A Study On Mine Hoist Fault Diagnosis Technology Based On Information Fusion

Aiming at the importance of mine hoist in mine Production,And hoist the event of an accident caused by the serious consequences of such issues,On the current mine hoist the fault diagnosis problems have been studied.As the mine under poor working conditions and the requirements of explosion-proof,Improve mine hoist system reliability it is very important,And complete failure prediction technology is to improve the reliability of the hoist system an important measure.Now commonly used by a single sensor on the elevator control system to detect,And its spectrum analysis,Failure to achieve the purpose of diagnosis.However,due to mine hoist the main body of work,Such as braking systems, mechanical drive system,lubrication system,In the course of their work,Have problems which may occur,This failure to accurately determine the type of great difficulty.This paper introduced a multi-sensor data fusion technology to upgrade the machine fault diagnosis,The so-called multi-sensor data fusion of information from multiple sensors to multi-level,multifaceted treatment,Export to a new,meaningful information,This new information is no single sensor by the lack of access to the,It was said that the detection of targets.Through multi-sensor data fusion,Time and space to expand coverage,increase confidence,To improve the reliability of detection system.Failure to determine the type of evidence leads in the theoretical reasoning algorithm, Through its use of the probability of failure of some to be binding confidence-building function without accurate probability that,Failure in the process of integration of information,Often in conflict evidence,This paper presents new evidence of the formula to prevent conflict,And through specific examples to prove the validity of the formula.Followed by wavelet packet of mine hoist system of rotating machinery vibration signals were analyzed,Decomposition of the vibration signals to a different band,Can effectively identify the fault information,And the integrated use of neural networks, Evidence Theory,the weighted integration algorithm of mine hoist fault diagnosis on the issue.Focusing on the theory of evidence in the information integration in decision-making role.