计量器具校准数据的可视化分析与故障预测  

Visual Analysis and Fault Prediction of Calibration Data of Measuring Instruments

作　　者：程福敏 CHENG Fumin(Shanxian Metrology,Verification and Testing Institute,Heze 274399,Shandong,China)

机构地区：[1]单县计量检定测试所,山东菏泽274399

出　　处：《流体测量与控制》2025年第1期39-41,共3页Fluid Measurement & Control

摘　　要：以计量器具校准数据为研究对象,通过对校准数据进行可视化分析,探索数据中蕴含的规律和故障特征,并基于机器学习算法构建故障预测模型。研究结果表明,可视化分析能够直观地展现校准数据的分布特点和异常情况,为故障诊断提供重要依据。同时,基于校准数据训练的故障预测模型能够有效识别潜在的器具故障,为计量器具的维护和管理提供决策支持。本文研究方法和成果可为计量器具的智能化管理提供新的思路和参考。This article takes the calibration data of measuring instruments as the research object.Through visual analysis of the calibration data,we explore the patterns and fault characteristics contained in the data,and build a fault prediction model based on machine learning algorithms.Research results show that visual analysis can intuitively display the distribution characteristics and anomalies of calibration data,providing an important basis for fault diagnosis.At the same time,the fault prediction model trained based on calibration data can effectively identify potential instrument faults and provide decision support for the maintenance and management of measuring instruments.The research methods and results of this article can provide new ideas and references for the intelligent management of measuring instruments.

关 键 词：计量器具 校准数据 可视化分析 故障预测 机器学习 

分 类 号：TB9[一般工业技术—计量学]