Reliability
The Phoenix Contact Relay (PCR) dataset is provided for the development of algorithms for the analysis of lifetime data. It differs from previously published datasets in the number and complexity of measurements, as well as the scope of units tested and the practical relevance of the data. Thus, it provides an opportunity to develop and evaluate new concepts for predictive maintenance. The PCR data set presented includes the life data of 546 relays with a total of more than 106 million switching cycles, collected over a period of several years at a sampling rate of 10 kHz.
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In traditional schemes, obtaining a robust topology requires high connectivity. We chose random undirected and directed network topologies for comparison to showcase the
advantages of entropy and connectivity.
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Power transformers are inevitably subjected to external short circuit impact during their service period. The electromagnetic force generated by the fault current may cause winding destabilization and collapse. The radial buckling of the inner winding accounts for a considerable proportion. Based on the effective contact of the sticks, the traditional analytical methods ignore the manufacturing deviation and operation impact (MDOI) characterized by assembly gaps and insulation shrinkage.
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This paper investigates the prescribed performance control (PPC) problem for a class of nonlinear strict-feedback systems with sensor/actuator faults. A shifting function is introduced to modify the output tracking error generated by the practically measured system state, based on which an improved PPC method is proposed to achieve the convergence of output tracking error to the prescribed region, and this convergence is shown to be independent of the initial tracking condition and insusceptible to sensor/actuator faults.
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A synthetic data for low power (P ≤10 mW) InGaAsP MQW-DFB lasers operating at a wavelength (λ) ranging from 1.53 to 1.57 µm at a case temperature laying between -40 ℃ to 85 ℃ with side mode suppression ratio of more than 35 dB is generated and can be used for laser lifetime prediction using machine learning based approaches.
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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization.
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3632 Views
Light wfeight Function create stem3 model with an complex route as in link figure data set
Link:
https://www.mathworks.com/matlabcentral/communitycontests/contests/5/ent...
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'XMD.mat' is the deterioration levels monitored before the failure of 10 components。
'XMDS.mat' is the deterioration levels monitored before the failure of 10 components subjected to random shocks.
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170 Views
Relevant trained model and experimental data for TIE-22-1436
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