Motor Fault Dataset

Motor Fault Dataset

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Electric Motor Dataset, Paper, and Code

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• hustcxl/Rotating-machine-fault-data-set: Open rotating mechanical fault datasets)
• Machine Learning Datasets for Production

Dataset: Vibration

• Charlie5DH/PredictiveMaintenance-and-Vibration-Resources: Papers and datasets for Vibration Analysis List of Dataset
• Vibration measurement on SAG mill drive motor | IEEE DataPort
• Electric Motor Vibrations Dataset | Zenodo
  • motor: unknown
  • status: embargo

Dataset: RUL

• Prognosis based on Varying Data Quality | Kaggle
• Preventive to Predictive Maintenance | Kaggle

Dataset: Inverter

• Inverter Data Set | Kaggle

Dataset: Bearing

• Konstruktions- und Antriebstechnik (KAt)  -  Data Sets and Download (Universität Paderborn)
• IEEE phm 2012 data challenge | Kaggle
• Intelligent bearing fault diagnosis dataset | Kaggle
• CWRU Bearing Dataset | Kaggle
• Fault Data Sets - Society For Machinery Failure Prevention Technology Rotating-machine-fault-data-set/MFPT
• Bearing Vibration Data under Time-varying Rotational Speed Conditions - Mendeley Data
  • component: bearing in motor
  • sensor: vibration, speed
  • paper: Bearing vibration data collected under time-varying rotational speed conditions - ScienceDirect
  • HW: SpectraQuest Inc.,: Machinery Fault Simulators induction?
  • report: Wavelet transform applied on machine vibration analysis
  • Konstruktions- und Antriebstechnik (KAt)  -  Data Sets and Download (Universität Paderborn)
• sliu7102/SQ-dataset-with-variable-speed-for-fault-diagnosis: Open dataset in the field of mechanical fault diagnosis under variable speed conditions, providing benchmark for algorithm performance evaluation

Dataset: Gearbox

• Gearbox Fault Detection Dataset, PHM 2009 (NASA) | Kaggle
• cathysiyu/Mechanical-datasets

Dataset: Induction Motor

• Current Signature Dataset of Three-Phase Induction Motor under Varying Load Conditions - Mendeley Data dl
• MAFAULDA Dataset Induction Motor Fault
  • kaggle: Induction Motor Faults Detection | Kaggle
  • MAFAULDA - Machinery Fault Database
  • Github 1: milank94/motor-fault-classification: The following is a machine learning project to classify induction motor fault modes.
  • Paper 1: Industrial Motor Fault Classification using Deep Learning with IoT Implications | by Milan Kordic | Towards Data Science
  • Github 2: mo26-web/Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning
• Treml - Experimental database for detecting and diagnosing rotor broken bar in a three-phase induction motor
• Inter-turn Short-Circuit In Induction Motor: | Kaggle
• The motor fault daignosis experiment dataset | Zenodo
• Experimental database for detecting and diagnosing rotor broken bar in a three-phase induction motor. | IEEE DataPort dl
  • motor: induction
• Frequency Occurrence Plots for Motor Fault Diagnosis based on Image Recognition | IEEE DataPort dl
• Triaxial Bearing Vibration Dataset of Induction Motor under Varying Load Conditions - Mendeley Data
• Modeling Electrical Motor Dynamics using Encoder-Decoder with Recurrent Skip Connection sagarverma/MotorDynamics: Modelling electrical motor dynamics using neural networks.
  • The dataset consists of the following electrical quantities; currents id and iq, voltages ud and uq, rotor speed ωr , stator pulsation ωs , and torque τem. The indices d and q denote three phase quantities represented in a two phase orthogonal rotating reference frame.
• Vibration, acoustic, temperature, and motor current dataset of rotating machine under varying operating conditions for fault diagnosis - ScienceDirect Vibration and Motor Current Dataset of Rolling Element Bearing Under Varying Speed Conditions for Fault Diagnosis: Subset3 - Mendeley Data
  • sensor: vibration, acoustic, temperature, current
  • fault: normal, inner bearing fault, outer bearing fault, shaft misalignment, rotor unbalance
  • motor: induction
  • speed: varying
• Experimental database for detecting and diagnosing rotor broken bar in a three-phase induction motor. | IEEE DataPort
  • sensor: vibration, voltage, current
  • fault: broken bar
• MatPiech/motor-fault-diagnosis: Multi-sensor data collection gathered to expand research on anomaly detection, fault diagnosis, and predictive maintenance, mainly using non-invasive methods such as thermal observation or vibration measurement. Pliki - ownCloud
  • sensor: thermal image, current, vibration
  • fault: misalignment

Dataset: DC Motor

• Direct current geared motor data: Voltage, current, and speed measured under different experimental conditions - Data in Brief
• F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms | Zenodo
  • motor: DC
  • sensor: This dataset presents the evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise).

Dataset: BLDC Motor

• Data on the first endurance activity of a Brushless DC motor for aerospace applications - Data in Brief
  • Data for: First endurance activity of a Brushless DC motor for aerospace applications - REPRISE project - Mendeley Data
  • Data(Linear motor load reference, Temperature inside the EMA box, Current supplied to the EMA (from power supply), Load cell measure, EMA position reference, EMA position measure from (embedded) LVDT sensor, EMA position measure from (external) absolute optical sensor, Current supplied to the linear motor (from its drive), EMA 3-phase currents)
  • Data for: First endurance activity of a Brushless DC motor for aerospace applications - REPRISE project - Mendeley Data dl v2
  • Data on the first endurance activity of a Brushless DC motor for aerospace applications | Mirko Mazzoleni
  • Data on the first endurance activity of a Brushless DC motor for aerospace applications | Mirko Mazzoleni Motor BLDC
  • Mendeley Data
  • Data on the first endurance activity of a Brushless DC motor for aerospace applications - ScienceDirect focus to nut and screw degradation
  • motor: BLDC
  • application: aerospace
• Autonomous underwater vehicle fault diagnosis dataset - Data in Brief
  • motor: BLDC
  • application: underwater
• Optimised approach of feature selection based on genetic and binary state transition algorithm in the classification of bearing fault in BLDC motor - Lee - 2020 - IET Electric Power Applications - Wiley Online Library
  • motor: BLDC
  • sensor: Hall Sensor
  • Chun-Yao Lee of Chun-Yuan Christian University, Taiwan cyl@cycu.edu.tw 著作
  • Fault Diagnosis of a Brushless DC Motor Using K-Nearest Neighbor Classification Technique with Discrete Wavelet Transform Feature Extraction | IEEE Conference Publication | IEEE Xplore
  • Intelligent Fault Diagnosis for BLDC With Incorporating Accuracy and False Negative Rate in Feature Selection Optimization | IEEE Journals & Magazine | IEEE Xplore
  • Symmetry | Free Full-Text | Feature Ranking and Differential Evolution for Feature Selection in Brushless DC Motor Fault Diagnosis
• Modeling and Fault Detection of Brushless Direct Current Motor by Deep Learning Sensor Data Fusion, Priscile Suawa, suawapri@b-tu.de
  • motor: BLDC
• An Expert System for Rotating Machine Fault Detection Using Vibration Signal Analysis, Ayaz Kafeel, ayaz2788@gmail.com
  • motor: BLDC
  • sensor: vibration
  • Sensors | Free Full-Text | An Expert System for Rotating Machine Fault Detection Using Vibration Signal Analysis
• BLDC motor temperature | IEEE DataPort
  • motor: BLDC
  • sensor: temperature
  • status: downloaded
  • The dataset contains two files (measurement for the motor without cooling, measurement results after installing an additional cooling fan on the shaft). The data: time stamp, winding temperature, casing temperature, speed, current, power loss, mean and standard deviation of the measured quantities for 14400 data records.
• Data:Non-Linear Flux & Thermal Losses in BLDC | IEEE DataPort dl
• Vibration dependent short duration short circuit in PMDC Motor | IEEE DataPort dl
• IDMT-ISA-ELECTRIC-ENGINE - Fraunhofer IDMT
  • motor: BLDC
  • sensor: acoustic

Dataset: PMSM

• Identifying the Physics Behind an Electric Motor | Kaggle Data Set Description: Identifying the Physics Behind an Electric Motor -- Data-Driven Learning of the Electrical Behavior (Part I)
• Vibration and Current Dataset of Three-Phase Permanent Magnet Synchronous Motors with Stator Faults - Mendeley Data Vibration and current dataset of three-phase permanent magnet synchronous motors with stator faults - ScienceDirect
  • motor: PMSM
  • sensor: vibration, current
  • fault: intern-turn fault, inter-coil fault
  • status: used

Dataset: Vehicle

• Sensors | Free Full-Text | Multi-Sensor Fault Detection, Identification, Isolation and Health Forecasting for Autonomous Vehicles MAminSFV/multi-sensor-FDII-health-forecasting-for-autonomous-vehicles: An Extension of A2D2 dataset by Audi with augmented sensor faults and different degradation paths

Dataset: Azure

• Microsoft Azure Predictive Maintenance | Kaggle

Motor Dataset New

• Mechanical faults in rotating machinery dataset (normal, unbalance, misalignment, looseness) - Mendeley Data
  • Sensor: accelerometer 4
  • Fault: misalignment, mechanical looseness, unbalance
  • Fault Diagnosis using eXplainable AI: A transfer learning-based approach for rotating machinery exploiting augmented synthetic data - ScienceDirect
  • Motor: induction
• Vibration, acoustic, temperature, and motor current dataset of rotating machine under varying operating conditions for fault diagnosis - ScienceDirect
  • First dataset consists of vibration, acoustic, temperature and driving current data under varying load conditions. Vibration, temperature, motor current, and acoustic data are collected under 3 different load conditions (0 Nm, 2 Nm and 4 Nm). The load conditions are controlled by hysteresis brake with air cooling method. The main motor rotates at a rated rotating speed of 3010 RPM.
  • Second, the collected dataset consists of vibration and current data acquired from the ball bearing with different fault types of inner race faults, outer race faults, and ball faults, according to changes in motor speed conditions (680 RPM and 2460 RPM).
• Triaxial bearing vibration dataset of induction motor under varying load conditions - ScienceDirect
• Dataset of single and double faults scenarios using vibration signals from a rotary machine - ScienceDirect
• University of Ottawa constant load and speed rolling-element bearing vibration and acoustic fault signature datasets - ScienceDirect
• Bearing vibration data collected under time-varying rotational speed conditions - ScienceDirect

Brushless DC Motor is a type of electric motor that is powered by direct current (DC) and does not use brushes to transfer electrical energy to the motor's rotor. Instead, it uses electronic commutation to control the motor's rotation. This design offers several advantages over traditional brushed DC motors, including higher efficiency, longer lifespan, and reduced maintenance requirements. Brushless DC motors are commonly used in a wide range of applications, including industrial machinery, automotive systems, and consumer electronics.

New Dataset Try This

• Multivariate Heterogeneous Time Series Data for Machine-Learning-Supported Monitoring of a Motor Test Bench
  • Fault: Normal, Rotor temperature sensor fault, vibration sensor fault, cooling fault, active short circuit fault
  • Sensor: temperature, current, vibration