Mining Machinery Fault Diagnosis Based On Harmonic Wavelet Analysis

Large stationary coal mine machinery, such as the hoist and the main fan is thevital importance of coal mine production safety equipment, its operational status of adirect impact on the economic benefits of coal production.Such equipment is not onlymaintenance of long duration, high cost and more serious, is prone to suddenaccidents or serious accident resulting in huge economic losses of enterprises and anegative social impact.Therefore, as soon as possible try to effectively detect thefailure may lead to catastrophic accidents of great significance to improve thereliability and safety of coal mining machinery, and one of the key technologies forthe early detection of fault signal feature extraction.The mine hoist and main fan complex structure and poor working environmentoutside interference and to characterize the failure characteristics of the signal is morecomplex.Due to the impact and the modulation caused by the dynamic signal is oftennon-stationary, this development can effectively deal with non-stationarycharacteristic signal and used in mine hoists and fan fault feature extraction hasimportant practical value in use.The hoist gearbox and fan drive system, using the harmonic wavelet analysismethod and extraction method conducted in-depth study on the characteristics ofoutstanding characterization equipment failure. The main contents include:(1)Fourier transform, wavelet analysis and harmonic wavelet analysis theory wasintroduced, and compare the strengths and limitations of these methods in the coalmine machinery fault feature extraction.(2)Enhance the common gear box and the fan drive system vibration and failuremechanism were studied.(3)Harmonic wavelet theory, take advantage of the harmonic wavelet transformfor fault diagnosis of the main mine fan and hoist gear box, and success from thevibration signal to extract the fault characteristic signal for the coal mine large fixedprecision machinery fault diagnosis to provide a reliable basis.