Journal ArticleDOI
Fault Detection Strategy of Vehicle Wheel Angle Signal via Long Short-Term Memory Network and Improved Sequential Probability Ratio Test
TLDR
The effectiveness of the proposed fault detection strategy of vehicle wheel angle signal via long short-term memory network (LSTM) and improved sequential probability ratio test (SPRT) is verified.Abstract:
In order to improve the accuracy of fault detection results, this paper proposes a novel fault detection strategy of vehicle wheel angle signal via long short-term memory network (LSTM) and improved sequential probability ratio test (SPRT). Firstly, a signal estimation method based on data-driven modeling is presented, which fuses the vehicle current status information and adopts the LSTM based on deep learning to estimate the vehicle wheel angle signal. Then, the signal residual sequence is obtained by comparing the estimated wheel angle signal with the measured wheel angle signal. Based on this, the improved SPRT method based on mathematical statistics is used to analyze the signal residual sequence, so as to detect the fault signal timely and accurately. Finally, the accuracy of the estimation results is analyzed under sinusoidal condition, double-lane change condition and sinusoidal sweep frequency condition, and the effectiveness of the fault detection strategy proposed in this paper is further verified under the stuck fault condition and drift fault condition. The results indicate the effectiveness of the proposed fault detection strategy, which is of great significance to improve the safety and reliability of the vehicle.read more
Citations
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Journal ArticleDOI
Fault Diagnosis and Fault-Tolerant Compensation Strategy for Wheel Angle Sensor of Steer-by-Wire Vehicle via Extended Kalman Filter
TL;DR: In this paper , a fault diagnosis and fault-tolerant compensation (FDFTC) strategy for wheel angle sensor of steer-by-wire (SBW) vehicle via extended Kalman filter (EKF) is proposed.
Journal ArticleDOI
An Effective Fault Detection Method for HVAC Systems Using the LSTM-SVDD Algorithm
TL;DR: Wang et al. as mentioned in this paper proposed a fault detection method that combines a system simulation model and an intelligent detection algorithm, which first uses the Modelica modeling language to build a scalable simulation model of the system to obtain fault data that are not easily accessible in practice.
Journal ArticleDOI
An integrated LSTM-AM and SPRT method for fault early detection of forced-oxidation system in wet flue gas desulfurization
Lars Svensson,Roger Smith +1 more
TL;DR: In this paper , a fault early detection method was developed to improve the predictive maintenance of the forced-oxidation system including blowers, pipes, and the slurry tank, and a model based on long short-term memory (LSTM) network and attention mechanism was constructed to predict real-time operation parameters and compare with the measured values.
Journal ArticleDOI
Steering Actuator Fault Diagnosis for Autonomous Vehicle With an Adaptive Denoising Residual Network
TL;DR: In this article , an adaptive denoising residual network (AD-ResNet) is proposed for fault diagnosis of steering actuator with reduced noise interference and improved accuracy, and the proposed method was validated against a fault dataset that was built using road experiments with an autonomous vehicle.
Journal ArticleDOI
Steering Actuator Fault Diagnosis for Autonomous Vehicle With an Adaptive Denoising Residual Network
TL;DR: In this paper , an adaptive de-noising residual network (AD-ResNet) was proposed for fault diagnosis of steering actuator with reduced noise interference and improved accuracy, which achieved an accuracy, a sensitivity, a specificity, and an F1-score of 91.66, 91.22, and 0.9159.
References
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Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network
Xiaofeng Yuan,Lin Li,Yalin Wang +2 more
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State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network
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UAV Attitude Estimation Using Unscented Kalman Filter and TRIAD
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