摘要
响应时间是反映压力变送器动态性能的关键技术指标,针对现有测试手段无法对在役设备直接检测的问题,分别建立基于噪声信号自回归与功率谱密度响应时间的时、频模型,研究噪声分析实时获取压力变送器响应时间方法。对噪声分析法进行仿真验证,结果表明该方法具有较高准确性和稳定性,且对不同参数的系统具有良好的适用性。对罗斯蒙特3051型压力变送器进行实验,与斜坡信号实验比对,噪声分析法与斜坡法响应时间结果偏差小于5%,对算法优化分析看出MTM算法和Welch算法较MUSIC算法结果更加吻合,分析数据长度达到1×105后结果趋于稳定。对核电站现场数据进行噪声法分析,结果符合预期,验证了所提方法用于传感器现场测试中的有效性。
The response time of pressure transmitter is a key technical index to reflect its dynamic performance.Given the existing testing methods can not direct detect the inservice equipment,the response time⁃frequency model based on the AR method(Autoregressive model)and power spectral density of noise signal is established to calculate the pressure transmitter response time via a real⁃time analysis.The simulation results present the satisfying accuracy and stability of the proposed method and verify the capability of systems with different parameters.A series of experiments are carried out with the commercially available pressure transmitter(Model 3051,Rosemont),and then compared with the standard ramp signal experiment.The resultant deviation between the noise analysis and the ramp method is less than 5%.The optimization of the power spectrum analysis shows the MTM and Welch algorithms are more consistent than the MUSIC algorithm,and the results tend to be stable when the amount of data is up to 1×10^(5).The noise method is also used to analyze the real⁃time data in a nuclear power plant,yielding results conforming with the expectation,which further verifies the effectiveness of the method in the on⁃site testing on the sensor.
作者
胡佳城
宋延勇
居法力
田昌
苏明旭
HU Jiacheng;SONG Yanyong;JU Fali;TIAN Chang;SU Mingxu(School of Energy and Power Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Institute of Process Automation&Instrumentation,Shanghai 200233,China;CNNC Sanmen Nuclear Power Co.,Ltd,Sanmen Zhejiang 317100,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2023年第6期916-921,共6页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(51776129)。
关键词
压力变送器
噪声分析
原位测量
响应时间
功率谱密度
AR模型
pressure transmitter
noise analysis
In⁃situ measurement
response time
power spectral density algorithm
AR model
