Research On Dynamics And Optimal Sensor Placement Of Shearer Ranging Arm

Coal is the main energy and has an important strategic position in China’seconomic and social development. Shearer which was safety and efficient productionmajor mechanical equipment of a modern mine has drawn more and more attention.Ranging arm is the most easy-to-failure component, and the power consumption ofcutting unit accounts the shearer power for80%-90%. So the ability to accuratelydiagnose ranging arm failure will directly affect shearer productivity, drive efficiency,energy consumption and service life. Testing and analyzing equipment vibrationsignal is a major means of condition monitoring and fault diagnosis, therefore,carrying out research on impact of system vibration and fault gear on system dynamiccharacteristics is helpful for condition monitoring and fault diagnosis. In order tomake a more accurate condition monitoring and fault diagnosis for shearer, selectingthe appropriate sensors monitoring points and the number of sensors are an essentialprocedure, moreover, analyzing the dynamics of the ranging arm is the theoreticalbasis of finding the appropriate sensor monitoring points and the number of sensors.Optimized sensors arrangement could provide the most valuable information at thelowest cost, which is the basis of improving system performance of conditionmonitoring and fault diagnosis.For gear fault can be demonstrated by the gear meshing kinetic parameters,particularly, gear meshing stiffness and strength are sensitive to gear fault, analysis ofgear meshing kinetic parameters is the basis of gear accurate fault diagnosis.Established a mathematic model of solving gear time-varying mesh stiffness based onmaterials mechanics and energy principles, afterwards, proposed a mathematic modelof solving gear time-varying meshing stiffness with crack propagating along toothwidth and crack depth. Time-varying mesh stiffness during gear operating processwas solved by numerical simulation. Through simulating gear mesh stiffness of a gearwith different crack length and depth, the conclusion that gear mesh stiffness reducedwith the crack extended.Because the high-speed zone in ranging arm is the high incidence of gear failure,a9-degree-of-freedom dynamic model was proposed for the high-speed zone inranging arm, with the model the dynamics of the high-speed zone, the influence ofimpact load on the high-speed zone gears, and the influence of gear with differentcrack width and length were analyzed, the results shown that the gear failure could be found by time-domain signal analysis. The influence of system vibrationcharacteristics by typical failure patterns in planetary gears was investigated, failurecaused periodic variation signal and impact components were significant. Comparedwith the frequency domain signal of normal gears, the frequency domain signal offault gears had the same frequency components, but some sidebands occurred aroundthe mesh frequencies, the amplitude of different failure mode was different. Excitationfrequency transmitted to the gear-box was main the gear mesh frequency and itsmulti-frequency. The simulated signal was free of noise and disturbance derived fromthe theoretical model, and theoretical analysis provided a theoretical basis for a deeperunderstanding and grasping the impact of typical damage to the vibrationcharacteristics of gear systems, which laying the foundation for further study offeature extraction methods, damage detection, degenerative condition assessment andpredict the remaining life.In order to optimize the vibration sensors arrangement on ranging arm, on thebasis of dynamics analysis of ranging arm and plate power flow theory, thedistribution of power flow on the ranging arm gear-box was simulated using the finiteelement method. The proper zones for vibration sensors were obtained based on thepower flow analysis, the results showed that the best zones for vibration sensors werethe areas around the bearing box. Based on the results of the power flow analysis,optimal sensor placement criterion were explained, the modal assurance criterion wasconducive parameter identification, compared with genetic algorithms, particle swarmoptimization algorithm was simple and easy to implement. The fitness function ofoptimal sensors arrangement on ranging arm was established the modal assurancecriterion, optimized calculation for optimal sensor placement on ranging arm wasconducted using particle swarm optimization algorithm, and then the optimal sensorplacement strategy was acquired.