基于加速度传感器的电缆防盗检测算法研究

电力电缆因具有较高的经济价值,常遭到不法分子的违法盗窃,文章设计了一套基于三轴加速度传感器的电缆在线监测算法及装置,实时监测电缆是否受到破坏性盗窃活动。首先在电缆沟搭建实验平台,采集传感器的加速度数据,并用小波系数相关法进行去噪处理,然后计算加速度与重力方向的夹角,并基于db4小波基对数据进行4层小波分解,获取基于角度的小波能量谱,同时计算合成加速度、偏度、标准差、熵等时频域特征判据,最后通过主成分分析降维,并用BP神经网络算法进行分类,多次测试表明,算法的平均准确率为96.25%,并对算法优化进一步提高了检测的准确性,为电缆防盗提供了一种新思路。

Research on Anti-theft Algorithm of Cable Based on Acceleration Sensor

Due to the high economic value of power cable, cable theft often occurs. In order to reduce the occurrence of cable theft in the cable trench of urban distribution system, online monitoring algorithm based on triaxial acceleration sensor is designed to distinguish whether the cable is damaged or not. Firstly, an experimental platform is built in the cable trench to collect the acceleration data of the sensor, and the wavelet coefficient correlation method is used for denoising. Then the angle between acceleration and gravity direction is calculated. Based on the DB4 wavelet basis, the data is decomposed into four layers of wavelet to obtain the angle-based wavelet energy spectrum. At the same time, the synthetic acceleration, skewness, standard deviation, entropy and other time-frequency characteristic criteria are calculated After classification by BP neural network algorithm, many tests show that the average accuracy of the algorithm is 96.25%, which provides a new idea for cable anti-theft.