Induction motor mechanical defect diagnosis using DWT under different loading levels

The information extraction capability of the widely used signal processing tool, FFT for diagnosing induction machines, is commonly used at a constant load or at different levels. The loading level is a major influencing factor in the diagnostic process when the coupled load and the machine come with natural mechanical imperfections, and at a low load, the mechanical faults harmonics are strongly influenced. In this context, the main objective of this work is the detection of the mechanical faults and the study of the effect of the loading level on the induction motor diagnostic process. We have employed a diagnosis method based on discrete wavelet transform (DWT) for the multi-level decomposition of stator current and extracting the fault’s energy stored over a wide frequency range. The proposed approach has been experimentally tested on a faulty machine with dynamic eccentricity and a shaft misalignment for three loading levels. The proposed method is experimentally tested and the results are provided to verify the effectiveness of the fault detection and to point out the importance of the coupled load

Remote machine condition monitoring based on power supply measurements

The most widely used rotating machines in the industry are three phase alternative current (AC) induction machines. With the advances in variable speed drive (VSD) technology, they have become even more reliable than their direct current (DC) counterpart. However, inevitably these motors soon begin to fail with time due to mechanical, electrical or thermal stress hence the need for condition monitoring (CM). Condition monitoring systems help keep machines running productively by detecting potential equipment failures before it actually fails. Many condition monitoring methods exist on the market including vibration monitoring; acoustic emission monitoring, thermal monitoring, chemical monitoring, current monitoring but most of these methods require additional sensors and expensive data acquisition system on top of a specialise software tool. This all increases the cost of ownership and maintenance. For more efficient monitoring of induction motor drive systems, this research investigates an innovative remote monitoring system using existing data available in AC drives based on AC motor operating process. This research uses standard automation components already present in most automated control systems. A remote data communication platform is developed, allowing access to the control data remotely over a wireless network and internet using PLC and SCADA system. Remote machine condition monitoring is not a new idea but its application to machine monitoring based on power supply parameters indirectly measured by an inverter is new. To evaluate the basic performance of the platform, the monitoring of shaft misalignment, a typical fault in mechanical system is investigated using an in-house gearbox test rig. It has resulted in a model based detection method based on different speed and load settings against the motor current feedback read by the inverter. The results have demonstrated that the platform is reliable and effective. In addition the monitoring method can be employed to detect and diagnose different degrees of misalignment in real time. This dissertation has major contributions to knowledge which includes: Understanding of real life machine condition monitoring problems for this application, including use of wireless sensor, communication over Industrial Ethernet and network security. The use of standard automation components (PLC and SCADA) in machine condition monitoring. MSc Research (Engineering) Thesis x An improved gearbox test rig platform which has the capability of remote control, acquiring and transferring data for monitoring induction machine drive system. The presented work shows that any machine using automated components such as PLC and SCADA and incorporating motor drive systems and other actuators has the potential to use the automated components for control, condition monitoring and reporting but this will require more tests to be done using the proposed platform

Design and Fabrication of a Gear Box Motor Current Analysis System

To achieve reliable and cost effective diagnosis, Motor current signature analysis is used to investigate the use of an induction motor as a transducer to indicate the faults in multistage gearbox via analyzing supply parameters such as phase current and instantaneous power. In gearboxes, load fluctuations on the gearbox and gear defects are two major sources of vibration. Further at times, measurement of vibration in the gearbox is not easy because of the inaccessibility in mounting the vibration transducers. This analysis system can be used for measuring the characteristics for a perfectly working gearbox and use the data as a standard for measuring faults and defects in other gearboxes. The objective of this paper is to design and fabricate a gearbox motor current analysis system at different gear operations for a constant load. Steady load conditions on the gearbox are tested for current signatures during different gear operations. The motor current analysis system can be used further to specify mainly faults in the gear, misalignment of meshed gears, and loss of contact of the gears

Investigation of Reductions in Motor Efficiency and Power caused by Stator Faults when operated from an Inverter Drive under Open Loop and Sensorless Vector Modes

The introduction of Variable Speed Drives (VSD) motor driven systems in industry is driven by the desire to increase motor efficiencies in plant. The efficiency savings are usually determined by initial energy assessments which consider factors such as the motor load type and operating conditions where the motor actual load may also be measured. However, once the system is installed and in operation, the designed-in energy efficiency of these systems may remain unchecked throughout the lifetime of the installation. Efficiency reductions may be caused by mechanical or electrical degradation of equipment that could remain undetected by the drive or user whilst the equipment appears to operate as normal. On larger systems, the financial cost of reduced efficiency can be significant. The aim of this paper is to simulate minor deteriorations in the operating conditions of a standard motor controlled from a VSD and ascertain if the worsening condition can be detected at an early stage. The deterioration in motor condition will be small enough to remain undetected by the VSD and not cause a drive fault. This paper also reviews the effect of the introduced motor imbalance on motor efficiency and introduces power factor measurement methods which can be a useful indicator of increased operating costs for equipment. Test results from the two drive operating modes of Volts/Hertz (v/f) and Sensorless Vector (SV) are compared. This is to determine if there is any noticeable difference in the measurements obtained for efficiency and power factor between drive operating modes

Diagnosis of broken bar fault in three-phase induction motors using fibre bragg grating strain sensors assisted by an algorithm

Mestrado de dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáIn this study, we developed an algorithm for identifying failures caused by broken bars in the rotors of three-phase induction motors through the analysis of their dynamic deformation using fibre optic Bragg gratings (FBGs) as sensing elements. The analysis of dynamic deformation enables the detection and diagnosis of various mechanical faults, such as misalignment, imbalance, bearing failures, and mechanical looseness. Furthermore, it allows for the identification of electrical faults, such as fractures or cracks in the rotor rings or bars To measure the dynamic deformation, we employed FBG-based sensors known for their key features, including high multiplexing capability, electromagnetic radiation immunity, and long-distance operation. Experimental tests were conducted on a small-scale induction motor (3 HP) to validate the method and explore its applicability to medium and large-scale machines. The motor was powered by two different supply sources: the utility power grid and a controled power sources, under load conditions of 75% and 100% of the rated load. During the tests, we used a rotor without any bar defects and subsequently a rotor with a broken bar. The presence of a broken bar was successfully identified under both load conditions and across all two power supply sources. The fault caused by the broken bar in the rotor was detected in two frequency regions obtained from the three sets of experiments. The first region was centred around the mechanical rotational frequency of the rotor, while the second region was approximately twice the electrical frequency of the power supply. The system demonstrated high sensitivity with a good signal-to-noise ratio and showcased advantages over conventional methods and sensors commonly used for identifying broken bar faults in induction motors.Neste estudo, desenvolvemos um algoritmo para identificar falhas em barras quebradas no rotor de motores de indução trifásicos por meio da análise da deformação dinâmica do estator usando grades de Bragg em fibras ópticas (FBGs) com assitência de um algoritmo. Essa análise possibilita a detecção e o diagnóstico de várias falhas mecânicas, como desalinhamento, desbalanceamento e folga mecânica. Além disso, permite a identificação de falhas elétricas, como fraturas ou rachaduras nos anéis ou barras do rotor. Para medir a deformação dinâmica, empregamos sensores baseados em FBG conhecidos por suas principais características, incluindo alta capacidade de multiplexação, imunidade à radiação eletromagnética e operação a longa distância. Testes experimentais foram conduzidos em um motor de indução em pequena escala (3 HP) para validar o método e explorar sua aplicabilidade em máquinas de médio e grande porte. O motor foi alimentado por duas fontes de alimentação diferentes: a rede elétrica de utilidade pública e por uma fonte controlada, sob condições de carga de 75% e 100% da carga nominal. Durante os testes, utilizamos um rotor sem defeitos no rotor e, posteriormente, um rotor com uma barra quebrada. A presença da barra quebrada foi identificada com sucesso em ambas as condições de carga e em todas as duas fontes de alimentação. A barra quebrada no rotor foi detectada em duas regiões de frequência obtidas a partir dos três conjuntos de experimentos. A primeira região estava centrada em torno da frequência rotacional mecânica do rotor, enquanto a segunda região era aproximadamente o dobro da frequência elétrica da fonte de alimentação. O sistema demonstrou alta sensibilidade com uma boa relação sinal-ruído e apresentou vantagens sobre os métodos convencionais e sensores comumente usados para identificar falhas em barras quebradas em motores de indução

Electrical Signature Analysis of Synchronous Motors Under Some Mechanical Anomalies

Electrical Signature Analysis (ESA) has been introduced for some time to investigate the electrical anomalies of electric machines, especially for induction motors. More recently hints of using such an approach to analyze mechanical anomalies have appeared in the literature. Among them, some articles cover synchronous motors usually being employed to improve the power factor, drive green vehicles and reciprocating compressors or pumps with higher efficiency. Similarly with induction motors, the common mechanical anomalies of synchronous motor being analyzed using the ESA are air-gap eccentricity and single point bearing defects. However torsional effects, which are usually induced by torsional vibration of rotors and by generalized roughness bearing defects, have seldom been investigated using the ESA. This work presents an analytical method for ESA of rotor torsional vibration and an experimentally demonstrated approach for ESA of generalized roughness bearing defects. The torsional vibration of a shaft assembly usually induces rotor speed fluctuations resulting from the excitations in the electromagnetic (EM) or load torque. Actually, there is strong coupling within the system which is dynamically dependent on the interactions between the electromagnetic air-gap torque of the synchronous machine and the rotordynamics of the rotor shaft assembly. Typically this problem is solved as a one-way coupling by the unidirectional load transfer method, which is based on predetermined or assumed EM or load profile. It ignores the two-way interactions, especially during a start-up transient. In this work, a coupled equivalent circuit method is applied to reflect this coupling, and the simulation results show the significance of the proposed method by the practical case study of Electric Submersible Pump (ESP) system. The generalized roughness bearing anomaly is linked to load torque ripples which can cause speed oscillations, while being related to current signature by phase modulation. Considering that the induced characteristic signature is usually subtle broadband changes in the current spectrum, this signature is easily affected by input power quality variations, machine manufacturing imperfections and the interaction of both. A signal segmentation technique is introduced to isolate the influence of these disturbances and improve the effectiveness of applying the ESA for this kind of bearing defects. Furthermore, an improved experimental procedure is employed to closely resemble naturally occurring degradation of bearing, while isolating the influence of shaft currents on the signature of bearing defects during the experiments. The results show that the proposed method is effective in analyzing the generalized roughness bearing anomaly in synchronous motors

Fault detection and diagnosis of a multistage helical gearbox using magnitude and phase information from vibration signals

Vibration generated by a gearbox carries a great deal of information regarding its health condition. This research aims primarily on the detection and diagnosis of tooth defects in a multistage gearbox based on advanced vibration analysis. Time synchronised averaging (TSA) analysis is effective at removing noise but it is inefficient in implementation and in diagnosing different types of faults such as bearing defects other than gears. Conventional bispectrum (CB) can eliminate Gaussian noise while it preserves the signal’s phase information, however its overpopulated contents can still provide inaccurate information regarding to different types of gear faults. Recently developed modulation signal bispectrum (MSB) has the high potential to lead to the high accuracy of diagnostics of gearboxes as it more effectively characterises modulation signals such as gearbox vibrations. Therefore, the research takes MSB as the fundamental tool for analysing gearbox vibration signals and developing accurate diagnostic techniques. Firstly, it has realised that conventional techniques often ignore the effect of phase information in gearbox diagnostics. This thesis then focuses on developing CB and MSB based techniques for detecting and diagnosing of gearbox faults. Secondly, it has found that vibration responses from a multiple stage gearbox have high interferences between amplitude modulation (AM) and phase modulation (PM) which can be formalised from both gear faults and inherent manufacturing errors. However, the faults can induce wider bandwidth vibrations. Correspondingly, optimal component based schemes are also developed based on the use of MSB coherence results. Then the proposed MSB method allows an effective gearbox diagnosis using the signals in a narrower frequency band that is below twice the rotational frequency plus the highest meshing frequency amongst different gear transmission stages, being more suitable for wireless network condition monitoring systems. It has also found that the signals at resonance frequencies has a higher signal-to-noise ratio and more effective for obtaining accurate diagnosis. Also software encoder based TSA was found to be not robust and accurate due to the influences of noise and referencing components on obtaining a reliable phase signal for implementing TSA. Finally, the diagnostics carried out upon different fault cases using both CB and MSB have verified the proposed approaches can provide accurate diagnostic results, and with the new MSB based detector and estimator being more effective in differentiating between diffident fault locations for two local and one non-uniformly distributed tooth damages in a two stage helical gearbox

THE USE OF EFFICIENCY INDICATORS FOR THE DETECTION OF COMBINED MOTOR ASYMMETRY FAULTS AND THEIR EFFECTIVENESS WHEN USED ON INVERTER DRIVEN MOTOR SYSTEMS

The use of Variable Speed Drives (VSD’s) for the control of AC motor systems in industry is well established and continues to expand year-on-year. The increasing use of VSD's can be found not only in renewable energy applications such as wind turbines and tidal generators but also in transport such as motor vehicles and marine propulsion, as well as industry such as on conveyors, material processing and pumping applications. To ensure safe, reliable and efficient operation of these applications, Condition Monitoring CM is essential. Following a detailed literature review of established research on motor-driven system CM, it has been found that existing research works are more concerned with detection and identification of specific motor faults. There is a lack of research into how certain motor faults contribute to the degradation of the motor driven system efficiency. Whilst the efficiency monitoring of an AC motor system has previously been researched, being able to measure efficiency decreases caused by certain motor faults and on a VSD system operating in different control modes is not an area that has been studied previously. In fact, new European Union EU draft regulations detailing potential future legislation that may become mandatory to define the efficiency of motor driven systems fed by VSD’s has been drafted, but does not detail how these efficiencies may be measured or monitored in the field. To overcome the gap in research, this research focuses on the use of efficiency monitoring methods on a VSD-driven motor system to measure any reduction in efficiency at an early stage caused by minor motor faults. The studies are based on model simulation of a basic DOL-operated AC motor followed by experimental work on a laboratory test rig where the model simulation is translated to a VSD operating at a fixed-speed with different loads applied. This research has found that the efficiency reduction of the motor driven system under different faulty conditions can be detected using certain characteristics of the motor signals. Novel findings have also shown that the efficiency of the motor driven system can be improved by selecting different VSD operating modes. The research also shows that different VSD control techniques can help to improve the regulation of motor speed control when the motor is subjected to minor faults. These findings are important as they provide proof-of-concept for users of VSD systems who may wish to implement efficiency monitoring strategies on their VSD-operated motors with the minimum of intervention. Furthermore, simply by changing the operating strategy of the users VSD, there may be immediate efficiency benefits offered to the equipment that do not require any new hardware