Weigh-in-Motion System Based on an Improved Kalman and LSTM-Attention Algorithm

Abstract

A weigh-in-motion (WIM) system continuously and automatically detects an object’s weight during transmission. The WIM system is used widely in logistics and industry due to increasing labor and time costs. However, the accuracy and stability of WIM system measurements could be affected by shock and vibration under high speed and heavy load. A novel six degrees-of-freedom (DOF), mass–spring damping-based Kalman filter with time scale (KFTS) algorithm was proposed to filter noise due to the multiple-input noise and its frequency that is highly coupled with the basic sensor signal. Additionally, an attention-based long short-term memory (LSTM) model was built to predict the object’s mass by using multiple time-series sensor signals. The results showed that the model has superior performance compared to support vector machine (SVM), fully connected network (FCN) and extreme gradient boosting (XGBoost) models. Experiments showed this improved deep learning model can provide remarkable accuracy under different loads, speed and working situations, which can be applied to the high-precision logistics industry.

Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction

“…In the LSTM with attention applied to time series forecasting, the input data are typically divided into a series of time steps and processed through the LSTM. The attention mechanism then provides a weighted sum of the hidden states of the LSTM units, which is used as input to a fully connected layer for the final prediction [ 42 ].…”

Development and Temperature Correction of Piezoelectric Ceramic Sensor for Traffic Weighing-In-Motion

“…There is an urgent need to reduce the phenomenon of overload, monitor and evaluate the traffic volume, and ensure the safety and efficiency of vehicle transportation. The WIM system automatically obtains the vehicle load information through the buried load cells on the road without affecting the normal driving of vehicles, so as to achieve the purpose of overload control [3][4][5]. As the core of the WIM system, the sensor plays a vital role in the whole measurement process.…”