Research And Implementation On Fault Diagnosis For Mine Automatic Drainage System

Today, mines are developed towards digital and intelligent direction. With the developing of Mine Wide Interated Automation System, mine drainage mode is shifting from from manual to automatic. The change has achieved some effects on reducing labor intensity ande improving working effect. However, it also results more starting failures, more fault shut-down and system hard to maintain, since the increasing of equipment quantity, the more complex device structure, the stronger dependence on device, the more-normalized control flow.Aimed at above issues, the thesis firstly described technique situation of drainage monitoring and fault diagnosis, elucidated basic composition, operation process, monitoring requirements and methods of mine drainage system, and typical architecture of mine automatic drainage system. Common troubles and its symptom of mine automatic drainage system were generalized in detail. Based on analyzing characteristics of some main fault diagnosis methods and mine automatic drainage system, a new approach to diagnosing faults were researched which combining fault tree analysis method, system-level fault diagnosis with fuzzy fault diagnosis.Then, the paper introduced the basic concept, diagnosis principle, diagnostic criteria and implement approach of selected fault diagnosis methods. Taking typical alarm "Negative Pressure at Startup" for example, the design idea of fault diagnosis approach seclected and realizing process of fault diagnosis module were detailed as follows:1) Establishing alarm system according to monitoring requirements, and building fault tree taking alert event as top event.2) Real time alarm triggering fault tree, and diagnosing fault with sensor information.3) By using system-level fault diagnosis test, diagnosing the faults that cannot be traced back to bottom events according to fault tree quantitative analysis, for narrowing the fault aera down.4) If the fault causes are still not bottom events, locating them by fuzzy pattern recognition. 5) Adding components breakdown times, to improve veracity of fault tree quantitative analysis.Finally, through testing and analyzing the results, conclusion shows that the fault diagnosis method being researched can accurately diagnose faults which can trigger alarm, but can not realize fault prediction, needs further researchand and development.