Research On The Automatic Detection Method Of Rubber Marks On The Runway

With the development of our country's civil aviation industry, its infrastructure is gradually becoming large-scale and complex. The airport runway is an important part of civil aviation infrastructure, and its skid resistance of runway pavement affects the flight safety directly. In the process of aircraft landing, rubber particles are created because of the friction between the tire and pavement, which becomes the rubber marks and attaches on the runway pavement. The rubber marks will gradually reduce runway skid resistance, which will case accident, for example, skidding off the runway. In order to ensure the safety of civil aviation airport runway and airworthiness, the rubber marks detection has become an important part of airport infrastructure maintenance. This research can promote the automation of the airport runway maintenance equipment.Based on the analysis of the current detection methods of rubber mark, this article has, firstly, analyzed the main reasons of the formation of the rubber marks and studied the influence created by the rubber mark on friction coefficient, flatness, number of cracks, then summarized the main features of the airport runway rubber marks. Secondly, the airport runway rubber mark detection system controlled by the SCM has been designed and the hardware platform and software platform has been built. And it is consisted of three parts which are the vehicle mobile terminal subsystem, the wireless communication subsystem and the remote control subsystem. And this system can realize the function of rubber marks' image acquisition, image detection, data transmission and display results. Thirdly, this article has adopt The gray image feature extraction algorithm to solve the problem of automatic detection of airport runway rubber, which is not accuracy enough, so the image feature extraction algorithm based on the RGB color space has been proposed. From the practical application point of view, the above two algorithms are not adaptive to airport runway pavement's complex environment. In order to guarantee the reliability of the system's hardware, the article has introduced the BP neural network technology to improve the above two algorithms. Finally, this article has verified the feasibility and effectiveness of the system through computer simulation and hardware.