Transmission Line Golloping Monitoring Based On MEMS Nine-axis Sensor

the galloping of transmission lines is an important issue long plagued the safe operation of the power grid.lt refers to the movement of high-voltage transmission lines under shock excitation of the wind,which is characterized by a long time,large-scale,causing light line fatigue,wear,severe tower collapsed,power splitting.Since the 1950 's,our experts conducted a study on galloping all aspects of work,the main cause analysis into galloping,galloping monitoring and galloping prevention.Real-time monitoring systemis capable of warning when galloping occurs,to provide protection for the safe operation of power system,and also to provide first-hand data for the study of the causes wire galloping,more on how to prevent and control line galloping,since the high-voltage wire and towers are generally built in relatively scarce staff the mountains or the desert,galloping monitoring technology relies mainly on means of real-time monitoring of the state of motion.Existing monitoring techniques is based on video surveillance and acceleration sensor mon-itoring.Video surveillance system is more intuitive,but only qualitative descriptions galloping motion,and by the light conditions,it is difficult to monitor at night.Compared to the video mon-itor,the acceleration sensor obtaines galloping displacement by secondary integrating through the collected acceleration data of the monitoring points,the drawback is that the accelerometer read-ings change not necessarily due to the acceleration caused by translational movement,the rotation of sensor also change accelerometer reading,which would lead to a problem when there are a rel-atively large r translational acceleration the measuring point at the same time rotation movement,rotation and translational component can not be distinguished from just accelerometer readings.The traditional algorithms based only on the accelerometer assumed measurement point to be a particle,simply ignore rotation in galloping,it is difficult to ensure the correctness of the displace-ment estimated.With the popularity ofMEMS sensors in recent years,cheap,reliable 9-axis MEMS sensor unit(including triaxial accelerometer,three-axis gyroscope,three-axis magnetometer)is more and more applicated in such as mobile phones,smart Wear equipment and other fields,as a basis for the use of motion capture unit.It also brings new opportunities resolve galloping monitoring issues.using 9-axis MEMS sensor can overcome the problem that using the accelerometer alone is interferenced by the rotation movement,and get accurate motion status information from a single measurement point,but also through the development of multi-sensor joint estimation algorithm to achieve restoration of the whole galloping track onlineFor overcoming the deficienciesan in individual point motion estimation with an accelerometer,we develop a galloping estimation framework based on nine-axis MEMS sensor,and its accuracy is conducted through simulation and hardware evaluation experiments,a new offset compensa-tion is proposed algorithm based on experimental,experimental results show that the performance of the compensated system is much better than the results estimated using only the accelerome-ter.further,we develop an algorithm to recovery the the whole trajectory of galloping line based on multi-sensor nodes,which can fix track deviation.the paper is organised as follow:?Presentation of traditional accelerometers algorithm,only secondary integral to estimate dis-placement,analyze the the offset issue of trajectory,and the reasons why rotation affects the accelerometer;?present 9-axis sensor noise characteristics,make a foreshadowing and error analysis for the proposed nine-axis architecture,where we focus on how to use the Allan variance techniques,the actual sensor noise variance is calculated;and how to conduct magnetometer correction,given the correction algorithm and simulation results.?design the proposed 9-axis architecture,discuss in detail a huge advantage compared to the traditional 9-axis architecture algorithm,based on the simulation and hardware experimental to analysis deviation reasons,propose gyro bias error propagation equation,as well as com-pensation algorithm based on the Kalman filter,after compensation,displacement amplitude reaches accuracy of 907%?design multi-sensor model recovery algorithms,optimization solution and performance test-ing,focus on solving the problem of arc-length constraint encountered recovery of the whole wire;?Finally,the article presents real-time testing of the whole algorithm architechture based on OpenGL visualization model of the wire.