Traditional singular value detection algorithm based on wavelet transform has obvious test result on larger mutation signal,but not obvious on the signal which has subtle changes or is affected by noise,leading to considerable error. To solve this problem,make improvements over the original algorithm, the method do the computing processing including the domain transformation and index transformation to the high frequency coefficients which is produced in the wavelet decomposition process, screening a new set of high-frequency coefficients,then using the wavelet reconstruction algorithm to recover the original signal. The matlab simulation results show that the improved method highlights the mutation effect of the singular value,and detects singular points more accurately. Combined with negative pressure wave method,achieve the heating network leak location. The combination still needs a large number of experiments to verify.%传统基于小波变换的奇异值检测对大突变量信号检测效果明显,而对细微变化的信号或受噪声影响的信号奇异值检测不明显.为解决此问题在原基础上做出改进,对小波分解产生的高频系数进行域变换的数学处理方法,做指数变换.筛选一组新的高频系数,再运用小波重构恢复出原信号.通过运用matlab实现的仿真结果表明改进方法突出了奇异值的突变效果,也更准确地检测奇异点.通过与负压波法的结合实现对热网泄漏点的定位,该结合仍需大量实验来验证.
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