Research On Active Noise Control Insubway Pipeline

The construction of subway ventilation tunnels is an important part of subway planning and design,and its ventilation power mainly comes from high-power fans.However,the noise of high-power fans is relatively large,making noise control an important issue in subway planning and design.Traditional passive noise control technology greatly reduces the working efficiency of low wind turbines,and wastes resources more seriously.Active noise control technology can significantly reduce noise wind resistance,improve fan efficiency,and save resources.This paper focuses on active control technology to reduce subway pipeline noise,focusing on the identification of secondary sound source paths,the convergence speed of control algorithms,and the balance of steady-state performance.The main work is as follows:(1)By studying the relevant theories of the pipe sound field and acoustic waveguide,the feasibility of active noise control in the noise control of the pipe sound field is demonstrated.The single-channel feedforward structure is taken as an example to filter the classic control algorithm-x minimum mean square error(Filtered-x Least Mean Square(FXLMS)algorithm is derived,and the key factors limiting system performance are pointed out through indicators such as convergence performance,steady-state error,and computational complexity.Combining the design of Chengdu Metro Line 2 to study the noise characteristics and noise propagation characteristics of subway ventilation tunnels,and collect actual noise analysis to verify the correctness of the theoretical derivation,and provide a basis for the design of the test platform and the development of algorithms.(2)Analyze and select components such as pipelines and electro-acoustic devices on the basis of clear control objectives,and complete the design of the test platform based on the feedforward control structure.The primary loudspeaker is used as the noise source,and the reference microphone collects the primary noise as the reference signal.The input and output noise signals are respectively processed by a power amplifier,a preamplifier,a reconstruction filter,and an anti-aliasing filter.The platform can meet the requirements of control principles and algorithm prototype verification.(3)The noise active control algorithm is discussed,and an improved method is designed,which mainly uses the LMS algorithm improved by proportional normalization to identify the secondary acoustic channel.From the test results,it can be seen that the use of the PNLMS algorithm can speed up the adaptive algorithm Convergence speed and steady-state misadjustment performance can also be kept constant,which improves the accuracy and timeliness of secondary acoustic channel identification,and ultimately results in a greater improvement in noise control effects.(4)Integrate the previous theoretical analysis,test platform design,algorithm improvement,etc.,verify the function and algorithm effectiveness through the simulation experiment of the test platform,and summarize analysis and prospects based on the final results.