Acoustic emission (AE) technique has been merged to a promising method for structural health monitoring in non-destructive technique. So an analysis of the AE signal is becoming a very important research component. In this paper, an algorithm is developed for detection of the crack signal among different noise signals since the AE signal is also generated by several means like any impact or rubbing action on the structure which may give erroneous results. An AE monitoring system is developed with three experimental setups to generate three types of AE signals from three dissimilar sources. Thus, an algorithm is developed to identify the crack signal by comparing the parameters of different signals acquired from different sources using some signal processing techniques such as parameter based analysis, waveform based analysis e.g. fast Fourier transform, continuous wavelet transform, cross-correlation coefficient, magnitude coherence coefficient, and energy distribution. After identification of the crack signal, the distance of the crack source has been calculated by analysing the signal in time–frequency domain also an algorithm has been designed to calculate the velocity of the acoustic wave more accurately and consequently the distance of the crack.

声发射（AE）技术已被合并为一种无损技术中用于结构健康监测的有前途的方法。因此，对AE信号的分析正成为非常重要的研究组成部分。在本文中，开发了一种算法来检测不同噪声信号中的裂纹信号，因为AE信号还通过多种方法生成，例如对结构的任何撞击或摩擦作用，都可能产生错误的结果。开发了具有三个实验设置的AE监视系统，以从三个不同的源生成三种类型的AE信号。因此，开发了一种算法，该算法通过使用一些信号处理技术（例如基于参数的分析，基于波形的分析）比较从不同来源获取的不同信号的参数来识别裂纹信号。快速傅立叶变换，连续小波变换，互相关系数，幅度相干系数和能量分布。识别出裂纹信号后，通过分析时频域信号来计算裂纹源的距离，并设计了一种算法，可以更准确地计算声波的速度，从而计算出裂纹的距离。