Fuzzy Diagnosis Method In The Fan Fault Diagnosis In Research And Application

Fans are widely used to various sectors of the national production. It plays an important role in the country’s economic development. So development condition monitoring and fault diagnosis for fans to guarantee them in safe and reliable operation is of great theoretical significance and practical significance.This paper applies fuzzy theory to the fan fault diagnosis, according to the fuzzy symptoms of fan fault proceeding fault state recognition and fuzzy reasoning, then make the diagnosis. This method overcomes the difficulty of obtaining accurate information for traditional diagnostic. It adapts to the randomness and fuzziness of fan running state and fault representation, because of the influence of process parameters, temperature change, the impact of surrounding environment, in the continuous operation process.Through researching the fan fault mechanism, decide the vibration intensity and frequency doubling peak as trouble library of fault waiting for inspection. Gets subordinate function in Matlab curve fitting method and fuzzy distribution method. Reference expert experience and a large number of the diagnosis example results, establishing fuzzy matrix preliminary. Complete fuzzy equation with the weighted average type model. Using PDM2000data acquisition analyzer which is made in Dalian university of technology to gather vibration signal of fault fans, then obtain numerical through time domain and frequency domain analysis. After fuzzy fault diagnosis, acquire the result. Contrast with the example diagnosis result, proving this method is feasible.Develop fan fuzzy fault diagnosis system with C++language to auxiliary solve subordinate function and fuzzy equation and realize the fuzzy matrix self-learning function. Amend fuzzy diagnosis matrix constantly and gradually raise the fuzzy diagnosis matrix adaptability and accuracy.Using this model diagnose draft fan and blower in Dongbei special steel mill. Through signal acquisition, data extraction, reference selected, fuzzy diagnosis system diagnosis, and so on, determining the induced draft fan is normal, blower have shaft crack fault. Stop for repair, displaying the correct diagnosis result and proving that this model is practical.