Abstract This paper investigates the problem of incipient fault detection and diagnosis (FDD) in wind energy conversion systems (WECS) using an innovative effective approach called ensemble learning-sine cosine optimization algorithm (EL-SCOA). The evolved strategy involves two primary steps: first, a sine-cosine is used to extract optimize features order only select most descriptive ones. Seco...

Faults and anomalous behavior affect the operation of Heating, Ventilation Air Conditioning (HVAC) systems. This causes performance loss, energy waste, noncompliance with regulations discomfort among occupants. To prevent damage, automated, fast identification faults in HVAC systems is needed. Fault Detection Diagnosis (FDD) techniques are very effective for these purposes. The best FDD methods...

Prompt detection and diagnosis of faults in industrial systems areessential to minimize the production losses, increase the safety of the operatorand the equipment. Several techniques are available in the literature to achievethese objectives. This paper presents fuzzy based control and fault detection for a6/4 switched reluctance motor. The fuzzy logic control performs like a classicalproporti...

In this paper, a general linear time-varying multiple-axis (LTVMA) vibration model of shield tunnel boring machine (TBM) cutterhead driving system is established. The corresponding multiple inputs and multiple outputs (MIMO) state-space model is also presented. The linear vibration model is analysed, and the vibration-torque transfer function matrix and the vibration-torque static gain matrix a...

This work addresses the problem of fault detection and diagnosis (FDD) for a quad-rotor mini aerial vehicle (MAV). Actuator faults are considered on this paper. The basic idea behind the proposed method is to estimate the faults signals using the extended state observers theory. To estimate the faults, a polynomial observer is presented by using the available measurements and know inputs of the...

The current paper proposes intelligent Fault Detection and Diagnosis (FDD) approaches, aimed to ensure the high-performance operation of Wind energy conversion (WEC) systems. First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. main idea behind use PSO remove irrelevant features extract only most significant ones from raw data in order improve ...

Being a safety-critical system, safety is extremely important for any nuclear power plant (NPP). Therefore, to maintain the safety of NPPs at an acceptable level, preventive measures are necessary to deal with potential issues. During plant operation, faults and failures can occur in sensors, equipment, and processes which can have impact on the performance of the plant. These faults are more p...

The development of health monitoring technology for liquid rocket engines (LREs) can effectively improve the safety and reliability launch vehicles, which has important theoretical engineering significance. Therefore, we propose a fault detection diagnosis (FDD) method large LOX/kerosene engine based on long short-term memory (LSTM) generative adversarial networks (GANs). Specifically, first mo...