A Pattern Recognition Based Airworthiness Discrimination Method for Airport Runway Pavement
A technology for airport runway and pattern recognition, which is applied in character and pattern recognition, computer parts, instruments, etc., can solve the problems of time-consuming, laborious and huge investment, and achieve high efficiency, efficiency, safety and stability, and fast discrimination.
Active Publication Date: 2021-07-23
民航机场建设集团华北有限公司
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The airport field staff drives the friction coefficient detection vehicle to the runway for multiple times at high speed to generate the road surface friction coefficient. The traditional method requires a huge investment and is time-consuming and laborious. However, in a busy airport, it is often difficult to find a time slot to complete the project. Work
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[0052] Such as figure 2 Shown, the airworthiness discrimination method of airport runway pavement surface airworthiness based on pattern recognition of the present invention, comprises the following steps:
[0053] A. Use the tolerance fuzzy clustering algorithm to cluster and preprocess the data samples:
[0054]This method mainly collects trace images near the two-way touchdown zone of the runway and the two-way take-off holding point. In order to achieve simple structure, simple training, and ensure high precision of the algorithm, the main body uses RBF neural network to achieve simple linear learning and nonlinear learning. high-precision effect. On the other hand, the clustering of data samples and the number of hidden layer neurons have a decisive impact on the performance of RBF neural network, while the rules of traditional clustering algorithms are too harsh, and the clustering processing of pixel sample sets in trace images Effect is unsatisfactory, so the presen...
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The invention discloses a method for judging the airworthiness of an airport runway surface based on pattern recognition, which includes: clustering and preprocessing data samples by adopting a tolerance fuzzy clustering algorithm; number to obtain the optimal real-time performance; train the RBF neural network; use the multi-dimensional compensation method to optimize the local part of the algorithm to achieve the most accurate discrimination results with the least number of hidden layer neurons. The invention only needs to acquire runway monitoring images to complete the airworthiness discrimination of the airport runway surface in real time without the participation of manual and other equipment, and has the advantages of fast discrimination speed, high efficiency, safety and stability.
Description
technical field [0001] The invention belongs to the fields of artificial intelligence, big data analysis and computers, and in particular relates to a pattern recognition-based method for judging the airworthiness of an airport runway surface. Background technique [0002] Due to the frequent take-off and landing of aircraft, rubber scratches or rain and snow on the pavement of airport runways lead to a decrease in friction coefficient, which seriously affects aviation safety. At present, the airworthiness judgment of the airport runway pavement needs the help of the runway friction coefficient detection vehicle, which is generally converted from a sports car. The airport field staff drives the friction coefficient detection vehicle to the runway for multiple times at high speed to generate the road surface friction coefficient. The traditional method requires a huge investment and is time-consuming and laborious. However, in a busy airport, it is often difficult to find a t...
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IPC IPC(8): G06K9/62
CPCG06F18/285G06F18/23G06F18/214
Inventor 张新平张严慈凌萍萍
Owner 民航机场建设集团华北有限公司