| The normal operation of catenary system is directly related to the reliability and safety of railway running system.Thus in order to discover the potential hazards in time,each technical parameter of catenary must be monitored to analyze and judge the operating status of catenary function.Now to prevent the damages caused by the high temperature of electrically connecting clamps and the changes of messenger wire tension,catenary monitoring system must be designed to detect the clamp temperature and the messenger wire tension.And to ensure the locations of catenary faults,the inspection vehicle must be positioned in the monitoring process at the meantime.With analysis on the catenary requirements of parament detection system and vehicle positioning system,the clamp temperature and messenger wire tension monitoring system and the inspection vehicle positioning system based on UWB were established in this paper.The catenary detection systems of electrically connecting clamp temperature and messenger wire tension were designed in this paper.On one hand,the key parameters of the thermal imager are determined by establishing the infrared detection model of the clamp temperature.On the other hand,the tension detection plan is designed through the mechanical analysis of messenger wire compensator.Then the experiment confirmed that the detection precision can meet the catenary detection index.Further according to the wireless positioning theories,the numbers of base stations and the requirements of inspection vehicle positioning,the positioning system of inspection vehicle based on UWB technology was established with the application of P440 modules.Then the coordinate's solution method based on least-squares method was put forward.Then aim to optimize the distance error of UWB system,the presicion improving model based on neural network algorithm was proposed.Meanwhile the genetic algorithm was applied to improve network performance.So the coordinates can be calculated with the optimized distance by the process of network train.On the other hand,the dynamic precision improving model was desgined with the use of information filter algorithm.Then the positioning precision in the process of inspection vehicle motion can be optimized by the combination of state equation and measurement equation.Through experiment of vehicle positioning,the conculsion can be confirmed that in static positioning,the data solutions of z axis by UWB system were inaccurate with the effect of distance errors and base station layout.So the initial positioning precision could not meet the positioning requirements.Then with the application of centroid algorithm,the 3-d positioning precision was 38 cm,but the coordinates of z axis was still with considerable errors.After using the neural network to optimize the distance errors,the precision was 16.8 cm and the errors of z axis were obviously decreased.Futher after the network was optimized by genetic algorithm,the precision was 13.9 cm.So the performance of positioning system improved.On the other hand,in dynamic positioning process,there were some differences between the real vehicle trajectory and the measurement vehicle trajectory by GA-ANN optimization,and then the positioning precison was 19.2 cm.By the use of information filter algorithm,the errors of x axis and z axis were decreased,and the precison was 16.3 cm.Finally the system can more accurately capture the vehicle position.The influence from the photographing frequency of infrared thermal imager,the frequency and errors of UWB positioning system and the speed of vehicle on temperature monitoring and positioning system based on UWB were analyzed with the build of monitoring and positioning system model.Then the conclusion can be confirmed by experiments that the temperature monitoring positioning system can collect the location and temperature information of each clamp through positioning the inspection vehicle in order to achieve dealing with the faults in time. |
PDF Full Text Request