information, and thus the purposes of accuracy, rapidness and intelligence of the early faults of the mine fan are achieved.

Description

technical field [0001] The invention relates to an online fault diagnosis system for an intelligent early mine ventilator, which belongs to the field of equipment fault diagnosis. It diagnoses and identifies the state and state changes of a mine ventilator by analyzing and calculating the state signal of a mine ventilator, especially for the mine ventilator. The fault diagnosis of mine ventilator in harsh environment belongs to the field of early fault diagnosis of mine ventilator. Background technique [0002] Mine ventilator is an important equipment for continuously conveying fresh air, diluting dust, and toxic and harmful gases to the mine. casualties. In order to ensure the safe, reliable and stable operation of mine ventilators, early fault diagnosis of mine ventilators is required. [0003] Due to the harsh working environment and long-term operation of mining fans, they are prone to failures, with many types of failures, weak characteristic signals and strong backg...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to develop an intelligent monitoring system aimed at the deficiency that the current monitoring system of mining fans can only detect the middle and late failures of mining fans, but cannot diagnose the early failures of mining fans. Early online fault diagnosis system for mine ventilators, which is used for early fault diagnosis of mine ventilators

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