Development Of Distributed Condition Monitoring System For Belt Conveyor Idler Bearings

Coal plays an important role in national production,and belt conveyor is an indispensable tool in coal production.Its normal operation is related to the safety of coal production.Roller bearing,as a key part of belt conveyor,is also the most used part of belt conveyor.Its environment is mostly high temperature,high humidity and large dust occasions.The power loss of roller bearing in the early stage of failure is mainly in the form of vibration sound,and in the later stage of failure is mainly in the form of friction heat generation,which is easy to cause hidden dangers of underground safety.The health status of idler bearing directly affects the normal operation of belt conveyor.This paper takes idler bearing of belt conveyor in underground coal mine as the research object,and conducts the following studies on how to collect idler bearing signals,how to transmit idler bearing signals and how to analyze idler bearing signals:(1)There are a large number of idler bearings and they are widely distributed in coal mines.If the traditional vibration acceleration sensor is adopted to collect idler bearing signals,there will be a large number of vibration acceleration sensors,resulting in high system cost and a large number of redundant data.The pickup is used as the signal acquisition sensor of roller bearing to effectively solve the above problems.(2)The collected idler bearing signal transmission needs media.In order to avoid laying communication cables again and reduce "information island",127 V lighting power line under the coal mine is selected as signal transmission channel.The collected sound signals of roller bearings contain redundant data.In order to reduce the pressure of mass data transmission,undersampled compressed sensing is adopted as signal preprocessing method,and then Hilbert transformation is performed to effectively amplify the characteristic frequency of roller bearing faults.(3)Different fault characteristic frequencies of idler bearings are classified,the resonance harmonics of compression signals are detected by USING Co Sa MP algorithm,and the permutation entropy operation of recovery signals is carried out to judge the faults and types of idler bearings.(4)An experimental platform for bearing sound signal state monitoring is built,which is composed of sound acquisition device(pickup),analog-to-digital converter(AN9238),digital signal processor(DSP),power carrier module(KQ-330),induction power acquisition module,etc.,to collect and analyze the sound signals of different faulty bearings.The results show that the system can diagnose the faults and types of bearings well,which verifies the feasibility of the system.Figure [39] Table [ 8 ] Reference [ 73 ]...