Reference health

Diagnostics of stator faults of the single-phase induction motor using thermal images, MoASoS and selected classifiers

https://doi.org/10.1016/j.measurement.2016.07.008
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30/30 checkable references clean · checked 2026-07-22

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

11 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 30 checked references that resolve
resolves10.1109/MIE.2013.2287651
Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques
resolves10.1155/2016/7145715
Discriminant Feature Distribution Analysis-Based Hybrid Feature Selection for Online Bearing Fault Diagnosis in Induction Motors
resolves10.1016/j.engfailanal.2014.11.020
Failure prediction of diesel engine based on occurrence of selected wear particles in oil
resolves10.5370/JEET.2015.10.4.1558
Support Vector Machine Based Bearing Fault Diagnosis for Induction Motors Using Vibration Signals
resolves10.1016/j.isatra.2014.09.006
A novel procedure for diagnosing multiple faults in rotating machinery
resolves10.1016/j.ymssp.2015.10.025
Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
resolves10.1016/j.measurement.2016.04.036
Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal: A review
resolves10.1016/j.ymssp.2015.02.008
A summary of fault modelling and predictive health monitoring of rolling element bearings
resolves10.1515/amm-2016-0028
Recognition of Acoustic Signals of Induction Motors with the Use of MSAF10 and Bayes Classfier
resolves10.1016/j.measurement.2015.05.049
Influence of constructive parameters and power signals on sound quality and airborne noise radiated by inverter-fed induction motors
resolves10.1016/j.ymssp.2015.10.020
Acoustic emission-based condition monitoring methods: Review and application for low speed slew bearing
resolves10.1515/aoa-2016-0036
Acoustic Diagnostics Applications in the Study of Technical Condition of Combustion Engine
resolves10.12913/22998624/63386
IDENTIFICATION AND MONITORING OF NOISE SOURCES OF CNC MACHINE TOOLS BY ACOUSTIC HOLOGRAPHY METHODS
resolves10.1007/s12206-015-0321-9
An on-line condition monitoring system for induction motors via instantaneous power analysis
resolves10.1515/aee-2015-0004
Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier
resolves10.1016/j.epsr.2015.06.008
A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors
resolves10.1515/aoa-2016-0028
Vibroacoustic Measurements and Simulations Applied to External Gear Pumps. An Integrated Simplified Approach
resolves10.1016/j.eswa.2011.08.004
Intelligent fault diagnosis of rotating machinery using infrared thermal image
resolves10.17531/ein.2015.4.1
The innovative design concept of thermal model for the calculation of the electromagnetic circuit of rotating electrical machines
resolves10.1016/j.applthermaleng.2015.05.038
An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique
resolves10.1016/j.fuel.2016.03.066
Analysis of the pilot injection running Common Rail strategies in a research diesel engine by means of infrared diagnostics and 1d model
resolves10.1016/j.infrared.2015.06.002
Production line quality control using infrared imaging
resolves10.1016/j.infrared.2015.09.004
Thermal image based fault diagnosis for rotating machinery
resolves10.1016/j.ress.2015.07.026
Perspective analysis outcomes of selected tribodiagnostic data used as input for condition based maintenance
resolves10.2478/msr-2014-0005
Investigations of Thermocouple Drift Irregularity Impact on Error of their Inhomogeneity Correction
resolves10.1515/msr-2015-0019
Method of Measurement of Capacitance and Dielectric Loss Factor Using Artificial Neural Networks
resolves10.3390/en8010475
Wind Power Prediction Considering Nonlinear Atmospheric Disturbances
resolves10.1016/j.asej.2014.10.005
A novel transmission line relaying scheme for fault detection and classification using wavelet transform and linear discriminant analysis
resolves10.1016/j.ymssp.2015.10.007
K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited
resolves10.1016/j.compchemeng.2015.09.013
GMM and optimal principal components-based Bayesian method for multimode fault diagnosis
The 11 references without a DOI — listed, not checked
no DOI — not checkedRotor failure diagnosis of induction motors by wavelet transform and Fourier transform in function of the load
no DOI — not checkedA distributed system of signal acquisition for induction motors diagnostic
no DOI — not checkedSensorless vibration diagnostics of permanent magnets traction electrical motors – the shaft unbalance example
no DOI — not checkedThermographic technique as a complement for MCSA in induction motor fault detection
no DOI — not checkedThermal diagnostic in electrical machines
no DOI — not checkedDiagnostics of electric equipments by means of thermovision
no DOI — not checkedThermal face recognition
no DOI — not checkedEarly detection of spontaneous combustion disaster of sulphide ore stockpiles
no DOI — not checkedUtilization of diffusion processes and fuzzy logic for vulnerability assessment
no DOI — not checkedApplication of K-nearest neighbor (KNN) approach for predicting economic events: theoretical background
no DOI — not checkedEvaluation of influence of spectral and prosodic features on GMM classification of Czech and Slovak emotional speech
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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