基于小波分析的智能轮胎磨损和载荷的检测方法

Detection Method of Intelligent Tire Wear and Load Based on Wavelet Analysis

为了获取轮胎运行状态下的状态信息,提出了一种基于小波变换的智能轮胎磨损和载荷检测方法,用于实时检测轮胎的载荷和磨损状态。为研究轮胎在运行时胎面的震动情况,通过贴装于轮胎内壁中央的三轴加速度传感器获取加速度波形,再通过莫尔斯小波多尺度分析轮胎接地点处的胎面震动情况,提取特征,输入BP神经网络,获取检测结果。结果表明:所提出的算法可以较为精确地监测轮胎的磨损和载荷状态;在90%以上的情况下,可以实现磨损绝对误差在0.3 mm以内,载荷绝对误差在12 kg以内。为车辆提供关键轮胎信息,助力安全驾驶,有广泛的应用前景。

In order to obtain the state information of tires in running state,a wear and load detection method for intelligent tires based on wavelet transform was proposed,which was used to detect tire load and wear state in real time.In order to study the vibration of the tread when the tire was running,the acceleration waveform was obtained through a three-axis accelerometer attached to the center of the inner wall of the tire,and then the Morse wavelet was adopted to analyze the tread vibration at the grounding point of the tire at multiple scales to extract features.Input the features into the BP neural network to obtain the detection result.The results show that the proposed algorithm can more accurately monitor the tire wear and load state;in more than 90%of the cases,the absolute error of wear can be achieved within 0.3 mm,and the absolute error of load is within 12 kg.The method can provide key tire information for the vehicle and assist safe driving,so it has a wide range of application prospects.