{"title":"测量设备计量可靠性评价过程中动态误差分析的特点","authors":"V. Ignatkin","doi":"10.33955/2307-2180(2)2019.36-42","DOIUrl":null,"url":null,"abstract":"The article discusses metrological reliability of measuring equipment (ME), argues that ME imprecision must be considered not in statics, 'out in dynamics, taking into account the change of its characteristics over time. Measurement imprecision and its components are considered as random processes that are fully characterized by multidimensional distribution. It is advisable to determine the probability of metrological measurements directly from the experiment due to the difficulties of analytical solution to the problem. The characteristics of dynamic imprecision depend on both the values of the measured object and the ME properties. The physical cause of dynamic imprecision taking place is inertia of ME, its exhaustive description relies on the use of Duamel integral, which determines the response of inertial link to the input influence. As a criterion for signal differences one can use quite different functionals, taking into account further use of measurement results, the convenience of computing, the properties or input influences, and so on. It is most expedient to use the dispersion of signal differences. To calculate the parameters of dynamic imprecision it is necessary to know the energy spectrum of the input signal. The given ratios can be used for both stationary and non-stationary processes. \nThe paper provides examples of using these ratios, recommendations for reducing measurement errors in each particular case.","PeriodicalId":52864,"journal":{"name":"Metrologiia ta priladi","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Features of Dynamic Error Analysis in the Process of Evaluation of Metrological Reliability of Measuring Equipment\",\"authors\":\"V. Ignatkin\",\"doi\":\"10.33955/2307-2180(2)2019.36-42\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article discusses metrological reliability of measuring equipment (ME), argues that ME imprecision must be considered not in statics, 'out in dynamics, taking into account the change of its characteristics over time. Measurement imprecision and its components are considered as random processes that are fully characterized by multidimensional distribution. It is advisable to determine the probability of metrological measurements directly from the experiment due to the difficulties of analytical solution to the problem. The characteristics of dynamic imprecision depend on both the values of the measured object and the ME properties. The physical cause of dynamic imprecision taking place is inertia of ME, its exhaustive description relies on the use of Duamel integral, which determines the response of inertial link to the input influence. As a criterion for signal differences one can use quite different functionals, taking into account further use of measurement results, the convenience of computing, the properties or input influences, and so on. It is most expedient to use the dispersion of signal differences. To calculate the parameters of dynamic imprecision it is necessary to know the energy spectrum of the input signal. The given ratios can be used for both stationary and non-stationary processes. \\nThe paper provides examples of using these ratios, recommendations for reducing measurement errors in each particular case.\",\"PeriodicalId\":52864,\"journal\":{\"name\":\"Metrologiia ta priladi\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Metrologiia ta priladi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33955/2307-2180(2)2019.36-42\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metrologiia ta priladi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33955/2307-2180(2)2019.36-42","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Features of Dynamic Error Analysis in the Process of Evaluation of Metrological Reliability of Measuring Equipment
The article discusses metrological reliability of measuring equipment (ME), argues that ME imprecision must be considered not in statics, 'out in dynamics, taking into account the change of its characteristics over time. Measurement imprecision and its components are considered as random processes that are fully characterized by multidimensional distribution. It is advisable to determine the probability of metrological measurements directly from the experiment due to the difficulties of analytical solution to the problem. The characteristics of dynamic imprecision depend on both the values of the measured object and the ME properties. The physical cause of dynamic imprecision taking place is inertia of ME, its exhaustive description relies on the use of Duamel integral, which determines the response of inertial link to the input influence. As a criterion for signal differences one can use quite different functionals, taking into account further use of measurement results, the convenience of computing, the properties or input influences, and so on. It is most expedient to use the dispersion of signal differences. To calculate the parameters of dynamic imprecision it is necessary to know the energy spectrum of the input signal. The given ratios can be used for both stationary and non-stationary processes.
The paper provides examples of using these ratios, recommendations for reducing measurement errors in each particular case.