Research And Implementation Of Time-grating Sensor Remote Monitoring System

As a high-precision sensor,the time-grating sensor has been used in industrial production and national defense construction.After years of research and technological innovation,it has achieved a major breakthrough.Driven by national policies and industrial production,the machinery manufacturing industry is developing toward intelligentization,informatization,and automatization.Based on market demand feedbacks,research on smart time-grating sensors has been proposed.The research content of this article is the networking key technology and system development of remote monitoring system for time-grating sensors,laying a solid foundation for intelligent time-grating sensors to entering the market.In the field of high-precision measurement,the development of the monitoring system must be designed for the sensor itself to meet the actual operating conditions,because the characteristics and parameters of different sensors are quite different.The core of the timegrating sensor is the generation of the excitation signal and the construction of uniform coordinate system.By introducing the principle of the time-grating sensor and analyzing the signal characteristics,the underlying hardware circuit is improved to realize network interface design firstly,and then a monitoring system with health prediction function is developed based on the analysis of signal characteristics,which has good real-time performance,high reliability,standardized development and strong portability.Based on the above,this paper has studied the remote monitoring system of timegrating sensor,the main research work is as follows:(1)Through the introduction of the measurement principle of the field-type time-grating sensor,the characteristics of the sensor excitation signal are emphatically analyzed,the unequal amplitude or phase non orthogonal of the excitation signal are analyzed,deriving the second-order error,which eventually lead to the error of the phase difference of the induced signal,resulting in the measurement error and influencing the precision of the sensor.(2)For the theoretical analysis,the selection of characteristic parameters is determined,and the amplitude and phase of excitation signal generated by each module of the sensor signal processing system are collected.The correlation between each module circuit and the excitation signal is analyzed,and a health status of the circuit warning based on excitation signal data is proposed.The BP neural network and the RBF neural network are used to determine the diagnostic criteria.(3)Based on the prediction of data trend to achieve the purpose of pre-diagnosis,the trend prediction of the excitation signal of the time-grating sensor is analyzed by using autoregressive prediction model,gray prediction model,BP neural network model and RBF neural network model on the basis of discrete wavelet transform.This paper takes the excitation signal amplitude output by the power amplification module as an example,500 data are collected and fitted by using multiple models.Then,the variation trend of the amplitude of the excitation signal is predicted according to the fitting function.The predicted value is compared with the actual value to analyze advantages and disadvantages of the four algorithms.(4)The hardware and software design of Time-grating sensor monitoring system.The design of the networked hardware platform mainly includes the design of excitation signal generation module,signal conditioning module,data acquisition module,and Ethernet module.Software system design mainly includes database design,server design,protocol package design,early warning function design,and monitoring interface development.(5)Utilizing the laboratory hardware environment,the performance of the monitoring system is tested and the functions of the system are verified and optimized.In summary,combined with the characteristics of the time-grating sensor signal,a remote monitoring system for the time-grating sensors was developed based on the network technology,which can monitor the operating status of sensors and the health of circuits,and promote the development process of intelligentized time-grating sensors.