摘要
为了实现复杂结构下的管道缺陷检测以及强干扰环境下检测信息的有效传输,设计了一种新型煤层气管道缺陷识别系统。系统以弱磁检测为基础,通过LoRa技术实时传输信号至上位机;通过最小二乘法和小波消噪处理算法对信号进行处理,并采用K最近邻分类算法确定缺陷位置。实验结果表明,系统对复杂结构下的管道缺陷具有较强的辨识能力,且传输过程中的检测信号具有较强的抗噪性能。
In order to realize the detection of pipeline defects under complex structure and the effective transmission of detection information under strong disturbing environment, a new system of CBM fault identification is designed. Based on field weakening detection, the system real-time convey the signal to the host computer by the technology of LoRa. The signal is processed by the least square method and wavelet denoising algorithm, and use the K nearest neighbor classification algorithm to ascertain the location of defection. The experimental results show that the system has stronger identification ability for pipeline defects under complex structure and the detection signal has stronger anti-noise performance during the transmission process.
作者
董鹏飞
乔铁柱
DONG Peng-fei;QIAO Tie-zhu(Key Laboratory of Advanced Transducers and Intelligent Control System,Ministry of Education,Institute of Measurement and Control Technology,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《煤炭技术》
CAS
2018年第11期359-361,共3页
Coal Technology
基金
山西省自然科学基金项目(201601D011059)
关键词
煤层气管道
弱磁检测
缺陷识别
LoRa技术
coal bed gas pipeline
weak magnetic detection
defect recognition
LoRa technology
