摘要
针对目前国内各种钢丝绳检测仪器的不足之处,选定了钢丝绳断丝损伤信号识别的特征量,并介绍了信号处理和特征提取算法。提出了利用BP神经网络技术对检测信号进行分析处理的方法,提高了检测的精度和灵敏度。通过模拟和实际检测,断丝损伤识别的准确率达到了90%,验证了网络的可靠性和实用性。
Aiming at the defect of steel rope broken wires check device at home now, the signal eigenvalue was selected, the practical methods of signal processing and character extraction were discussed and summarized . BP neural network method was used to analyze and process the signal from the broken wires in a steel rope, the accuracy and sensitivity of check was improved. The simulation and actual detection show that the veracity of broken is 90% , its reliability and practicality are validated.
出处
《机电工程》
CAS
2008年第8期44-46,共3页
Journal of Mechanical & Electrical Engineering
基金
浙江省教育厅科研资助项目(20050454)
关键词
钢丝绳
断丝
检测
信号处理
神经网络
steel rope
broken wires
detection
signal processing
neural network
