Performance Of Induction Motor Research Articles

О возможности проведения контроля состояния асинхронных электродвигателей с частотно-регулируемым приводом методом спектрального анализа

One of the important tasks of current energy power industry is to increase the reliability of induction motors operation. A promising direction for monitoring their technical condition is application of methods of spectral analysis of signals. However, very little attention is paid to the diagnostic assessment of induction motors as a part of a variable frequency drive, as well as the use of frequency converters for diagnostic purposes. Therefore, the issues related to monitoring the condition of induction motors with variable frequency drives are relevant and require scientific research. The purpose of the study is experimental evaluation of the possibility to use the spectral analysis method to assess the technical condition of induction motors driven by frequency converters. The research has been carried out on AIR71A6 induction motor with a serviceable rotor winding and one broken rotor bar rotor winding. The internal magnetic field is considered as a diagnostic signal in steady-state and start-up mode. The condition has been evaluated based on the determination of harmonics in the amplitude spectrum from the dummy rotor winding. A Short Time Fourier Transform is used for signal processing. The spectra of the internal magnetic field have been obtained at start-up and in steady-state mode when the engine is fed by an autotransformer and frequency converter. A diagnostic sign of the presence of broken bars, that is an increase of harmonic amplitudes from the dummy rotor winding, manifested itself not only when the electric motor is fed by an autotransformer, but also frequency driven. Comparing the amplitudes of harmonics in the presence and absence of a frequency converter allows us to conclude that interference of the converter slightly affect the amplitudes of specific harmonics. Using the example of an internal magnetic field signal, it is shown that spectral analysis methods can be used to diagnose the induction motors condition with a variable speed drive.

Localized Bearing Fault Analysis for Different Induction Machine Start-Up Modes via Vibration Time-Frequency Envelope Spectrum.

Bearings are the most vulnerable component in low-voltage induction motors from a maintenance standpoint. Vibration monitoring is the benchmark technique for identifying mechanical faults in rotating machinery, including the diagnosis of bearing defects. The study of different bearing fault phenomena under induction motor transient conditions offers interesting capabilities to enhance classic fault detection techniques. This study analyzes the low-frequency localized bearing fault signatures in both the inner and outer races during the start-up and steady-state operation of inverter-fed and line-started induction motors. For this aim, the classic vibration envelope spectrum technique is explored in the time-frequency domain by using a simple, resampling-free, Short Time Fourier Transform (STFT) and a band-pass filtering stage. The vibration data are acquired in the motor housing in the radial direction for different load points. In addition, two different localized defect sizes are considered to explore the influence of the defect width. The analysis of extracted low-frequency characteristic frequencies conducted in this study demonstrates the feasibility of detecting early-stage localized bearing defects in induction motors across various operating conditions and actuation modes.

Analysis of a Doubly-Fed Induction Motor for Soft Start Operation based on Stator Flux Vector Control

This paper aims at analysis of an operation of a doubly-fed induction motor (DFIM). The paper mainly focuses on the soft start method for the DFIM using the conventional topology that is normally used in the case of a doubly-induction generator (DFIG). Likewise, the details about reactive power control is also discussed. With the proposed method, the DFIM can start from zero to any speed by controlling the machine-side converter (MSC). The computer simulation is performed to a 5 kW wound rotor induction motor using PLECS software. The simulation results validate that the DFIM can operate from the rest to any speed while operating only under the conventional topology.

Detection of Broken Bars in Induction Motors Operating with Closed-Loop Speed Control

Rotor bar breakage in induction motors is often detected by analysing the signatures in the stator current. However, due to the alteration of the current spectrum, traditional methods may fail when inverter-fed motors operate with closed-loop control using a cascade structure to regulate the speed. In this paper, the potential of zero-sequence voltage analysis to detect this fault is investigated, and a new index to quantify the severity of the fault based on this signal is proposed. Signals from motors operating under different control strategies and signals from motors powered from the mains are considered to verify the robustness of the proposed fault severity index. As a result, in all the analysed conditions the value of the proposed index for the healthy motor is found to be approximately 0.010, while for the faulty machine it is between 0.110 and 0.252.

Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

Induction motor drives with variable speed applications that employ vector control are quite popular nowadays because they provide strong dynamic performance and flexible speed control. By decoupling the torque-producing current components of stator current from the rotor flux, Indirect Field Oriented Control is recognized for generating excellent performance in induction motor drives. This investigation is being done to show the effectiveness of the novel FPI input-output data-trained ANFIS controller and compare the three controllers' performance in terms of load variation capabilities, motor parameter variation, and speed tracking. Consequently, a comparison of the three controllers is important to select which controller performs high in induction motor drive. Indirect Field Oriented Control of induction motor with Fractional Proportional Integral (FPI), Integer Proportional Integral (IPI), and Adaptive Neuro-Fuzzy Inference System (ANFIS) controllers are all discussed in this work along with their designs and comparative analysis. The square of error was used as a fitness function to genetically optimize the FPI and IPI controller parameters. The suggested Adaptive Neuro-Fuzzy Inference System (ANFIS) controller uses a hybrid learning approach. It is trained by the FPI controller's input-output data. Using the results of MATLAB simulations under various operating situations, the performance of the ANFIS controller was compared with FPI and IPI controllers. Because of FPI controller includes an extra parameter for adjustment, namely integration order, it performed better than IPI controller for speed control of the induction motor. According to the simulation findings, the percentage peak overshoots while employing ANFIS, FPI, and IPI controllers were 0.495 %, 12.062 %, and 14.699 % respectively. As a result, ANFIS exhibits a drastic reduction in overshoot. Additionally, with the ANFIS controlled induction motor drive, the speed achieves the required set value at 0.14 s. For no load, constant, and changing loads, the induction motor drive's performance has been examined.

Performance and Safety Improvement of Induction Motors Based on Testing and Evaluation Standards

Performance and Safety Improvement of Induction Motors Based on Testing and Evaluation Standards

Efficiency-Centered Fault Diagnosis of In-Service Induction Motors for Digital Twin Applications: A Case Study on Broken Rotor Bars

The uninterrupted operation of induction motors is crucial for industries, ensuring reliability and continuous functionality. To achieve this, we propose an innovative approach that utilizes an efficiency model-based digital shadow system for in situ failure detection and diagnosis (FDD) in induction motors (IMs). The shadow model accurately estimates IM losses and efficiency across various operational conditions. Our proposed method utilizes efficiency as the primary indicator for fault detection, while losses serve as condition indicators for fault diagnosis based on real-time motor parameters and loss sources. We introduce a bond graph as a fault diagnosis network, linking loss sources, motor parameters, and faults. This interconnected approach is the key aspect of our proposed diagnostic method and aims to be used in fault diagnosis as a general method. A case study of a broken rotor bar is used to validate the proposed method using a dataset of five motors. Among these, one motor operates without failure, while the remaining four exhibit broken rotor faults categorized as 1, 2, 3, and 4. The proposed method achieves 99.99% precision in identifying one to four defective rotor bars in IMs. Comparative analysis demonstrates good performance compared to vibration-based FDD approaches. Moreover, our methodology is computationally efficient and aligned with Industry 4.0 requirements.

Role of End-Ring Configuration in Shaping IE4 Induction Motor Performance

Role of End-Ring Configuration in Shaping IE4 Induction Motor Performance

Empirical Advancements in Field Oriented Control for Enhanced Induction Motor Performance in Electric Vehicle

Empirical Advancements in Field Oriented Control for Enhanced Induction Motor Performance in Electric Vehicle

Evaluation of a multiphase cascaded H-bridge inverter for induction motor operation

Multi-phase systems are becoming more popular for applications requiring high power and precise motor control, even if single-phase AC power is still frequently utilized in households and some enterprises. While both systems have benefits over single-phase, there are trade-offs associated with each. Because of its balanced operation and effective power transfer, the three-phase (3-Φ) system is the most widely used multi-phase system. Nevertheless, different phase values can be investigated for particular applications where reducing torque ripple and harmonic content is essential. Using odd numbers of phases (such as 5-Φ) that are not multiples of three is one method. This design has the ability to reduce torque ripple by producing a more balanced magnetic field as compared with even-numbered phases. But adding more phases also makes the system design and control circuitry more complex. Systems with five phases (5-Φ) provide a compromise between performance and complexity. Applications such as electric ship propulsion, rocket satellites, and traction systems may benefit from their use. Nevertheless, choosing a multi-phase system necessitates carefully weighing the requirements unique to each application, taking into account elements like cost, power transmission, control complexity, and efficiency. The increasing popularity of electric vehicles and renewable energy technologies has led to the need for inverters in current electric applications. Conventional inverters provide square wave outputs, which cause the drive system to become noisy and cause harmonics. Multi-phase multilevel inverters can be used to enhance inverter functioning and produce an improved sinusoidal output. This study focuses on an induction motor drive powered by a five-phase multilevel cascaded H-Bridge inverter. With less torque and current ripples in the motor rotor, the power conversion harmonics are reduced and the switching components of the inverter are under less stress. However, in comparison to traditional inverters, it does require a greater number of legs. Because the switches needed for the cascaded H-Bridge inverter are less expensive in five-phase systems, they are favoured over higher phase orders. Furthermore, the suggested inverter removes 5th order harmonics, something that is not possible with traditional inverters. A five-phase induction motor appropriate for variable speed driving applications is also suggested by this research. Lastly, utilizing pulse width modulation (PWM) converters and an FPGA controller, an experimental study is carried out to assess the dynamic performance of the suggested induction motor drive. Particular attention is paid to the In-Phase Opposition Disposition (IPD) PWM technique.

Design and Implementation of Real-Time Sensors for Three-Phase Induction Motor Performance Monitoring using Internet of Thing (IoT)

This article delves into the design and implementation of cost-effective sensors tailored for real-time monitoring of three-phase induction motor performance. The research primarily centers on the assessment of the operational effectiveness of a suite of sensors, including the PZEM-004t power sensor, MLX90614 temperature sensors, NJK-5002C rotation sensors, and ADXL345 vibration sensors, within the context of three-phase induction motor performance analysis. The monitoring system for three-phase induction motor performance is built around the ESP-32 platform, incorporating the ADXL345 vibration sensor. This article successfully presents the individual sensor performance, which was systematically evaluated through testing on a three-phase induction motor that had been meticulously designed and closely observed. The unit tests reveal that all sensors employed in the experiments exhibit an average error rate of less than 5%. When assessed as an integrated system, the three-phase induction motor performance monitoring system demonstrates robust functionality, effectively measuring critical variables such as voltage, current, power factor, temperature, vibration, and rotational speed.

Optimized Deep Belief Network for Efficient Fault Detection in Induction Motor

Numerous industrial applications depend heavily on induction motors and their malfunction causes considerable financial losses. Induction motors in industrial processes have recently expanded dramatically in size, and complexity of defect identification and diagnostics for such systems has increased as well. As a result, research has concentrated on developing novel methods for the quick and accurate identification of induction motor problems.In response to these needs, this paper provides an optimised algorithm for analysing the performance of an induction motor. To analyse the operation of induction motors, an enhanced methodology on Deep Belief Networks (DBN) is introduced for recovering properties from the sensor identified vibration signals. Restricted Boltzmann Machine (RBM) is stacked utilizing multiple units of DBN model, which is then trained adopting Ant colony algorithm.An innovative method of feature extraction for autonomous fault analysis in manufacturing is provided by experimental investigations utilising vibration signals and overall accuracy of 99.8% is obtained, which therefore confirms the efficiency of DBN architecture for features extraction.

Evaluasi Penggerak Mesin Pengolahan Tandan Kosong (EFB) dengan Menggunakan Motor Induksi di PT. Suryabumi Argo Langgeng Sumatra Selatan

The research issues include the performance of three-phase induction motors and the impact of load on three-phase induction motors. This study aims to develop a driving system for empty fruit bunches (EFB) processing machines using induction motors at PT. Suryabumi Agro Langgeng, South Sumatra. The research was conducted at PT. Suryabumi Agro Langgeng in South Sumatra, from May to June 2024. Primary data in this research were obtained through observation and interviews, while secondary data were gathered from document analysis. In the context of this research on three-phase induction motors, document analysis techniques can be used to analyze various documents such as scientific literature, technical specifications, maintenance reports, production records, or other documents related to induction motors. The research methods include system requirements analysis, system design and implementation of the driving system, and performance testing of the developed system. The results show that the use of induction motors can provide better operational efficiency in EFB processing. This research is expected to contribute positively to improving the efficiency and productivity of PT. Suryabumi Agro Langgeng's operations.

Improved performance of linear induction motors based on optimal duty cycle finite-set model predictive thrust control

Linear induction machines (LIMs) find widespread adoption in various applications, owing to their inherent advantages such as low noise, compact turning radius, and excellent climbing capability. LIMs are extensively utilized in linear metro applications. However, in practical operations, the output thrust shrinks with the increase in speed, which is attributed to end effects. This phenomenon leads to a reduction in efficiency. In addition, fluctuations in the normal force impact system stability, posing disturbances to the suspension system. To address these challenges, this paper suggests a finite-set model predictive thrust control (FS-MPTC) for a drive system employing a linear induction motor (LIM). The FS-MPTC optimizes the duty cycle for the active voltage vector and allocates the remaining period to one of the zero voltage vectors. The selected zero voltage vector reduces the switching transition between it and the active voltage vectors. The duty cycle is calculated for the six voltage vectors by incorporating the deadbeat concept and the derivative value for the electromagnetic thrust. In the prediction stage of the FS-MPTC, the computed duty cycle and the corresponding voltage vector are used simultaneously and repeated for the six voltage vectors. The cost function comprises two terms: the error between the reference thrust and predicted thrust value as the first term and the error between the rated primary flux linkage and its predicted value as the second term. The reference thrust is generated from the outer speed control loop. To validate the effectiveness of the proposed control approach, Japanese 12000 linear induction machine parameters are employed for verification. Comparative analysis of the performance between the suggested control method with the optimal duty cycle and the same process with a fixed duty cycle demonstrates superior performance when utilizing the optimal duty cycle. Finally, the proposed FS-MPTC with the optimal duty cycle offers a promising solution to enhance the operational efficiency of the LIM-based drive systems.

Automatic Switching of Three Phase Induction Motor during Fault Condition

Abstract: Three-Phase Induction Motor Automated Transition in Defective Conditions Maintaining the effective operation of three-phase induction motors is crucial in a variety of industrial contexts. However, malfunctions such as phase inconsistency, voltage drop, and overcurrent can seriously impair motor performance, leading to loss of operation and possible damage. This article introduces an automatic switching method designed to improve the fault-tolerance capacity of induction motors in order to address these issues. The system uses advanced fault detection algorithms to identify abnormal conditions quickly and enable a seamless transition to backup power or other configurations. It also incorporates preventive measures to guard against phase abnormalities and voltage variations that could harm the motor. Through simulation and real-world testing, the suggested system's dependability and effectiveness are confirmed, highlighting its potential to guarantee continuous motor running in industrial applications, a three-phase induction motor must be automatically switched on. A two-motor system a primary motor and a backup motor is shown in this study. If the primary motor fails, the backup motor is automatically turned on. Microcontroller design controls the entire switching process.

Improving Rotational Stability and Enhancing Efficiency with Variable Inertial Flywheels and Magneto-rheological Fluids

Variations in the rotational speed of a flywheel are naturally resisted by the moment of inertia. A high moment of inertia must be maintained to minimize angular velocity variations. Conversely, a significant moment of inertia makes it difficult to start spinning machines. A flywheel with a variable moment of inertia has been suggested to solve this issue. Although fluctuations between the masses' radii across the flywheel's axis may be used to approximate true inertia, the variable inertial flywheel's (VIF) control mechanisms are somewhat complex. Magneto-rheological (MR) Fluids can be utilized to avoid the complexity of the VIF. The applied device parameters determine the design and construction of the VIF system using a relatively simple control technique. To determine the relation between the semi-active VIF control system and the input parameters of a rotating electrical machine to decrease energy losses, adequate data from a VIF coupled with an induction motor (IM) system is gathered in this study. An analysis was done on the system, and the outcome showed a possible improvement in the performance of IM. This study significantly reduces power consumption and smooth speed build-up possibility for the proposed system.

Design Of Maximum Torque Per Ampere Control Method In Squirrel Cage Three-Phase Induction Motor

Improving the performance of three-phase induction motors is currently carried out by various control methods. One of them is controlling a three-phase induction motor using the Maximum Torque Per Ampere (MTPA) method. This paper focuses on the study of modeling specific motor models using the MTPA method. The purpose of the study is to prove that with the squirrel cage motor model, the speed can be increased above its rating. The MTPA method is a method of controlling a three-phase induction motor by controlling the current from the torque speed. Modeling is tested to see the responsiveness of the modeled system. The experimental results were tested using two-speed references and the system showed that MTPA control induction motors can improve the performance of three-phase induction motors. The results from the design show that the MTPA method can increase the performance of three-phase induction motors to reach 84.4%. The results of this study can be used as one way to model induction motors.

ANFIS-based optimisation for achieving the maximum torque per ampere in induction motor drive with conventional PI

This research presents an innovative approach to controlling the speed of an induction motor drive by utilizing a combination of neural networks and fuzzy inference systems (ANFIS). The study focuses on computing the rotor's magnetic flux while considering different overshoot and settling criteria for torque and motor speed. The goal is to optimize torque per ampere and generate the necessary torque. The proposed ANFIS-based torque-per-ampere control technique offers a distinctive method applicable to a static induction motor model. This method allows for an increase in stator current while maintaining flexibility and individuality in motor control strategies. It compares various motor vector control methods, specifically focusing on strategies to reduce torque ripple. These strategies include adaptive ANFIS, fuzzy logic control (FLC), and proportional-integral (PI) control. The research highlights the effectiveness of an adaptive ANFIS controller in achieving the most significant reduction in torque ripple within the induction motor system. This proposed problem identification sets the stage for exploring and developing solutions to enhance the performance and efficiency of induction motor drives.

A winding design for improving 3-phase induction motor performance

One of the most popular electric motors used today is the 3-phase induction motor, which has a sturdy design, is less expensive, and is simple to use. Improvements to the materials used in the rotor or stator of induction motors, raising the number of motor phases, and employing a 3-phase induction motor for 1-phase power are just a few of the ways the motor is now being developed to perform better. These studies are all pricey, though. The goal of this study is to determine how to enhance the motor's performance at a reasonable cost. The suggested remedy was to create a 3-phase induction motor winding with a 1-layer design that resembled a symmetrical 6-phase winding. The primary study topics were the motor's rotor speed, mechanical torque, efficiency, and winding current when it was powered by a three-phase power source. The results of the study show that, although consuming less winding current, the 3-phase induction motor with a new winding design outperforms a traditional 3-phase induction motor in terms of rotor speed, mechanical torque, and efficiency.

Practical Test on the Operation of the Three-Phase Induction Motor under Single-Phasing Fault

Single-phasing is a common problem in the three-phase electrical grid. Despite the fact that the fault occurs in one phasing, the three-phase load is affected, and therefore the load is typically turned off. The three-phase induction motor is the most commonly used in the industry; therefore, this research investigates the behavior of the three-phase induction motor under a single-phasing fault. The main aim of this paper is to answer the question, should the three-phase induction motor be turned off under a single-phasing fault? The problem is investigated theoretically and compared with practical tests to explore the parameters of the induction motor (current, stator temperature, and vibration) that are affected under healthy and single-phasing fault conditions. A practical test machine is built to test the motor behavior under single-phasing faults, where the practical experiment results are compared to those of the simulations. Despite the common recommendation under single-phasing fault is to turn off the induction motors, the preliminary results of this study show that turning off an induction motor under single-phasing can be avoided under certain operating conditions with a simple protection scheme, which is useful in some practical situations.