Improved Chicken Swarm Optimization And Its Application In Sound Power Measurement System

The sound power level can objectively and comprehensively reflect the intensity and characteristics of the radiation noise radiated by the sound source.Accurate measurement of sound power level can not only reflect the noise level,but also provide a theoretical basis for formulating reasonable noise reduction measures.When using a sound level meter to measure sound power,the data is displayed on a liquid crystal screen.There are problems of low measurement efficiency and limited display and storage contents.And sound intensity instruments are expensive when using sound intensity instruments to measure sound power.For some large-scale nonmobile devices,sound power measurement needs to be performed in the field.In order to solve the above problems,a sound power measurement system for measuring sound power using comparison method in situ is constructed,the hardware platform of which consists of a microphone,a signal conditioning circuit and a data acquisition card and the software platform of which is built by the LabVIEW development tool.The powerful data processing capability of the computer is utilized to realize the collection,processing,analysis,storage and management of multi-channel noise data.Using the virtual instrument in the LabVIEW tool,an operable soft panel is built on the computer screen instead of the traditional hardware instrument panel so that functions like the diverse display of measurement data and the report output can be achieved.Frequency weighting and spectrum analysis greatly affect the accuracy of sound power measurement.Analyzing the reasons for the large error of frequency weighting by using bilinear transformation method and combining with the application of intelligent algorithm in filter optimization design,an improved chicken swarm optimization is proposed in this thesis.Based on the feasibility of six basic function test proof algorithms,the algorithm is used to optimize the design of the frequency weighting filter.In addition,the multi-sampling rate digital filter bank algorithm is used to analyze the octave.The half-band filter and the octave band-pass filter are designed to implement the simulation and verification.Finally,the overall scheme is designed according to the system requirements.The improved chicken swarm optimization proposed in this thesis can significantly improve the nonlinear error of the frequency weighting filter designed by the bilinear transformation method.The sound power measurement system meets the requirements of the international standard ISO 3747-2010 for the on-site comparison method,and can realize multi-channel signals.The system also has the advantages of friendly human-computer interaction,simple operation,high measurement efficiency and good system stability.