Motor current signal analysis using a modified bispectrum for machine fault diagnosis

This paper presents the use of the induction motor current to identify and quantify common faults within a two-stage reciprocating compressor. The theoretical basis is studied to understand current signal characteristics when the motor undertakes a varying load under faulty conditions. Although conventional bispectrum representation of current signal allows the inclusion of phase information and the elimination of Gaussian noise, it produces unstable results due to random phase variation of the sideband components in the current signal. A modified bispectrum based on the amplitude modulation feature of the current signal is thus proposed to combine both lower sidebands and higher sidebands simultaneously and hence describe the current signal more accurately. Based on this new bispectrum a more effective diagnostic feature namely normalised bispectral peak is developed for fault classification. In association with the kurtosis of the raw current signal, the bispectrum feature gives rise to reliable fault classification results. In particular, the low feature values can differentiate the belt looseness from other fault cases and discharge valve leakage and intercooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis of stator current for the diagnosis of motor drive faults from downstream driving equipment

Conserving Energy with No Watt Left Behind

Facilities managers for industrial and commercial sites want to develop detailed electrical consumption profiles of their electrical and electromechanical loads, including expensive physical plant for heating, ventilation, and air conditioning (HVAC) and equipment for manufacturing and production. This information is essential in order to understand and optimize energy consumption, to detect and solve equipment failures and problems, and to facilitate predictive maintenance of electromechanical loads. As energy costs rise, residential customers are also developing a growing interest in understanding the magnitude and impact of their electrical consumption quickly, easily, and informatively

Evaluation of saliency tracking as an alternative for health monitoring in PMSM-drives under nonstationary conditions

This paper evaluates the capability of saliency tracking to assess the health condition of permanent magnet synchronous motor (PMSM) drives operating under nonstationary conditions. The evaluated scheme is based on saliency tracking methods, which are associated to the accurate sensorless control of AC drives without zero speed limitations. In this work two representative saliency tracking architectures are evaluated: High Frequency (HF) injection, and PWM transient excitation. Although a monitoring approach based on HF injection was previously reported, a comparative study to evaluate the most representative saliency tracking schemes to assess health condition in drives was still missing. The aim of this work is to fill out this gap by evaluating and comparing two saliency-based monitoring schemes (one based on HF-injection and the other based on PWM transient excitation) to evaluate their performance in the presence of inter-turn winding faults. Simulation and experimental results are presented which confirm that both schemes offer excellent detection capabilities and that are suitable for drives operating under nonstationary conditions including standstill operation. Significant differences are also found for instance, PWM transient excitation offers improved accuracy since the approach is not affected by the inverter nonlinearities and is suitable for full-speed range applications. The main drawback here is complexity and the hardware requirements. Schemes based on HF-injection proved to be very simple and provide comparable results; however a good performance is only guaranteed for the zero-to-medium speed range applications which limit their applicability

Machine Health Monitoring and Fault Diagnosis Techniques Review in Industrial Power-Line Network

The machinery arrangements in industrial environment normally consist of motors of diverse sizes and specifications that are provided power and connected with common power-bus. The power-line could be act as a good source for travelling the signal through power-line network and this can be leave a faulty symptom while inspection of motors. This influence on other neighbouring motors with noisy signal that may present some type of fault condition in healthy motors. Further intricacy arises when this type of signal is propagated on power-line network by motors at different slip speeds, power rating and many faulty motors within the network. This sort of convolution and diversification of signals from multiple motors makes it challenging to measure and accurately relate to a certain motor or specific fault. This chapter presents a critical literature review analysis on machine-fault diagnosis and its related topics. The review covers a wide range of recent literature in this problem domain. A significant related research development and contribution of different areas regarding fault diagnosis and traceability within power-line networks will be discussed in detail throughout this chapter

Induction machine faults detection using stator current parametric spectral estimation

International audienceCurrent spectrum analysis is a proven technique for fault diagnosis in electrical machines. Current spectral estimation is usually performed using classical techniques such as periodogram (FFT) or its extensions. However, these techniques have several drawbacks since their frequency resolution is limited and additional post-processing algorithms are required to extract a relevant fault detection criterion. Therefore, this paper proposes a new parametric spectral estimator that fully exploits the faults sensitive frequencies. The proposed technique is based on the maximum likelihood estimator (MLE) and offers high-resolution capabilities. Based on this approach, a fault criterion is derived for detecting several fault types.The proposed technique is assessed using simulation signals, issued from a coupled electromagnetic circuits approach-based simulation tool for mechanical unbalance and electrical asymmetry faults detection. It is afterward validated using experiments on a 0.75-kW induction machine test bed for the particular case of bearing faults

Development of an induction motor condition monitoring test rig And fault detection strategies

Includes bibliographical references.This thesis sets out to develop an induction motor condition monitoring test rig to experimentally simulate the common faults associated with induction motors and to develop strategies for detecting these faults that employ signal processing techniques. Literature on basic concepts of induction motors and inverter drives, the phenomena of common faults associated with induction motors, the condition monitoring systems were intensively reviewed

State of the art and trends in the monitoring, detection and diagnosis of failures in electric induction motors

Producción CientíficaDespite the complex mathematical models and physical phenomena on which it is based, the simplicity of its construction, its affordability, the versatility of its applications and the relative ease of its control have made the electric induction motor an essential element in a considerable number of processes at the industrial and domestic levels, in which it converts electrical energy into mechanical energy. The importance of this type of machine for the continuity of operation, mainly in industry, is such that, in addition to being an important part of the study programs of careers related to this branch of electrical engineering, a large number of investigations into monitoring, detecting and quickly diagnosing its incipient faults due to a variety of factors have been conducted. This bibliographic research aims to analyze the conceptual aspects of the first discoveries that served as the basis for the invention of the induction motor, ranging from the development of the Fourier series, the Fourier transform mathematical formula in its different forms and the measurement, treatment and analysis of signals to techniques based on artificial intelligence and soft computing. This research also includes topics of interest such as fault types and their classification according to the engine, software and hardware parts used and modern approaches or maintenance strategies

Diagnosis of Rotor Asymmetries Faults in Induction Machines Using the Rectified Stator Current

(c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Fault diagnosis of induction motors through the analysis of the stator current is increasingly being used in maintenance systems, because it is non-invasive and has low requirements of hardware and software. Nevertheless, its industrial application faces some practical limitations. In particular, the detection of fault harmonics that are very close to the fundamental component is challenging, as in large induction motors working at very low slip, because the leakage of the fundamental can hide the fault components until the damage is severe. Several methods have been proposed to alleviate this problem, although all of them increase noticeably the complexity of the diagnostic system. In this paper, a novel method is proposed, based on the analysis of the rectified motor current. It is shown that its spectrum contains the same fault harmonics as the spectrum of the original current signal, but with a much lower frequency, and free from the fundamental component leakage. Besides, the proposed method is very easy to implement, either by software, using the absolute value of the current samples, or by hardware, using a simple rectifier. The proposed approach is presented theoretically and validated experimentally with the detection of a broken bars fault of a large induction motor.This work was supported in part by the Spanish "Ministerio de Ciencia, Innovacion yUniversidades (MCIU)," in part by the "Agencia Estatal de Investigacion (AEI)," and in part by the "Fondo Europeo de Desarrollo Regional (FEDER)" in the framework of the "Proyectos I+D+i -Retos Investigacion 2018," under Project RTI2018-102175-B-I00 (MCIU/AEI/FEDER, UE).Puche-Panadero, R.; Martinez-Roman, J.; Sapena-Bano, A.; Burriel-Valencia, J. (2020). Diagnosis of Rotor Asymmetries Faults in Induction Machines Using the Rectified Stator Current. IEEE Transactions on Energy Conversion. 35(1):213-221. https://doi.org/10.1109/TEC.2019.2951008S21322135

Diagnostic System for Asynchronous Motors and Synchronous Generators Operating in Autonomous Mode Developed through the Use of DAQ Devices and Labview Programming Environment

The paper explores the possibilities for the use of DAQ devices in developing specialised diagnostic systems for monitoring and diagnostics of electrical equipment with asynchronous electric drives and autonomous synchronous generators. The primary focus is on the construction of a system responsive to different complementary diagnostic methods, such as the spectral current- voltage analysis, Park's method, instantaneous power theories, etc. Such a system might be applied locally (discretely) and/or conjointly in a centralized equipment monitoring system with the use of the LabView platform

Application of Park's power components to the differential protection of three-phase transformers

This paper presents a new scheme for power transformers differential protection, in which the concept of the Park's instantaneous differential powers is introduced. The proposed method is able to detect winding insulation failures and to distinguish them from magnetizing inrush current transients. Experimental and simulation results are presented and discussed