Mechanical Sensing
This dataset is in support of my research paper - Fault Analysis Centrifugal Pump (To download preprint, pls click on the title).
Acknowledgement : The author as such is thankful to none but obliged to his family for bearing his personal endeavours. Pls read Legal Disclosure Statement.
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Experiment Details:
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Calibration comparison data, including data obtained by calibrating the large deformation sensor using the proposed calibration device suitable for large deformation six-dimensional force sensors, and data obtained by calibrating the same large deformation six-dimensional force sensor using the calibration device suitable for high rigidity six-dimensional force sensors.
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289 Views
Insulation fault detection in rotating machinery using Partial Discharge (PD) has been a hot research topic over the last decades. In recent years, attention has also been paid to low voltage machines, following the advent of wide bandgap semiconductor devices. This paper presents a low-cost, modular, and full-digital PD monitoring device, particularly suitable for deployment in large industrial plants.
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Comparative measurements between a digital acquisition system and an analog acquisition system, namely National Instruments CompactRIO.
The dataset includes the measurements of a 10-days accelerated test performed on a tapered bearing (12 rolling elements) mounted on a motor test bench, from the brand-new condition until failure. The test bench was working at 2400 revolution per minute (RPM), and the bearing was preloaded with 4000 N.
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The Partial Discharge - Localisation Dataset, abbreviated: PD-Loc Dataset is an extensive collection of acoustic data specifically curated for the advancement of Partial Discharge (PD) localisation techniques within electrical machinery. Developed using a precision-engineered 32-sensor acoustic array, this dataset encompasses a wide array of signals, including chirps, white Gaussian noise, and PD signals.
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New capabilities involving sensors, data collection, and data analysis have enabled innovations in how engineered systems are monitored and maintained. Whereas each new evolution of maintenance philosophies has relied upon the current technological state, this research examines potential future capabilities in the field of prognostics and health management (PHM). PHM algorithms for predicting the estimated time to failure for a system are based on sensor data, physical models, or a combination of both.
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This is a data set to show the advantage of the method in this paper, the data set has two kinds of data: the multi-sine phase-shifting images and comparison method images, the images are all modulated for different targets, such as: The half of white ping pong ball . In this data set, the “3phase.bmp” are the images for the method in this paper, the ”2plus1.bmp” are the images for all kinds of two phase-shifting methods, where R layer image is average intensity image, G layer and B layer images are phase-shifting images.
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While resistance training promotes muscle hypertrophy, accessibility of equipment is a barrier. This study evaluated a wearable VAriable Resistance Suit (VARS) as a novel and alternative method to achieve muscle hypertrophy. It was hypothesized that by providing adjustable, bi-directional and speed dependent resistance, VARS can target specific muscles to improve muscle strength, size and mass in an accessible and portable device.
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