Signal processing method for dynamic weighing based on wavelet transform
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摘要: 针对目前动态汽车衡因货车拖磅称重而导致称重信号异常及称重不准确问题，提出采用小波变换极大值信号重构算法对拖磅称重信号进行处理：首先将拖磅称重信号逐层分解到不同频域和时域，在保持频率不变的条件下，对称重信号逐级求极大值点，得出信号逐级变化趋势；然后将多级称重信号按原离散逼近系数重构成新的称重信号，进而得到车辆称重信息。现场实测表明，采用小波变换极大值信号重构算法处理后的货车拖磅称重数据与正常过磅时称重数据的误差小于1%。Abstract: In order to solve problems of abnormal weighing signal and inaccurate weighing caused by truck forced braking on dynamic truck scale, a signal restructuring algorithm of wavelet transform maxima was used to process weighing signal of truck forced braking. The weighing signal is decomposed layer by layer in various frequency and time domain firstly and gradual trend of weighing signals at different levels is obtained by calculating the maxima point under condition of stable frequency. Then the weighing signals at different levels are restructured into relative true value according to original discrete approximation coefficients, so as to get truck weighing information. The field testing shows that the error is less than 1% between weighing value of truck forced braking processed by the signal restructuring algorithm of wavelet transform maxima and normal weighing value.
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