| Wind turbine condition monitoring dataset of Fraunhofer LBF |
|
mxds3cvcya564e31 |
机器收录·待核验 |
| A Dataset of Seismic and Ambient Vibrations from a 16-Story Building in Bucharest, Romania, Capturing the 10 Largest Vrancea Earthquakes (ML 4.0-4.4) of 2025 |
|
mxdsazk0sk9bpf33 |
机器收录·待核验 |
| "CNC machine tool fault data" |
machine_tool |
mxdshp8qmkcvdc37 |
核心 · 已核验 |
| Aging data based on daily cogeneration profile |
fuel_cell |
mxdsx1z7rr817e74 |
核心 · 已核验 |
| Associated Dataset for High-Impedance Ground Fault Identification in Distribution Networks |
|
mxds6t07rbywgk34 |
核心 · 已核验 |
| DT-MAS architecture for smart maintenance of aircraft fuel distribution systems |
pump aero_engine |
mxdsfzjmag74a872 |
核心 · 已核验 |
| Fault Simulation Data of a Central Air Conditioning System in Changsha, China, for the Year 2025 |
|
mxds0csee3kh4h12 |
核心 · 已核验 |
| Cleaned and Preprocessed Aventa AV-7 Wind Turbine SCADA Dataset for Anomaly Detection and Cybersecurity Research |
|
mxdsnmak1kj33y43 |
机器收录·待核验 |
| Dataset for "Experimental Study on Cycle Aging of 3.4 Ah Lithium-Sulfur Pouch Cells: Temperature and Current Investigation" |
|
mxdscshzvmvmtm25 |
机器收录·待核验 |
| A Dataset of Seismic and Ambient Vibrations from a 12-Story Building in Bucharest, Romania, Capturing the 10 Largest Vrancea Earthquakes (ML 4.0-4.4) of 2025 |
|
mxds3t27dm2xgr15 |
机器收录·待核验 |
| An experimental framework for determining wear in porous journal bearings operated in the mixed lubrication regime |
journal_bearing |
mxds4xzrse8jy985 |
核心 · 已核验 |
| The WEICan Data used in the paper "An accumulation method for early fault warning and its application to wind turbine systems" |
|
mxdsxgc4eqpety98 |
机器收录·待核验 |
| Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods |
|
mxdssw5x45j90657 |
机器收录·待核验 |
| Offboard laser Doppler vibrometry dataset for UAV propeller fault diagnosis |
rotorcraft_uav |
mxds6mhg3cegp672 |
核心 · 已核验 |
| IEA Wind TCP Task 49 Failure Risk Mitigation for Floating Offshore Wind Arrays |
wind_turbine |
mxdsrd6r8hq5kv38 |
核心 · 已核验 |
| A Multifunction Vehicle Bus Physical-Layer Dataset for Network Fault Diagnosis in Rail Transit Systems |
|
mxdsa8ta93n5kc84 |
核心 · 已核验 |
| A Dataset of Seismic and Ambient Vibrations from an 8-Story Building in Bucharest, Romania, Capturing the 10 Largest Vrancea Earthquakes (ML 4.0-4.4) of 2025 |
|
mxdsat69sjd1g855 |
机器收录·待核验 |
| Vibration Data from 37-story Building in Bangkok During 7.7Mw Earthquake on 28 March 2025. |
|
mxds6jerezgvyj38 |
机器收录·待核验 |
| Dataset from cutting tool performance and cutting edge quality testing in relation to machining process parameters |
|
mxdscps0zxx2nn61 |
机器收录·待核验 |
| Bearing Database - Combined Failure (Test 2) |
|
mxdsbgerfg0g8k51 |
机器收录·待核验 |
| A Dataset of Seismic and Ambient Vibrations from a 4-Story Building in Bucharest, Romania, Capturing the 10 Largest Vrancea Earthquakes (ML 4.0-4.4) of 2025 |
|
mxds9cega4q5vs49 |
机器收录·待核验 |
| Characterization of the iPhone LiDAR Sensor for Vibration Measurement and Modal Analysis - Dataset |
|
mxds9h7bm3zwgm53 |
机器收录·待核验 |
| Experimental study of machinability of CHSF/PR composites by end milling |
|
mxdswech7na25c23 |
机器收录·待核验 |
| Wind_Turbine_Blade_Acoustic_Dataset |
|
mxdskb8p4pats378 |
机器收录·待核验 |
| Motor-Current Dataset for Cycle-Level Payload Estimation on Two KUKA KR3 Robots |
|
mxdsmg3n6r07dy86 |
机器收录·待核验 |
| Aventa AV-7 ETH Zurich Research Wind Turbine SCADA and high frequency Structural Health Monitoring (SHM) data |
|
mxds9cfe2ptpjr26 |
机器收录·待核验 |
| Experimental design and results for surface roughness (Ra) and specific cutting energy (Ec) in AISI 1045 end milling |
|
mxds3m8rq5wyg725 |
核心 · 已核验 |
| Twin-spool Rotor Fault-free and Unbalance Vibration Dataset |
|
mxdsfkpqtqe0vh55 |
机器收录·待核验 |
| CAMELOT benchmark for Structural Health Monitoring |
|
mxdsfbfjhz0qyd10 |
机器收录·待核验 |
| Local Attention Pointer Bearing Fault Diagnosis |
|
mxdsv2jzwsv8z448 |
核心 · 已核验 |
| Shearographic Anomaly Detection Dataset (SADD) |
|
mxdsgv54kd2ej042 |
机器收录·待核验 |
| Multi-Condition Lithium-ion Battery Degradation Dataset |
|
mxds8gg6n03f4164 |
机器收录·待核验 |
| Peer-review data and script for paper: Advancing physico-chemical pathway for understanding the effect of electrolyte composition on battery degradation |
|
mxdsa4yha88ahr67 |
机器收录·待核验 |
| Study on the influence of electric erosion on the early lubrication state of rolling bearings |
rolling_bearing |
mxdsz43620egtp96 |
核心 · 已核验 |
| Effect of Voltage Frequency on the Formation of Electric Damage on Bearing Outer Race |
rolling_bearing |
mxdsewmzpyrz8d49 |
核心 · 已核验 |
| URMA-CRTI dataset for rolling element bearing vibration data |
|
mxdshevbxdenm509 |
机器收录·待核验 |
| Supplementary Material: Multivariate time-series data from a hydraulic test rig used for condition monitoring |
|
mxdsra1mj1rpva46 |
机器收录·待核验 |
| Multimodal Bearing Failure Diagnosis Dataset Under Various Startup Modes of an Asynchronous Electric Motor |
|
mxdsnsrjk5etm857 |
机器收录·待核验 |
| ASTM C93900 Bronze Plain-Bearing Bushing Vibration Dataset for Condition Monitoring and Deep Learning Applications |
journal_bearing |
mxdshpkawph31t62 |
核心 · 已核验 |
| DATA for A Structural Response Prediction Method Based on Data-Driven for Offshore Wind Turbines Considering Time-Dependent Corrosion Damage |
|
mxds1n2f4b9rny04 |
机器收录·待核验 |
| Database of Lithium-Ion Battery Aging: Degradation Modes, Electrode Resistance Rise, and Impedance |
|
mxds96wmzpv9z406 |
机器收录·待核验 |
| Dataset on Guided Waves from Long-Term Structural Health Monitoring under Uncontrolled and Dynamic Conditions |
|
mxdsm0wgdn99a472 |
机器收录·待核验 |
| Compressor PLC Data Based on 5G Edge Computing |
|
mxdsdk1reg3ta196 |
机器收录·待核验 |
| Low-frequency oscillation test data for a certain model of plunger pump |
|
mxds40ggern5f947 |
机器收录·待核验 |
| Dataset: Polymer degradation and its effects in an electrical submersible pump system |
|
mxdsf42f1gerw663 |
核心 · 已核验 |
| Experimental Investigation in to Lubricant Properties and Surface Features on Thrust-ball Bearing Skidding and Friction Torque |
rolling_bearing |
mxdswd0ba4apjn18 |
核心 · 已核验 |
| Accelerated Life Test Method for Low speed Heavy Load Self Lubricating Joint Bearings[Received 7 November 2024, revised 18 January 2025, accepted 20 January 2025, available online 28 January 2026. *Corresponding author. E-mail: qxw@ysu.edu.cn, Tel: +86-18603373001. This project was supported by the Research on Common Technologies by the Science and Technology Bureau (JPPT-2017-142). 科工局专项(JPPT-2017-142)资助.] |
|
mxdsff3t860vkz13 |
核心 · 已核验 |
| Prediction Method of Contact Fatigue Behavior of High-speed Train Transmission Gears Considering Wheel Rail Service Status |
gearbox |
mxdseywm6057k565 |
核心 · 已核验 |
| Structural Health Monitoring test data and procedures |
|
mxdsbbytmkntgv07 |
机器收录·待核验 |
| MOTOR FAULT DETECTION DATA |
|
mxdsr5rfw96mbt74 |
核心 · 已核验 |