| Flow velocity is one of the basic elements of hydrological observation.So accurate measurement of flow rate plays an extremely important role on water conservancy projects,ecological environment,flood control and disaster as well as military operations,which has become research hotspot in meteorological,hydrological,environmental and other fields.To ensure the accuracy of the flow measurement results,a metrological verification system should be established specifically applied to the existing flow velocity measurement equipment.At present,the general flow meter calibration equipment: straight water flume and calibration car,reflected lower efficiency and higher costs due to its bulky shape,high construction and maintenance costs and fewer available devices.Therefore,it is necessary to develop an annular flow velocity standard device to provide verification service for small rotating element current meter.Firstly,the overall design and collaborative optimization of the device were carried out.And the basic parameters and existing problems of the existing flow velocity verification equipment were analyzed.The necessity of developing a set of small-scale portable flow velocity standard device was proposed,and the design target and technical parameters of the device were clarified.According to the functional requirements of the standard device,the workflow of the measurement and control system was designed,and the conceptual model of the device was established by using the SolidWorks 3D modeling tool.To improve the automation degree of the device,the digital image recognition method based on BP neural network was used to identify the indication of the measured instrument.To realize the parameterization of the device design scheme,an improved multidisciplinary collaborative optimization algorithm was used to identify the optimal solution of the design variables of each discipline.According to the design goal of the device,the optimization models,three sub-disciplines of annular flume geometry parameters,servo system motion parameters and the overall weight of the standard device,were established respectively.Furthermore,the rationality of the optimization results was determined,realizing the optimal design of the standard device.Secondly,the hardware circuit and the verification software of the standard device measurement and control system was completed.We had achieved the servo motor speed control through the servo driver operating mode setting and electrical level conversion interface.And using the RS-422 serial communication technology and ADM3485 interface chip,we achieved the encoder data read.In addition,the Xilinx IP core,such as the three-mode Ethernet MAC and GTP high-speed serial transceivers and so on,and the 88E1111 PHY chip were used to realize the high-speed Ethernet data communication between the FPGA and the upper computer.The design of the standard device verification software was completed by using the object-oriented programming method and the multilayer architecture model.The specific function module of the software was realized by the C ++ programming language,and the verification data management was realized by the SQL Server database.Finally,a non-statistical uncertainty evaluation model for small sample and unknown distributed measurement data was established by combining the grey system theory and the uncertainty assessment method,and applied to the uncertainty evaluation of the verification results.According to the selected series of verification points,the A uncertainty component of the verification results was calculated by using the grey system method,the Bessel method,the range method and the maximum error method respectively.The feasibility of the grey system theory in the uncertainty evaluation of the small sample data was comparatively analyzed.Moreover,the source and the evaluation method of B uncertainty component of the standard device were also studied. |
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