煤矿机械在役轴类零件超声检测现状及展望

Status and prospects of ultrasonic testing for in-service shaft components of coal mine machinery

随着工业4.0和中国制造2025的全面推进,为应对装备制造业发展的新形势,确保质量为先,未来对煤矿机械智能检测与评价技术的需求将会越来越多。全国煤矿兴起智能化建设的高潮,煤矿装备将向着高转速、高功率方向发展,关键零部件的无损检测技术将面临新的挑战。总结了煤矿机械轴类零件无损检测现状,指出了在役轴非拆卸检测存在的问题,主要是因为缺陷回波、结构回波和转换回波在时域上混叠造成缺陷漏检,因为界面压力改变超声波的传播行为造成缺陷定量误差。分析了超声无损检测技术的发展现状和趋势,超声检测将向着无损定量评价、大数据分析、在役检测和计算超声学的方向发展,指出了煤矿机械在役轴类零件超声非折卸检测面临的关键难题,要对在役条件下超声回波产生机理、超声信号反卷积处理和基于大数据的缺陷智能评价这3方面进行深入研究,为缺陷信号提取和缺陷准确定量分析提供理论支持,实现在役轴类零件缺陷检测和剩余寿命预测,以确保煤矿机械安全运行。

With the comprehensive progress of made in China 2025 strategy and Germany’s Industry 4.0,the coal mine equipment industry faces new challenges,and ensure quality,there will be ever more demands for intelligent detection and evaluation technology of coal mining machinery in the future.With the development of the intelligent technology,the higher requirements of coal mine equipment are raised including high power and high speed,and the nondestructive testing technology of key components will face new challenges.The characteristics of non-destructive testing for the coal mine equipment were summed up,and the problems of non-disassembly test of in-service shaft were pointed out.Crack echo,structural echo and conversion echo are aliasing in time domain with certain parts undetected.The propagation characteristics of ultrasonic are easily changed by the interface pressure between the shaft and the connector,resulting in quantitative errors.The development trends of ultrasonic testing were summarized as follows:toward quantitative nondestructive evaluation,toward in-service monitoring and detection big data analysis,and toward computational ultrasound.The problems for non-disassembly ultrasonic inspection were pointed out with quantitative evaluation methods for fatigue crack of in-service shaft components designed,including ultrasonic testing system modeling under in-service conditions,intelligent processing of ultrasonic signals and intelligent evaluation based on big data.All the research will provide theoretical support for accurate quantitative analysis of crack of in-service shaft components.