With the accelerating electrification revolution, new challenges and opportunities are yet
emerging, despite range anxiety is still one of the biggest obstacles. Battery has been in the …

Fault detection and diagnosis (FDD) is of utmost importance in ensuring the safety and
reliability of electric vehicles (EVs). The EV's power train and energy storage, namely the …

Motor plays a core role in most industrial equipment. Accurate fault diagnosis of motor is a
critical task and intelligent data-driven methods have gained significant advances. However …

Continual learning is promising in intelligent fault diagnosis of three-phase motors, which
allows diagnosis networks to increase diagnosable fault classes without tedious retraining …

In recent years, deep learning has been extensively applied to bearing fault diagnosis with
remarkable achievements. However, in real industrial scenarios, the primary challenge in …

Electric vehicle (EV) is crucial for future transportation which will improve fuel economy and
contributes toward the reduction of emissions. EVs are becoming an increasingly integrated …

Faulty heat pump system operating can cause excessive energy consumption and an
uncomfortable indoor environment. Data-driven method is one of the most widely studied …

Most of the mechanical fault diagnosis methods of induction motors (IMs) are based on
vibration signals. However, vibration sensors are expensive and require direct contact with …

This paper proposes a novel preprocessing method, namely stator current operation
compensation (SCOC), for deep learning-based fault diagnosis of a permanent magnet …

This article presents an intelligent and accurate framework for fault diagnosis of induction
motors using light gradient boosting machine (LightGBM). The proposed framework offers …