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In this article, two methods for broken bar detection in induction motors are considered and tested using data collected from the LIAS laboratory at the University of Poitiers. The first approach is Motor Current Signature Analysis (MCSA) with Convolutional Neural Networks (CNN), in which measurements have to be processed in the frequency domain before training the CNN to ensure that the resulting model is physically informed. A double input CNN has been introduced to perform a 100% detection regardless of the speed and load torque value. A second approach is the Principal Components Analysis (PCA), in which the processing is undertaken in the time domain. The PCA is applied on the induction motor currents to eventually calculate the Q statistic that serves as a threshold for detecting anomalies/faults. Even if obtained results show that both approaches work very well, there are major differences that need to be pointed out, and this is the aim of the current paper.

This paper aims at achieving real-time optimal speed estimation for an induction motor using the Extended Kalman filter (EKF). Speed estimation is essential for fault diagnosis in Motor Current Signature Analysis (MCSA). The estimation accuracy is obtained by exploring the noise covariance matrices estimation of the EKF algorithm. The noise covariance matrices are determined using a modified subspace model identification approach. In order to reach this goal, this method compares an estimated model of a deterministic system, derived from available input–output datasets (using voltage–current sensors), with the discrete-time state-space representation used in the Kalman filter equations. This comparison leads to the determination of model uncertainties, which are subsequently represented as noise covariance matrices. Based on the fifth-order nonlinear model of the induction motor, the rotor speed is estimated with the optimized EKF algorithm, and the algorithm is tested experimentally.

In this article, we propose to determine the dynamic model of a squirrel-cage induction motor from a reduced amount of information. An adaptive observer is also built from this model in order to obtain a speed estimation and to perform rotor fault monitoring by Tacholess Order Tracking (TOT). We also propose a generalization of the notion of angular sampling in order to adapt to this type of defect. The procedure is validated in the laboratory on a test bench dedicated to the study of rotor bar defects.

This article presents a mechanical fault diagnosis methodology in synchronous machines using only a single current measurement in variable speed conditions. The proposed methodology uses order tracking in order to sample the analysis signal as a function of the rotor angle. The spectrum of the signal is then independent of speed and it could be employed in frequency analysis. Order tracking is usually applied using rotor position measurement. In this work, the proposed method uses one current measurement to estimate the position as well as the analysis signal (rotation speed). Furthermore, a statistical approach is used to create a complete diagnosis protocol. At variable speed and with only one current measurement the diagnosis is challenging. However, order tracking will allow simpler analysis. The method is proved in simulations and experimental set-up.

The concept of a digital twin is increasingly appearing in industrial applications, including the field of predictive maintenance. A digital twin is a virtual representation of a physical system containing all data available on site. This paper presents condition monitoring of ventilation systems through the digital twin approach. A literature review regarding the most popular system faults is covered. The motor current signature analysis is used in this research to detect system faults. The physical system is further described. Then, based on the free body diagram concept and Newton’s second law, the equations of motion are obtained. Matlab/Simulink software is used to build the digital twin. The Concordia method and the Fast Fourier Transform analysis are used to process the current signal, and physical and numerical system current measurements are obtained and compared. In the final step of the modeling, specific frequencies were adjusted in the twin to achieve the best simulation. In addition, a statistical approach is used to create a complete diagnostic protocol.

The paper presents tools to model low speed airflow coming from a turbulent machine. This low speed flow have instabilities who generate noise disturbances in the environment. The aim of the study proposed in this paper, is the using of cyclostationary tools with audio signals to model this airflow and detect the noisy frequencies to eliminate this noise. This paper also deals with the extraction in real time of the frequency corresponding to the noise nuisance. This extraction makes it possible to build a software sensor. This software sensor can be used to estimate the air flow rate and also to control a future actuator which will reduce the intensity of the noise nuisance. This paper focuses on the characteristic of the sound signal (property of cyclostationarity) and on the development of a software sensor. The results are established using an experimental setup representative of the physical phenomenon to be characterised.

The paper deals with software sensors which facilitates the diagnosis of electrical machines in non-stationary operating conditions. The technique targeted is order tracking for which different techniques exist to estimate the speed and angle of rotation. However, from a methodological point of view, this paper offers a comparison of several methods in order to evaluate their performance from tests on a test bench. In addition, to perform the tests, it is necessary to initialize the different methods to make them work correctly. In particular, an identification technique is proposed as well as a way to facilitate initialization. The example of this paper is that of a synchronous generator. Angular sampling allows the spectrum to be stationary and the interpretation of a possible defect. The realization of the angular sampling and the first diagnostic elements require the knowledge of two fundamental quantities: the speed of rotation and the angular position of the shaft. The estimation of the rotation speed as well as the estimation of the angular position of the shaft are carried out from the measurement of an electric current (or three electric currents and three voltages). Four methods are proposed and evaluated to realize software sensors: identification technique, PLL (Phase Locked Loop), Concordia transform and an observer. The four methods are evaluated on measurements carried out on a test bench. The results are discussed from the diagnosis of a mechanical fault.

In order to reveal the complete topology of unsteady coherent flow structures the instantaneous measurement of the 3D velocity field is being of the great interest in fluid mechanic. Several different methods were proposed to achieve a 3D version of the technique (scanning light sheet, holography, 3D PTV). We aimed in our study to develop a 3D technique than enables to obtain the 3D kinematic field of an impinging jet by using 2D measurements. In this study and in order to validate the proposed technique [1], the tomographic particle image velocimetry technique has been applied to time resolved PIV recordings. The first step before the validation was to study the vortex shedding phenomena between the jet exit and the slotted plate. The experiments were performed at a Re = 4458 with an initial velocity U 0 =7m/s using three cameras Phantom V711 and a Nd: YLF LDY 300 Litron laser. In the present study, we analyzed the coherent structures organization by a 3D-velocity visualization. Both mean and fluctuating part of velocity were analyzed for several positions in z. The results has shown that a couple of vortex rolls are created downstream the flow at y/H=2.

Impinging jets which interact with sharp edges like slotted plates can be found in ventilation and air conditioning systems. In some cases, these configurations can be a source of desirable sounds like in musical instruments. However, they can be a source of noise in other applications such as air conditioning systems. Thus in order to reduce the noise produced from such configurations a more profound study of the flow dynamics should be implemented. All previous studies of impinging jets on a slotted plate were done in 2D. Accordingly, the objective of the present study was to reconstruct the studied volume by combining stereoscopic PIV measurements and the POD method. Consequently, an experimental set up has been developed and implemented in order to generate a flow that hits a slotted plate. On the other side, the PIV technique was used in order to study the dynamics of such a flow. The kinematic fields of twenty two parallel planes are measured by means of stereoscopic PIV. Afterwards, the analysis of the most energetic modes was obtained by the application of the snapshot POD on the kinematic fields obtained by POD. The results showed that the reconstruction of each of the planes needed only three first three modes. The reconstructed volume is obtained by an interpolation of the reconstructed planes which were phased by a trigger signal. The analysis of the vortex structures were done by the application of several vortex detection criteria.

This work is supported by a company wishing to develop new products in the field of energy monitoring in industry. It concerns the real-time estimation of the electrical consumption of an asynchronous motor without electrical measurement. The challenge consists of estimating the characteristic quantities of the motor (speed, torque, powers, efficiency) with only one vibratory measurement, information on the nameplate and commercial documentation available online. To obtain a real-time estimate, traditional FFT analysis is replaced by a PLL initially designed for power grid analysis. So, the second challenge is to modify this PLL for use with vibratory measurement characterized by a low signal-to-noise ratio, amplitude variations and a non-stationary behavior. A complete design and experimental tests are presented to validate the proposed approach.