Design On Remote Diagnosis System Of Leakage Fault In Heating Network

In recent years, accidents of heating pipe leakage occurred frequently, the main reason for this phenomenon is the lack of fault diagnosis systems, which lead to the failure of locating the fault point in time, so the optimal repairing time is delayed and the influence of accidents is further expanded, and more difficulties are brought to the repairing work. In this paper, the leakage fault in the primary heating network is set to be the background, a remote diagnosis system of a network leakage fault is designed in order to solve the lagging problem of the current fault diagnosis.Considering the actual heating situation in our country, the negative pressure wave method is used to diagnose the heating pipeline leakage fault in this paper. According to the need of the fault diagnosis and the actual working condition of the heating station, the embedded chip STM32is selected to complete the design of the hardware and software in the local controller of the heating station. Furthermore, GPS timing technique was used to realize the clock synchronization of controllers in each site, the collected data labeled with time can avoid the time error caused by the delaying of data transmission. Considering sites scattered in the networking mode, GPRS and the Internet network are selected, the remote data transmission in each site is accomplished through the industrial-grade DTU. The remote fault diagnosis system which communicates with each station through the socket is an application program based on the MFC dialog box, each site sends relevant data information to the remote fault diagnosis center initiatively when they tell the pressure of data surpassing threshold. After receiving and parsing the information correctly the fault center will invoke the MATLAB dynamic library encapsulated with of the wavelet algorithm which can denoise the collected pressure signal, and use db4wavelet to analysis the detail signals in multi-scale to find the maxima of the wavelet transform modulus that is the position of singular point, then calculate the time of collecting negative pressure wave and the time difference through a timestamp carried by stress data and the sampling frequency to find the leak point through the negative pressure wave leakage location formula.Experiment results show that a simulated leak point in a4-km-pipeline, this system only takes several seconds to notice the fault information and locate the leak point which improves the real-time of the fault diagnosis obviously.