王 威,徐志鹏,汤建斌,曹松晓,周 彬.基于自适应峰值提取算法的水表梅花针计数方法研究[J].电子测量与仪器学报,2023,37(10):80-88
基于自适应峰值提取算法的水表梅花针计数方法研究
Research on plum blossom needle of water meter counting based on adaptive peak picking algorithm
  
DOI:
中文关键词:  计量学  梅花针  峰值检测  背景异或  水表检定  机器视觉
英文关键词:metrology  plum blossom needle  peak detection  background XOR  water meter calibration  machine vision
基金项目:浙江省自然科学基金(LY18E050009)项目资助
作者单位
王 威 1.中国计量大学浙江省流量计量技术研究重点实验室 
徐志鹏 1.中国计量大学浙江省流量计量技术研究重点实验室 
汤建斌 1.中国计量大学浙江省流量计量技术研究重点实验室 
曹松晓 1.中国计量大学浙江省流量计量技术研究重点实验室 
周 彬 1.中国计量大学浙江省流量计量技术研究重点实验室 
AuthorInstitution
Wang Wei 1.Zhejiang Provincial Key Laboratory of Flow Measurement Technology, China Jiliang University 
Xu Zhipeng 1.Zhejiang Provincial Key Laboratory of Flow Measurement Technology, China Jiliang University 
Tang Jianbin 1.Zhejiang Provincial Key Laboratory of Flow Measurement Technology, China Jiliang University 
Cao Songxiao 1.Zhejiang Provincial Key Laboratory of Flow Measurement Technology, China Jiliang University 
Zhou Bin 1.Zhejiang Provincial Key Laboratory of Flow Measurement Technology, China Jiliang University 
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中文摘要:
      针对水表出厂检定过程中的被检表梅花针在接近于采集频率 1 / 2 的高速转动下识别效果差的问题,提出了一种基于自 适应峰值提取算法的水表梅花针计数方法。 首先对图像进行预处理转化为二值化图像,再利用背景异或法对当前帧图像与起 始帧图像进行异或运算得到梅花针运动轨迹,统计梅花针转动过程中的白色像素占比大小变化,最后通过自适应峰值提取算法 统计转动齿数。 通过实验,证明了该算法克服了伪波峰对峰值提取算法的干扰,相较于传统统计方法,该方法对梅花针转动齿 数识别效果显著,误差不超过 1%。
英文摘要:
      In order to solve the problem of poor recognition effect of the plum blossom needle of the water meter in the process of factory calibration when it rotates at a high speed close to half of the acquisition frequency, a counting method of the plum blossom needle of the water meter based on the adaptive peak picking method is proposed. Firstly, the image is preprocessed and converted into a binary image. Then, the background XOR method is used to perform XOR operations on the current frame image and the starting frame image to obtain the motion trajectory of the plum blossom needle, and the change in the proportion of white pixels is calculated during the rotation process of the plum blossom needle. Finally, the number of rotating teeth is counted through the adaptive peak picking algorithm. The experimental results show that the algorithm overcomes the interference of false wave peaks on the peak picking algorithm. Compared with traditional statistical methods, this method has a significant recognition effect on the number of rotating teeth of plum blossom needles, with an error of no more than 1%.
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