Stray Flux Multi-Sensor for Stator Fault Detection in Synchronous Machines

The aim of this paper is to detect a stator inter-turn short circuit in a synchronous machine through the analysis of the external magnetic field measured by external flux sensors. The paper exploits a methodology previously developed, based on the analysis of the behavior with load variation of sensitive spectral lines issued from two flux sensors positioned at 180° from each other around the machine. Further developments to improve this method were made, in which more than two flux sensors were used to keep a good sensitivity for stator fault detection. The method is based on the Pearson correlation coefficient calculated from sensitive spectral lines at different load operating conditions. Fusion information with belief function is then applied to the correlation coefficients, which enable the detection of an incipient fault in any phase of the machine. The method has the advantage to be fully non-invasive and does not require knowledge of the healthy state.

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Procedure for Detection of Stator Inter-Turn Short Circuit in AC Machines Measuring the External Magnetic Field

Energies ◽

10.3390/en14041132 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1132

Author(s):

Remus Pusca ◽

Raphael Romary ◽

Ezzeddine Touti ◽

Petru Livinti ◽

Ilie Nuca ◽

...

Keyword(s):

Magnetic Field ◽

External Magnetic Field ◽

Short Circuit ◽

Physical Phenomenon ◽

Invasive Procedure ◽

Spectral Lines ◽

Stator Windings ◽

Non Invasive ◽

Healthy State ◽

Rotor Poles

This paper presents a non-invasive procedure to detect inter-turn short circuit faults in the stator windings of AC electrical machines. It proposes the use of the stray external magnetic field measured in the vicinity of the machine to determine stator faults. The originality introduced by this procedure is the analysis method presented in the paper, which when compared to usual diagnosis methods, does not require any data on the healthy state of the machine. The procedure uses the magnetic unbalance created by the rotor poles and the load variation in faulty cases. The presented method can be applied to induction and synchronous machines used as a motor or generator. It is based on the variation of sensitive spectral lines obtained from the external magnetic field when the load changes. Analytical relationships are developed in the paper to justify the proposed method and to explain the physical phenomenon. To illustrate these theoretical considerations, practical experiments are also presented.

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Quantifying Internal Load in Pre-Professional Contemporary Dancers: The Association Between Objective Heart-Rate Derived Outcome Measures and Subjective Dancers’ and Teachers’ Perceptions

Journal of Dance Medicine & Science ◽

10.12678/1089-313x.031522h ◽

2021 ◽

Author(s):

Janine H. Stubbe ◽

Benjamin Soerel ◽

Raôul Oudejans ◽

Jolan Kegelaers ◽

Rogier M. van Rijn

Keyword(s):

Heart Rate ◽

Perceived Exertion ◽

Pearson Correlation ◽

Correlation Coefficients ◽

First Year ◽

Contemporary Dance ◽

Teachers Perceptions ◽

Non Invasive ◽

Subjective Perceptions ◽

Training Impulse

Background: Monitoring heart rate is one of the most common methods used to quantify internal training load (ITL) in athletes. The aim of this study was to determine whether subjective measurements can be used as a simple, non-invasive, and inexpensive method for assessing ITL in pre-professional contemporary dancers.Method: A total of 16 first-year contemporary dance students participated in this study. Students wore heart rate monitors during 56 training sessions. After each session, students completed the rate of perceived exertion (RPE) scale and teachers completed the rate of observed exertion (ROE) scale. For each session, we calculated the session-RPEs (sRPE), session-ROEs (sROE), and heart-rate-derived ITLs [i.e., Banister TRaining IMPulse method (TRIMP) and Edwards TRIMP]. Pearson correlation coefficients were calculated to determine the association between sRPE, sROE, Banister TRIMP, and Edwards TRIMP.Results: Between-individual correlation between Banister TRIMP and subjective dancers’ (sRPE) and teachers’ perceptions (sROE) were moderate (r = .49, p < 0.01) to large (r = .57, p < 0.01). Between-individual correlations between Edwards TRIMP and the subjective perceptions (sRPE and sROE) were very large (r = .74, p < 0.01; and r = .79, p < 0.01). There was a statistically significant large (r = 0.52, p < 0.01) to almost perfect (r = 0.93, p < 0.01) within-individual correlation between the sRPE and the two measured TRIMP methods. There was a statistically significant small (r = .29, p < 0.01) to almost perfect (r = .92, p < 0.01) within-individual correlation between the sROE and the two measured TRIMP methods. Conclusion: The results of this study suggest that the sRPE is a simple, non-invasive, inexpensive, and valid method for quantifying ITL in pre-professional dancers.

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Parametric Method based Inter-Turn Incipient Short Circuit Stator Fault Detection of Induction Motor

Indian Journal of Science and Technology ◽

10.17485/ijst/2016/v9i43/104668 ◽

2016 ◽

Vol 9 (43) ◽

Author(s):

W. Abitha Memala ◽

V. Rajini

Keyword(s):

Fault Detection ◽

Induction Motor ◽

Short Circuit ◽

Parametric Method ◽

Stator Fault

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Induction Motors Stator Fault Analysis based on Artificial Intelligence

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v2.i1.pp69-78 ◽

2016 ◽

Vol 2 (1) ◽

pp. 69 ◽

Cited By ~ 4

Author(s):

Hussein Taha Hussein ◽

Mohamed Ammar ◽

Mohamed Moustafa Hassan

Keyword(s):

Artificial Intelligence ◽

Fault Detection ◽

Short Circuit ◽

Fault Analysis ◽

Fault Detection And Diagnosis ◽

Neuro Fuzzy ◽

Detection Approach ◽

Three Phase ◽

Detection And Diagnosis ◽

Stator Fault

This article presents a method for fault detection and diagnosis of stator inter-turn short circuit in three phase induction machines. The technique is based on the stator current and modelling in the dq frame using an Adaptive Neuro-Fuzzy artificial intelligence approach. The developed fault analysis method is illustrated using MATLAB simulations. The obtained results are promising based on the new fault detection approach.

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Abstract 237: Using the Thoracic Impedance to Predict Measures From Invasive Arterial Blood Pressure in Out-Of-Hospital Cardiac Arrest

Circulation ◽

10.1161/circ.140.suppl_2.237 ◽

2019 ◽

Vol 140 (Suppl_2) ◽

Author(s):

Andoni Elola ◽

Elisabete Aramendi ◽

Unai Irusta ◽

Per-Olav Berve ◽

Fredrik K Arnwald ◽

...

Keyword(s):

Blood Pressure ◽

Cardiac Arrest ◽

Pearson Correlation ◽

Correlation Coefficients ◽

Invasive Blood Pressure ◽

Pulse Detection ◽

Non Invasive ◽

Arterial Blood ◽

Test Sets ◽

Hospital Cardiac Arrest

Background: During cardiopulmonary resuscitation (CPR), pulse detection can be challenging. Invasive blood pressure measurements (IBP) can help monitoring patient hemodynamics, but arterial catheter placement is difficult. Transthoracic impedance (TI) measured between the defibrillator pads can detect circulation activity. We hypothesized that TI changes can predict the corresponding IBP, and potentially be used to non-invasively detect pulse during CPR. Materials and methods: We included 28 out of hospital cardiac arrest patients receiving CPR by the Oslo Emergency Service who had concurrent recordings of IBP (radial artery, BD, 20G, US) and TI (via defibrillator pads, LP15, Stryker, US). 5-second segments with stable and CPR artefact free signals were extracted (Figure). The circulation component of the TI signal (Figure, red line) was extracted using a Kalman smoother. Ten waveform features were computed per segment and fed into a random forest regressor to predict systolic and diastolic arterial pressures (SAP, DAP), their difference (DifAP) and area of the IBP signal (ArAP). Pearson correlation coefficients between the regression model and the IBP metrics were computed. Data were divided by patient into training/test sets to fit and evaluate the model, respectively, and the process was repeated 500 times. Results: 235 minutes (2261 segments) were extracted with median (Q1-Q3) values of 71.3(39.2-88.1) mmHg for SAP, 44.2(30.0-50.0) mmHg for DAP, 25.6(7.1-38.8) mmHg for DifAP and 63.4(17.0-85.9) mmHg*sec for ArAP. The correlation coefficients between TI-predicted and IBP-measured SAP, DAP, DifAP and ArAP were 0.62 (0.49-0.72), 0.36 (0.22-0.49), 0.69 (0.57-0.76) and 0.64 (0.50-0.73), respectively. Conclusions: Different hemodynamic phases can be observed in both TI and IBP (Figure). TI-based predictions showed good correlation with IBP measures. This could lead to new non-invasive methods to monitor different phases of circulation based on the TI.

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Abstract 128: RNA-seq Based Non-Invasive Endovascular Biopsy of Brain Arteriovenous Malformations

Stroke ◽

10.1161/str.51.suppl_1.128 ◽

2020 ◽

Vol 51 (Suppl_1) ◽

Author(s):

Ethan Winkler ◽

David McCoy ◽

Zhengda Sun ◽

Daniel Cooke

Keyword(s):

Differentially Expressed Genes ◽

Pearson Correlation ◽

Rna Extraction ◽

Correlation Coefficients ◽

Mapk Signaling ◽

Differentially Expressed ◽

Rna Seq ◽

Detachable Coil ◽

Illumina Hiseq ◽

Non Invasive

Introduction: To-date, there is no accurate means to identify which bAVMs will bleed and treatment remains controversial. Hypothesis: We developed an endovascular biopsy (EB) technique to isolate endothelial cells (ECs) from bAVMs in patients. We hypothesized this technique would allow RNA-seq analysis of relevant bAVM-related molecular pathways. Methods: EB was performed during angiography for bAVM patients undergoing resection. Cells were obtained from a bAVM juxta-nidal feeding artery and iliac artery (control) with a detachable coil and 0.035 inch wire. ECs were isolated with fluorescence assisted cell sorting (FACS). bAVM tissue was obtained from surgery, dissociated and underwent FACS sorting. Total RNA extraction and library preparation was performed, and samples sequenced on an Illumina HiSeq 4000 sequencer. Reads were aligned with Kallisto, and differentially expressed genes identified between bAVM and control with Sleuth using likelihood ratio tests. Correlations between EB and resected tissues were calculated with Pearson correlation coefficients. Principle Component Analysis (PCA) was used to assess for cell clustering. Results: EB was performed in 4 patients without complication or adverse event. PCA showed separation of bAVM ECs from controls. Analysis demonstrated 106 differentially expressed genes (FDR p ≤ 0.05). KEGG pathway analysis on these genes revealed enrichment in bAVM-related RAS/MAPK cell signaling functionally related to trophic factor, chemokine and gap junction signaling pathways. Detected genes were strongly correlated between EB and ECs isolated from resected tissues (R 2 = 0.77 for artery, nidus, and vein tissue). Results shown in Figure 1 . Conclusions: EB is a safe technique to permit non-invasive sequencing of bAVMs. These results implicate dysregulated KRAS/MAPK signaling in adult bAVMs. Whether this technique will allow for better natural history prediction or targeted medical therapies requires future study.

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Validation of the Next-Generation Caretaker Continuous Physiological Monitor Using Invasive Intra-Arterial Pressures in Abdominal Surgery Patients

Medical Research Archives ◽

10.18103/mra.v9i7.2482 ◽

2021 ◽

Vol 9 (7) ◽

Author(s):

Irwin Gratz ◽

Martin Baruch ◽

Isabel Allen ◽

Julia Seaman ◽

Magdy Takla ◽

...

Keyword(s):

Abdominal Surgery ◽

Pearson Correlation ◽

Decomposition Analysis ◽

Correlation Coefficients ◽

Middle Finger ◽

Arterial Catheter ◽

Next Generation ◽

Non Invasive ◽

Blood Pressures ◽

Mean Differences

Introduction The reliable detection and, ultimately, prediction of hypotensive events in post-operative settings remains an unsolved problem, as patients are currently only monitored intermittently because of the lack of validated, non-invasive/non-intrusive and continuous physiological monitoring technologies. With this goal in mind, the aim of this study was to validate a next-generation platform version of the currently FDA-cleared non-invasive Caretaker (CT) physiological monitor in the hemodynamically challenging environment of abdominal surgeries in comparison with blood pressures obtained from arterial catheters, evaluated against ANSI/AAMI/ISO 81060–2:2019 standards as well as against current non-invasive standard of care measurements provided by clinical-grade automatic oscillometric cuffs. Methods Comparison data from 41 major abdominal surgery patients at Cooper Hospital (Camden NJ) were analyzed in this IRB approved study. Each patient was monitored with a radial arterial catheter and CT using a finger cuff applied to the contralateral middle finger. Systolic and diastolic blood pressures continuously collected from the arterial catheter and CT were compared using Pearson correlation coefficients and Bland-Altman analysis. In addition, a trend analysis using 4Q plots was performed. Both the CT’s continuous BP tracking and the CT’s self-calibration capability were analyzed. Results The continuous data comparisons were performed with and without taking the CT recalibrations into account. With the recalibrations the mean differences and standard deviations (STDs) for systole and diastole were, respectively, -1.14 mmHg (13.82 mmHg) and -2.49 mmHg (9.42 mmHg), while the correlations were 0.80 and 0.78. Mean differences and STDs for an initial calibration and no subsequent recalibrations were, respectively for systole and diastole, -0.42 mmHg (16.73 mmHg) and -2.57 mmHg (10.36 mmHg), while the correlations were 0.64 and 0.67. For the CT’s self-calibrations alone, correlations for systole and diastole were, respectively, 0.83 and 0.75, while corresponding mean differences (STD) were -3.19 mmHg (10.86 mmHg) and -2.41 mmHg (8.18 mmHg). For 41% of total surgery time, both systole and diastole were within 8 mmHg of the arterial catheter Gold Standard. The concordances for systolic and diastolic blood pressure changes on a 30-second time scale were 0.87 and 0.86. The same comparison analysis for the automatic cuff and the arterial catheter data yielded: correlations for systole and diastole: 0.69 and 0.61, mean differences and STDs: 2.48 mmHg (15.82 mmHg) and 0.65 mmHg (10.68 mmHg). Conclusions The results of this study are significant in that they validate the future use of the CT physiological monitor, which utilizes Pulse Decomposition Analysis (PDA), in the post-operative monitoring scenario both as a monitor to detect hypotensive events to facilitate clinical intervention as well as provide signal inputs that could enable anticipatory measures.

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Model Predictive Controller Utilized as an Observer for Inter-Turn Short Circuit Detection in Induction Machines - Preprint Version

10.36227/techrxiv.13633376 ◽

2021 ◽

Author(s):

İlker Şahin ◽

Ozan Keysan

Keyword(s):

Short Circuit ◽

Induction Machine ◽

Main Idea ◽

Optimization Procedure ◽

Induction Machines ◽

Voltage Source ◽

Non Invasive ◽

Finite Control ◽

Predictive Controller ◽

Stator Fault

<p>In this paper, a novel and non-invasive stator inter-turn short circuit (ITSC) online detection method is presented for an induction machine (IM), driven by a two-level voltage source inverter (2L-VSI) via finite control set model predictive control (FCS-MPC). The main idea of the proposed method is to utilize the controller itself as an observer: under the presence of a fault, the distribution of inverter switching states significantly deviates from the original balanced case. Therefore, by inspecting the inverter switching vectors, which are the outcomes of the FCS-MPC routine's online optimization procedure, a stator fault can be detected efficiently. It is observed that both the zero-vector allocation over the complex plane and the allocation among the active vectors are influenced by the presence of a stator short-circuit fault. The proposed fault detection strategy introduces little to no extra burden for processor and memory. Experimental results verify the proposed method, and inter-turn short circuits of two and three turns are confidently detected and located for a 500 W, two-pole IM.</p>

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Short Circuit and Broken Rotor Faults Severity Discrimination in Induction Machines Using Non-invasive Optical Fiber Technology

Energies ◽

10.3390/en15020577 ◽

2022 ◽

Vol 15 (2) ◽

pp. 577

Author(s):

Belema P. Alalibo ◽

Bing Ji ◽

Wenping Cao

Keyword(s):

Fault Detection ◽

Optical Fiber ◽

Condition Monitoring ◽

Short Circuit ◽

Induction Machines ◽

Electric Machines ◽

Data Logging ◽

Detection Techniques ◽

Non Invasive ◽

Fiber Technology

Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having various machine fault-detection techniques is useful in allowing the ability to combine two or more in a manner that will provide a more comprehensive application-dependent condition-monitoring solution; especially, given the increasing role these machines are expected to play in man’s transition to a more sustainable environment, where many more electric machines will be required. This paper presents a novel non-invasive optical fiber using a stray flux technique for the condition monitoring and fault detection of induction machines. A giant magnetostrictive transducer, made of terfenol-D, was bonded onto a fiber Bragg grating, to form a composite FBG-T sensor, which utilizes the machines’ stray flux to determine the internal condition of the machine. Three machine conditions were investigated: healthy, broken rotor, and short circuit inter-turn fault. A tri-axial auto-data-logging flux meter was used to obtain stray magnetic flux measurements, and the numerical results obtained with LabView were analyzed in MATLAB. The optimal positioning and sensitivity of the FBG-T sensor were found to be transverse and 19.3810 pm/μT, respectively. The experimental results showed that the FBG-T sensor accurately distinguished each of the three machine conditions using a different order of magnitude of Bragg wavelength shifts, with the most severe fault reaching wavelength shifts of hundreds of picometres (pm) compared to the healthy and broken rotor conditions, which were in the low-to-mid-hundred and high-hundred picometre (pm) range, respectively. A fast Fourier transform (FFT) analysis, performed on the measured stray flux, revealed that the spectral content of the stray flux affected the magnetostrictive behavior of the magnetic dipoles of the terfenol-D transducer, which translated into strain on the fiber gratings.

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