LabVIEW-based Study Of Fan Remote Fault Diagnosis System

The mine fan can make mine ventilation, avoid gas accumulation and ensure Environment safety. The traditional ways usually adopt the regular maintenance to ensure good running. But it is easy to cause excessive or insufficient maintenance and difficult to adapt to the fault of randomness. It increases the downtime and economic losses. The emergence of fault monitoring and diagnosis technology avoids the problem and implements a way according to the state. Fault monitoring and diagnosis technology has realized the remote with the network. Based on those, mine fan remote fault diagnosis system has been studied and developed.Based on the GAF fan and the fan vibration quantity, the fan vibration mechanism and the common faults have been researched, the fan fault symptoms have been analyzed. Sensor, computer, network and database technology were used to study and design a C/S structure remote fault diagnosis system. The system is consisted of local client, remote client and server side. And the hardware system includes Vibration velocity transducers, holzer sensors, a signal acquisition card, and so on. The functions of collection-control, real-time monitoring, analysis and diagnosis, information management, remote communication are implemented. It has realized the fan vibration signal real-time acquisition, the dynamic monitoring operating status, the forecast-value and stop-range setting, alarm prompt. The establishment of the wired communication network makes the long distance real-time monitoring and diagnosis to be realized by the shared variables information technology. Based on those, giving a multiple fault diagnosis method based on AHP and a EMD-FFT combined analysis method in view of the complex signal. The high frequency interference signals are Effectively filtered and the fault signal frequency is extracted by this way. It can do the diagnosis according to the running status of equipment by ahp. It makes the realization of the fuzzy fault diagnosis of fan. And the failure probability is concluded.Lab VIEW was used to designe each module and associate them logically, achieve the multiple diagnostic algorithm and man-machine interface. Access was used to construct the database. Matlab was used to realize the EMD-FFT combined analysis method.