To improve the fault identification accuracy of rolling bearing and effectively analyze the fault severity, a novel rolling bearing fault diagnosis and severity analysis method based on the fast sample entropy, the wavelet packet energy entropy, and...
Accurately identifying the fault type of an optical current transformer (optical CT) and evaluating the fault severity can provide strong support for the operation and maintenance of a direct current (DC) power system. In response to the problems tha...
Rolling element bearings are critical components of rotating machinery, with their performance directly influencing the efficiency and reliability of industrial systems. At the same time, bearing faults are a leading cause of machinery failures, ofte...
The transient impact components in vibration signal, which are the major information for bearing fault severity recognition, are often interfered with by ambient noise. Meanwhile, for bearing fault severity recognition, the frequency band selection m...
Today, Permanent Magnet Synchronous Motors (PMSMs) are a dominant choice in industry applications. During operation, different possible faults in the system can occur, so early and automated fault detection and severity estimation are required to ens...
Dissolved gas analysis (DGA) is one of the transformer testing methods that has been widely used for a long time because it does not require the transformer to be offline for testing. The inspection can be conducted while the transformer is operating...
Rolling bearings are important components of rotating machines. For their preventive maintenance, it is not enough to know whether there is any fault or the fault type. For an effective maintenance, a fault severity monitoring needs to be conducted....
Spiral bevel gears are known for their smooth operation and high load carrying capability; therefore, they are an important part of many transmission systems that are designed for high speed and high load applications. Due to high contact ratio and c...
Gearboxes are widely used in industrial processes as mechanical power transmission systems. Then, gearbox failures can affect other parts of the system and produce economic loss. The early detection of the possible failure modes and their severity as...
The motor is essential for manufacturing industries, but wear can cause unexpected failure. Predictive and health management (PHM) for motors is critical in manufacturing sites. In particular, data-driven PHM using deep learning methods has gained po...
This study presents a novel interturn short-circuit fault (ISCF) and demagnetization fault (DF) diagnosis strategy based on a self-attention-based severity estimation network (SASEN). We analyze the effects of the ISCF and DF in a permanent-magnet sy...
Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having vari...
As the phase current sensors and rotor speed/position sensor are prone to fail in the late stage of an offshore doubly-fed induction generator based wind turbine (DFIG-WT), this paper investigates a hybrid fault-tolerant strategy for a severe sensor...
Increasing industrial competitiveness has led to an increased global interest in condition monitoring. In this sector, rotating machinery plays an important role, where the bearing is one of the most critical components. Many vibration-based signal t...
Cable is crucial to the control and instrumentation of machines and facilities. Therefore, early diagnosis of cable faults is the most effective approach to prevent system downtime and maximize productivity. We focused on a “soft fault state&rd...
We focus on an estimation method based on deep learning in terms of fault correction time for the operation reliability assessment of open-source software (OSS) under the environment of an edge computing service. Then, we discuss fault severity level...
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in...
Fault Detection and Diagnosis of electrical machine and drive systems are of utmost importance in modern industrial automation. The widespread use of Machine Learning techniques has made it possible to replace traditional motor fault detection techni...
The health state of rotating machinery directly affects the overall performance of the mechanical system. The monitoring of the operation condition is very important to reduce the downtime and improve the production efficiency. This paper presents a...
When an induction motor is running at stable speed and low slip, the fault signal of the induction motor’s broken bar faults are easily submerged by the power frequency (50 Hz) signal. Thus, it is difficult to extract fault characteristics. The...
Monitoring the condition of rotating machinery is critical in aerospace applications like aircraft engines and helicopter rotors. Faults in these components can lead to catastrophic outcomes, making early detection essential. This paper proposes a no...
During non-severe fault conditions, crowbar protection is not activated and the rotor windings of a doubly-fed induction generator (DFIG) are excited by the AC/DC/AC converter. Meanwhile, under asymmetrical fault conditions, the electrical variables...
Due to the complex mechanical structure of the spring-operated mechanism, its failure mechanisms often exhibit a multi-faceted nature, involving various potential failure sources. Therefore, conducting a failure mechanism analysis for multi-source fa...
In the manufacturing industry, robots are constantly operated at high speed, which degrades their performance by the degradation of internal components, eventually reaching failure. To address this issue, a framework for system-level fault diagnosis...
This paper presents an experimental investigation into the detection and classification of broken rotor bar (BRB) faults in a 1.1 kW squirrel cage induction motor (IM) across various load conditions and fault severities: 1.5 BRBs, 2 BRBs, 2.5 BRBs, a...
Bearings are the elements that allow the rotatory movement in induction motors, and the fault occurrence in these elements is due to excessive working conditions. In induction motors, electrical erosion remains the most common phenomenon that damages...
12 February 2020
The objective of this study is to find factors influencing the injury severity of vehicle at-fault accidents in Shenyang (China), and discuss the commonalities and differences between passenger and freight vehicle accidents. We analyzed 1647 traffic...
Early failure detection in gear systems reduces unplanned downtime and associated maintenance costs in rotating machinery. Although numerous indicators can be extracted from vibration signals, selecting the most relevant ones remains challenging. Thi...
The permanent magnet synchronous motor (PMSM) is a key power component in agricultural machinery. The harsh and variable working environments encountered during the operation of agricultural machinery pose significant challenges to the safe operation...
28 January 2023
The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the p...
This study introduces a novel predictive methodology for diagnosing and predicting gear problems in DC motors. Leveraging AdaBoost with weak classifiers and regressors, the diagnostic aspect categorizes the machine’s current operational state b...
The impact of the constituent oxides of nitrogen, carbon, sulphur, and other particulate matter which make up the gas emissions from diesel engines has motivated several control techniques for these pollutants. Water-in-diesel emulsions provide a rel...
There are numerous methods for detecting interturn faults (ITFs) in the field winding of synchronous machines (SMs). One effective approach is based on comparing theoretical and measured excitation currents. This method is unaffected by rotor tempera...
This paper addresses a comprehensive evaluation of a bearing fault evolution and its consequent prediction concerning the remaining useful life. The proper prediction of bearing faults in their early stage is a crucial factor for predictive maintenan...
A machine learning (ML) methodology for the robust detection and severity characterization of incipient gear faults under variable speed and load is postulated. The methodology is trained using vibration signals from a single accelerometer mounted on...
In determining the severity of power transformer faults, several approaches have been previously proposed; however, most published studies do not accommodate gas level, gas rate, and Dissolved Gas Analysis (DGA) interpretation in a single approach. T...
Displacement signals, acquired by eddy current sensors, are extensively used in condition monitoring and health prognosis of electromechanical equipment. Owing to its sensitivity to low frequency components, the displacement signal often contains sin...
There is an increasing interest in improving energy efficiency and reducing operational costs of induction motors in the industry. These costs can be significantly reduced, and the efficiency of the motor can be improved if the condition of the machi...
Currently, permanent-magnet-type traction motors drive most electric vehicles. However, the potential demagnetization of magnets in these motors limits the performance of an electric vehicle. It is well known that during severe duty, the magnets are...
Although the school bus is considered a safe form of transportation, school bus crashes are a major safety concern. School bus crashes are a result of driver error of either the at-fault school bus or another at-fault vehicle (where the school bus is...
In this paper, a fault-tolerant control method is proposed for a hexacopter under uncertainties. The proposed method is based on adaptive-sliding-mode control (ASMC) and a control allocation scheme. First, a mathematical model of the hexacopter is em...
As the most important device of an Autonomous Underwater Vehicle (AUV), thrusters are one of the main sources of fault. If the thruster fault can be diagnosed in the early stage, it would give more time to guarantee the safety of an AUV. Fault featur...
This paper (Part II) is a follow-up paper to our previous work on developing induction motor inter-turn fault (ITF) models (Part I). In this paper, an online ITF diagnosis method of induction motors is proposed by utilizing the negative sequence curr...
Grid-connected inverters are the core equipment for connecting marine energy power generation systems to the public electric utility. The variation of current sensor fault severity will make fault samples multimodal. However, linear discriminant anal...
In this paper, we introduce a health parameter and estimation algorithm to assess the severity of stator turn-to-turn/inter-turn short-circuit (TTSC) faults in wound-rotor synchronous generators (WRSG). Our methodology establishes criteria for evalua...
A rolling bearing is an important connecting part between rotating machines. It is susceptible to mechanical stress and wear, which affect the running state of bearings. In order to effectively identify the fault types and analyze the fault severity...
Traditional intelligent fault diagnosis methods focus on distinguishing different fault modes, but ignore the deterioration of fault severity. This paper proposes a new two-stage hierarchical convolutional neural network for fault diagnosis of rotati...
Faults in valves that regulate fluid flow and pressure in industrial systems can significantly degrade system performance. In systems where multiple valves are used simultaneously, a single valve fault can reduce overall efficiency. Existing fault di...
Power transformers, as critical components in regional power distribution and transmission systems, require early fault detection to ensure system reliability. This paper presents a scalable design capable of rapidly simulating winding faults in expe...
The incipient faults of rolling bearings are dynamically propagating in the service status. However, the bearing material and the size of the fault will affect its expansion trend and direction. Furthermore, bearings manufactured from different mater...
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