Research On Fractional-order Based Multi-Channel Rail Vehicle Active Noise Control Algorithm

Noise problems are very common in people’s lives,and long-term exposure to a noise environment may cause people’s mental and physical discomfort.With the rapid development of our country’s rail transit industry,the density of vehicle operations has increased significantly,and noise pollution is increasing,which in turn affects the health of drivers and passengers.The noise generated by rail vehicles is multi-sound sources and multi-frequency bands.Passive control methods such as sound absorption and sound insulation have a good control effect on medium and high-frequency noise,but they cannot effectively control low-frequency noise.Therefore,to solve the problem of low-frequency noise control,active noise control technology has gradually begun to be widely studied and applied.In the current common active noise control systems,the most used algorithm is the control algorithm based on adaptive filtering theory,such as the FxLMS control algorithm.The algorithm is simple,the structure is stable,and it is easy to implement the system;but the algorithm performance is limited,and it is difficult to achieve the ideal control effect under a complex environment.Therefore,it is necessary to further study and optimize the active noise control algorithm to improve the control effect.In this thesis,aiming at the current low-frequency noise reduction problem of rail vehicles,the design and verification of active noise control algorithms are carried out.First of all,designing a new variable step-size function to cope with the performance limitations of the FxLMS algorithm and the non-zero misalignment phenomenon caused by the conventional variable step-size algorithm,and the variable step size is optimized into a time-varying function of the amount of feedback error signal.A balance and performance improvement are achieved between the steady-state error and the steady-state error.Secondly,to improve the accuracy of the random signal description and the estimation of the nonlinear system,fractional calculus is introduced into the adaptive filtering algorithm.From integer order to fractional-order control,gradually optimize the gradient calculation.The proposed fractional-order algorithm is extended to a multi-channel fractional-order algorithm to adapt it to the noise control in large spaces of rail vehicles.According to the size of the target noise reduction space,multiple microphones and multiple speakers are used for global spatial noise signal acquisition and control.The active noise control algorithm of multi-channel rail vehicles based on fractional order was simulated and verified by MATLAB/SIMULINK software and LabVIEW platform,The results show that the algorithm has good convergence performance.Finally,to further verify the active noise control algorithm studied in this thesis,an active noise control experimental system based on the Ethernet control chassis CompactDAQ is built;and secondary channel modeling and identification,single-channel and multi-channel active noise control experiments are carried out.The results show that the algorithm proposed in this thesis has achieved good control effects on various noises of rail vehicles,and has a good engineering application prospect.