Motor Failure Research Articles

Chaos theory using density of maxima applied to the diagnosis of three-phase induction motor bearings failure by sound analysis

Bearing failures in the industry are a recurring problem that can cause permanent damage to machines and interrupt production in important sectors of a factory. For this reason, over the past few decades, different studies have been carried out to develop techniques for diagnosing this failure. The main challenge found in the diagnosis is to identify the fault and its severity with the machine operating under dynamic load conditions, generally requiring a large acquisition window. This paper presents an approach based on quantification of the chaotic behavior for the characterization of rigid ball bearing failure of a three-phase induction motor through the method called signal analysis based on chaos using density of maxima (SAC-DM) using the sound signal emitted by the engine. This technique is based on an algorithm that counts peaks of the motor sound signal in the time domain to detect faults using only a sensor and an algorithm with a low computational cost. Experimental results show that the SAC-DM technique is sensitive to bearing failure and allows the diagnosis to be made even under load variation and with an acquisition window of just 0.28s.

에너지 절감을 위한 전기 자동차용 고효율 독립 다상 IPM BLDC 허브모터 설계에 관한 연구

For an electric car traction motor has the efficiency of high efficiency motor, travel, space features efficiency as it will be motor is hub motor is suitable and to address Independent multi-phase ipm bldc the motor development test, and the tester to work with the efficiency and performance through the power to black. In addition, the most important by car accident, a secondary accident prevention must be ensured. To that end, part of the motor failure, driven by repairs in place reliable motor to an existing Y, △ structure with an independent structure have I motor. So, multi-phase independent structure with a new type I ipm bldc want to identify the characteristics of the motor, and the development of verification.

Fail-Safe Flight of a Fully-Actuated Quadrotor in a Single Motor Failure

In this letter, we introduce a new quadrotor fail-safe flight solution that can perform the same four controllable degrees-of-freedom flight as a standard multirotor even when a single thruster fails. The new solution employs a novel multirotor platform known as the T 3 -Multirotor and utilizes a distinctive strategy of actively controlling the center of gravity position to restore the controllable degrees of freedom. A dedicated control structure is introduced, along with a detailed analysis of the dynamic characteristics of the platform that change during emergency flights. Experimental results are provided to validate the feasibility of the proposed solution.

A Method for Monitoring the Condition of Rotor Windings in Induction Motors during Startup Based on Stator Current

Abstract—At present, one of the most effective methods for detecting dangling bars in squirrel-cage rotor windings of induction motors operating under severe starting conditions is the spectral analysis of stator current in a steady-state operation mode. The existing methods of testing in starting modes are not sensitive enough or their study has not been completed, although it is precisely such methods that allow diagnostics of machines that cannot be inspected in the steady-state operation mode. The purpose of this article is to develop a method for monitoring the state of rotor windings in induction motors operating under severe starting conditions based on the stator current in the starting mode, which is an urgent task. The studies were carried out both on digital models of an induction motor, developed in the Ansys software package, and on an experimental stand with a low voltage supplied to a low-voltage motor to increase the duration of its start. Signal processing is performed in the Matlab software package using the short-time Fourier transform. It is shown that only in the presence of a broken rotor bar, the amplitude of the harmonic component of the order coinciding with the number of motor pole pairs sharply increases at the lower side frequency; this indicates the presence of damage. It is shown that the developed technique for monitoring the condition of rotor windings in induction motors operating under severe starting conditions is more sensitive to broken rotor bars than the existing methods; this makes it possible to timely detect damage to rotor windings and prevent sudden failures of induction motors.

Comparative study of self tuning, adaptive and multiplexing FTC strategies for successive failures in an Octorotor UAV

This paper presents three fault-tolerant control (FTC) strategies for a coaxial octorotor unmanned aerial vehicle (UAV) regarding motor failures. The first FTC is based on a control mixing strategy which consists of a set of control laws designed offline, each one dedicated to a specific fault situation. The second FTC, a robust adaptive sliding mode control allocation is presented, where the control gains of the controller are adjusted online in order to redistribute the control signals among the healthy motors in order to stabilize the overall system. The third FTC strategy is a new strategy proposed in this article, which is based on a self-tuning sliding mode control (STSMC) where the control gains are readjusted based on the detected error to maintain the stability of the system. Multiple indoor experiments on an octorotor UAV are conducted to show and compare the effectiveness and the behavior of each FTC scheme after successive faults are injected. More specifically, we inject complete actuator’s failures into the top four motors of our octorotor. Every strategies show good fault tolerance results, although the control mixing method performs slightly better overall while the adaptive method performs slightly worse. However, the control mixing method requires a huge design effort to take into account as much situations as possible, while the adaptive method and the STSMC only require to determine a few gains. The adaptive method do not need fault detection to operate, but it thus does not provide information on the system’s health without an additional fault identification and diagnosis mechanism, while both the control mixing method and the STSMC provide such information.

Testing the stability of 'Default' motor and auditory-perceptual rhythms-A replication failure dataset.

Several studies have found that the motor rhythms that individuals produce spontaneously, for example during finger tapping, clapping or walking, are also rated perceptually as ‘very comfortable’ to listen to. This motivated proposal of the Preferred Period Hypothesis, suggesting that individuals have a characteristic preferred rhythm, that generalizes across perception and production.However, some of the experimental procedures used previously raise two methodological concerns: First, in many of these studies, the rhythms used for assessment of participants’ Perceptual Preferred Tempo (PPT) were tailored specifically around each participant's personal Spontaneous Motor Tempo (SMT). This may have biased results toward the central rhythm used, artificially increasing the similarity between spontaneous motor and auditory perceptual preferences. Second, a key prediction of the Preferred Period Hypothesis is that the same default rhythms are repeatedly found within-subject. However, measures of consistency are seldom reported, and increased within-subject variability has sometimes been used to exclude participants.The current study was an attempt to replicate reports of a correspondence between motor and perceptual rhythms, and closely followed previous experimental protocols by conducting three tasks: SMT was evaluated by instructing participants to tap ‘at their most comfortable rate’; PPT was assessed by asking participants to rate a 10 different rhythms according to how ‘comfortable’ they were; and motor-replication of rhythms was assessed using a Synchronization-Continuation task, over a wide range of rhythms.However, in contrast to previous studies, for all participants we use the same 10 perceptual rhythms in both the PPT and Synchronization-Continuation task, irrespective of their SMT. Moreover, we assessed and report measures of within- and between-trial consistency, in order to evaluate whether participants gave similar rating and produced similar motor rhythms across multiple sessions throughout the experiment.The data presented here fail to show any correlation between motor and perceptual preferences, nor do they support improved synchronization-continuation performance near an individual's so-called SMT or PPT. Rather, they demonstrate substantial within-subject variability in the spontaneous motor rhythms produced across repeated sessions, as well as their subjective rating of perceived rhythms. This report accompanies our article “Spontaneous and Stimulus-Driven Rhythmic Behaviors in ADHD Adults and Controls”[1], and provided motivation and insight for modifying the procedures used for SMT and PPT evaluation, and their interpretation.

Automated Outlier Detection for Electrical Motors and Transformers

Electrical appliances most commonly consist of two electrical devices, namely, electrical motors and transformers. Typically, electrical motors are normally used in all sort of industrial purposes. Failures of such motors results in serious problems, such as overheat, shut down and even burnt, in their host systems. Thus, more attention have to be paid in detecting the outliers. In a similar way, to avoid the unexpected power reliability problems and system damages, the prediction of the failures in the transformers is expected to quantify the impacts. By predicting the failures, the lifetime of the transformers increases and unnecessary accidents is avoided. Therefore, this paper presents the detection of the outliers in electrical motors and failures in transformers using supervised machine learning algorithms. Machine learning techniques such as Support Vector Machine (SVM), Random Forest (RF) and regression techniques like Support Vector Regression (SVR), Polynomial Regression (PR) are used to analyze the use cases of different motor specifications. Evaluation and the efficiency of findings are proved by considering accuracy, precision, F-measure, and recall for motors. Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Square Error (RMSE) and R-squared Error (R2) are considered as metrics for transformers. The proposed approach helps to identify the anomalies like vibration loss, copper loss and overheating in the industrial motor and to determine the abnormal functioning of the transformer that in turn leads to ascertain the lifetime. The proposed system analyses the behaviour of the electrical machines using the energy meter data and reports the outliers to users. It also analyses the abnormalities occurring in the transformer using the parameters involved in the degradation of the paper-oil insulation system and the voltage of operation as a whole leads to the predict the lifetime.

Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium

Juvenile neuronal ceroid lipofuscinosis (JNCL, aka. juvenile Batten disease or CLN3 disease) is a lysosomal storage disease characterized by progressive blindness, seizures, cognitive and motor failures, and premature death. JNCL is caused by mutations in the Ceroid Lipofuscinosis, Neuronal 3 (CLN3) gene, whose function is unclear. Although traditionally considered a neurodegenerative disease, CLN3 disease displays eye-specific effects: Vision loss not only is often one of the earliest symptoms of JNCL, but also has been reported in non-syndromic CLN3 disease. Here we described the roles of CLN3 protein in maintaining healthy retinal pigment epithelium (RPE) and normal vision. Using electroretinogram, fundoscopy and microscopy, we showed impaired visual function, retinal autofluorescent lesions, and RPE disintegration and metaplasia/hyperplasia in a Cln3 ~ 1 kb-deletion mouse model [1] on C57BL/6J background. Utilizing a combination of biochemical analyses, RNA-Seq, Seahorse XF bioenergetic analysis, and Stable Isotope Resolved Metabolomics (SIRM), we further demonstrated that loss of CLN3 increased autophagic flux, suppressed mTORC1 and Akt activities, enhanced AMPK activity, and up-regulated gene expression of the autophagy-lysosomal system in RPE-1 cells, suggesting autophagy induction. This CLN3 deficiency induced autophagy induction coincided with decreased mitochondrial oxygen consumption, glycolysis, the tricarboxylic acid (TCA) cycle, and ATP production. We also reported for the first time that loss of CLN3 led to glycogen accumulation despite of impaired glycogen synthesis. Our comprehensive analyses shed light on how loss of CLN3 affect autophagy and metabolism. This work suggests possible links among metabolic impairment, autophagy induction and lysosomal storage, as well as between RPE atrophy/degeneration and vision loss in JNCL.

Fundamental Frequency Suppression for the Detection of Broken Bar in Induction Motors at Low Slip and Frequency

Broken rotor bar (BRB) is one of the most common failures in induction motors (IMs) these days; however, its identification is complicated since the frequencies associated with the fault condition appear near the fundamental frequency component (FFC). This situation gets worse when the IM slip or the operation frequency is low. In these circumstances, the common techniques for condition monitoring may experience troubles in the identification of a faulty condition. By suppressing the FFC, the fault detection is enhanced, allowing the identification of BRB even at low slip conditions. The main contribution of this work consists of the development of a preprocessing technique that estimates the FFC from an optimization point of view. This way, it is possible to remove a single frequency component instead of removing a complete frequency band from the current signals of an IM. Experimentation is performed on an IM operating at two different frequencies and at three different load levels. The proposed methodology is compared with two different approaches and the results show that the use of the proposed methodology allows to enhance the performance delivered by the common methodologies for the detection of BRB in steady state.

Isotonic boosting classification rules

In many real classification problems a monotone relation between some predictors and the classes may be assumed when higher (or lower) values of those predictors are related to higher levels of the response. In this paper, we propose new boosting algorithms, based on LogitBoost, that incorporate this isotonicity information, yielding more accurate and easily interpretable rules. These algorithms are based on theoretical developments that consider isotonic regression. We show the good performance of these procedures not only on simulations, but also on real data sets coming from two very different contexts, namely cancer diagnostic and failure of induction motors.

Total cost optimization of submersible irrigation pump maintenance using simulation

PurposeThe unpredictable failure of submersible pump (SP) in groundwater irrigation systems has considerable negative economic consequences. The purpose of this paper is to develop a total cost minimization model that aims to optimize maintenance actions for SP. It reports on simulation-based stochastic scenario analysis for evaluating total cost of maintenance.Design/methodology/approachStochastic simulation modeling has been performed for failure of pump motor and corresponding maintenance. Five alternative scenarios were compared for total cost over 15 years starting with empirical data from a northern Ethiopian site. Downtime probabilities and spare part supply uncertainty have been considered in the mathematical model. The model is also validated using multiple ways.FindingsThe scenario comparisons indicate that despite the challenges of accessing SP doing one motor rewinding for each purchased pump system upon failure (preferably with shorter supply lead time and variability) seems to result in lowest overall costs for the time horizon considered.Practical implicationsThe model should help to make informed practical decision regarding planning and management of SP failure systems in a developing economy context. This should, therefore, lead to better revenue for smallholder farmers and improved food security in similar context.Originality/valueThere are limited number of publications that consider the life cycle costs with stochastic analysis when it comes to maintenance of SPs. To the best of the authors’ knowledge, no paper has previously directly addressed maintenance cost optimization for SP in irrigation. The study could be used to develop more sophisticated stochastic models with more efficient algorithms and consideration of additional sources of stochasticity for such system.

Application of Photoelectric Sensor in Vehicle Power Control System

Due to its characteristics of using clean electric energy and bringing no damage to the environment, electric vehicles (EVs) have become a new developmental direction for the automotive industry. Its reliability issues have also attracted the attention of experts and professionals. In the field of automotive power control, from the perspective of motor control, this study uses the photoelectric sensors (PSs) as the research objects and elaborates on the measurement principles of motor speed with PSs. Meanwhile, a diagnosis scheme is proposed for various faults in the measurement. Among them, the measurement speed is converted by the photoelectric signal, and the measured waveform is amplified. In the fault detection process, the Radial Basis Function (RBF) artificial neural network (ANN) is analyzed. By using this method, the difference in the motor speed detected by the sensor is calculated to determine the cause of the failure. The test uses the least-square method to compare the tested motor speed with the actual motor speed. The results show that PSs can measure the motor speed of EVs. As for the motor failures, the mean square errors (MSEs) of motor speeds generated by different faults are compared to determine the fault points according to the speed changes. In addition, the cause of motor failure can be determined by the real-time calculation of the speed differences. The above tests fully prove the effectiveness of measuring the speed of electric motors by PSs; therefore, PSs have broad application prospects in vehicle power control systems.

Analysis of the Stability of quadcopter and Control using PID controller

A UAV is an avion which fly without a human pilot which can be controlled by autopilot hardware. In this work, a type of aerial vehicle called quadcopter is considered which is very agile and unstable. A helicopter can be lifted by aerodynamic principle acting upon wings but quadcopter can't lift like helicopter any one of the motor failure or speed of the four motor mismatches will lead to a severe accident. As a result, it’s highly challenging for a human to control the flying quadcopter by controlling every motor directly, for this reason, they move for classic piloting method to achieve extreme reaction speed and attention. The scope of this paper is to develop an autonomous quadcopter using a PID controller which has a capacity of stable flying in the air with the help of using a microcontroller-based control mechanism. That can be done by measuring Euler angles to produce a control signal to the quadcopter to control its position and velocity. The Quadcopter is designed to be small enough so that cost would be minimized.

Evaluation of Failure Factors of a Small-Scale Motor in Laboratory Testing

The purpose of this study is to investigate and identify the failure of a small-scale motor in static tests and provide a solution to prevent it. The small-scale motor in this research has four SRM segments that are modeled on the internal ballistics of the shuttle booster motor and the construction of the Arian5 booster. First, a summary of the factors affecting the failure of solid rocket motors is presented, and then, the small-scale motor design and its prediction of ballistic performance are discussed. Following is the success of the first test and the failure of the second and third tests of the motor and its results. In order to evaluate the causes of second and third motor failure in static testing, the possible causes of the motor failure phenomenon are discussed, and finally, the main cause of motor failure is identified. The most common cause of failure in this project was the human error in defining the assembly of the throat parts and due to the closure of the combustion path.

A framework for electrified propulsion architecture and operation analysis

PurposeThe purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The intent for these evaluations was to account for varying operation strategies and to support architectural design space decisions, at the conceptual design stages, rather than single-point design solutions.Design/methodology/approachTo this end, main propulsion subsystems were categorized into energy, power and thrust sources. Two types of matrices, namely, the property and interdependency matrices, were created to describe the relationships and power flows among these sources. These matrices were used to define various electrified propulsion architectures, including, but not limited to, turboelectric, series-parallel and distributed electric propulsion configurations.FindingsAs a case study, the matrices were used to generate and operate the distributed electric propulsion architecture of NASA’s X-57 Mod IV aircraft concept. The mission performance results were acceptably close to the data obtained from the literature. Finally, the matrices were used to simulate the changes in the operation strategy under two motor failure scenarios to demonstrate the ease of use, rapidness and automation.Originality/valueIt was seen that this new framework enables rapid and analysis-based comparisons among unconventional propulsion architectures where solutions are driven by requirements.

Detection of liner surface defects in solid rocket motors using multilayer perceptron neural networks

Debonding problems along the propellant/liner/insulation interface are a critical point to the integrity and one of the major causes of structural failures of solid rocket motors. Current solutions are typically restricted to methods for assessing the integrity of the rocket motors structure and visually inspecting their components. In this context, this paper presents an improved algorithm to detect liner surface defects that may compromise the bonding between the solid propellant and the insulation. The use of Local Binary Patterns (LBP) provides a structural and statistical approach to texture analysis of liner sample images. Along with color information extraction, these two methods allow the representation of image pixels by feature vectors that are further processed by a Multilayer Perceptron (MLP) neural network classifier. The MLP neural network analyzes liner sample images and classifies each pixel into one of three classes: non-defect, foreign object, and defect. Several tests were executed varying different parameters to find the optimal MLP configuration, and as a result, the best classification accuracy of 99.08%, 90.66%, and 99.48% was achieved for the corresponding classes. Moreover, the defect size estimate showed that the MLP classifier correctly identified defects less than 1 mm long, with a relatively small number of training examples. Positive results indicate that the algorithm can identify liner surface defects with a performance similar to human inspectors and has the potential to assist or even automate the liner inspection process of solid rocket motors.

Pendeteksian Misalignment Menggunakan Multi Level Transformasi Wavelet Haar dan Coiflet pada Motor Induksi

Currently induction motors are widely used in industry due to strong construction, high efficiency, and cheap maintenance. Machine maintenance is needed to prolong the life of the induction motor. As studied, bearing faults may account for 42% -50% of all motor failures. In general it is due to manufacturing faults, lack of lubrication, and installation errors. Misalignment of motor is one of the installation errors. This paper is concerned to simulation of discrete wavelet transform for identifying misalignment in induction motor. Modelling of motor operation is introduced in this paper as normal operation and two variations of misalignment. For this task, haar and coiflet discrete wavelet transform in first level until fifth level is used to extract vibration signal of motor into high frequency of signal. Then, energy signal and other signal extraction gotten from high frequency signal is evaluated to analysis condition of motor. The results show that haar discrete wavelet transform at thirth level can identify normal motor and misalignment motor conditions well

Experimental Determination of Diagnostic Signs of Damage to the Rotor Windings of High-Voltage Power Plant Motors in Startup Mode

Induction electric motors are widely used as drives of various mechanisms in power engineering and industry. Their failure can lead to costly repairs, to a reduction in power, or, for example, to a complete shutdown of a power plant unit. One of the reasons for the failure of high-voltage induction motors operating under severe starting conditions is damage to the squirrel-cage rotor winding. Existing methods for monitoring the breakage of the winding bars of such electric motors are ineffective due to the peculiarities of their operating modes. Therefore, monitoring the condition of the bars of high-voltage motors at startup and searching for diagnostic signs is an urgent task. Initially, the studies were carried out with a model of a high-voltage induction motor, developed in the ANSYS software package. To confirm the results obtained for a real motor, research has also been conducted on the developed experimental bench. The recorded signals were processed based on the method of short-time Fourier transform in the MatLab environment. In the course of the study, it was shown that, in the presence of bar breaks, the spectrum of an induction motor exhibits sharply increased amplitudes of harmonic components of the dummy rotor winding at the lower side frequencies of the first orders; this confirms the possibility of using external magnetic field signal at startup to detect the presence of bar breaks in the squirrel-cage rotor winding of high-voltage induction motors with heavy prolonged starts.

Calculation of Inductive Resistances of Asynchronous Motor Windings at Rotor Eccentricity

In this paper, we propose a method for calculating the inductive resistances of asynchronous motor windings at rotor eccentricity. The eccentricity results from the displacement of the rotor axis relative to the axis of the stator bore and is accompanied by an uneven air gap. It does not lead to an immediate failure of the asynchronous motor, but is accompanied by a change in almost all electromechanical characteristics and increased energy consumption. In addition, the tension between the stator and the rotor increases and leads to an increase in the air gap unevenness and the subsequent rotor touching of the stator, i.e., the motor output out of service. Consequently, the detection of the rotor eccentricity at the early occurrence stages is an important problem. This requires a mathematical model of a three-phase asynchronous motor with the rotor eccentricity. For such a model, it is necessary to determine the inductive resistances of all motor windings. We propose magnetic flux schemes through the stator phase windings and the short-circuited inductor rotor winding to calculate the inductive resistances. We also propose to determine the inductive resistances using the zero and first members of the series of the average specific conductivity of the air gap obtained by expanding it in the Fourier series.

Study on the Fire Risk in Locked-Rotor Condition of Single-Phase Induction Motor

In this paper, the fire risk of a single-phase induction motor under a locked-rotor condition is described. In general, motor failure occurs in the locked-rotor condition owing to poor rotation of the rotor. Large inrush current flows when a motor starts, which is approximately 2–15 times larger than the rated current. In a single-phase induction motor under the locked-rotor condition, a large current that corresponds to the inrush current flows continuously through the stator winding. Such an overcurrent rises the temperature inside the stator winding, and thus the insulating material may catch fire. In this study, the restrained operating condition of the single-phase induction motor was simulated. Further, the degree of the overcurrent and temperature rise in the stator winding was measured. The experimental results, confirmed that the overcurrent was seven times larger than the rated current and the fire commenced at a temperature of approximately 300 ℃ inside the stator winding.