نتائج البحث

Microgrid Reliability Incorporating Uncertainty in Weather and Equipment Failure.

• Authors : Nallainathan, Sakthivelnathan¹ (AUTHOR); Arefi, Ali^1,2 (AUTHOR) ; Lund, Christopher¹ (AUTHOR)

• Source: Energies (19961073). Apr2025, Vol. 18 Issue 8, p2077. 23p.

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PREDICTING GAS LIFT EQUIPMENT FAILURE WITH DEEP LEARNING TECHNIQUES

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Mechanical equipment fault diagnosis method based on improved deep residual shrinkage network.

• Authors : Qiu S; School of Information Engineering, Dalian University, Dalian, Liaoning, China.; Liu L

Subjects: Equipment Failure Analysis*; Algorithms ; Neural Networks, Computer

• Source: PloS one [PLoS One] 2024 Oct 28; Vol. 19 (10), pp. e0307672. Date of Electronic Publication: 2024 Oct 28 (Print Publication: 2024).Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet

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工业生产设备故障领域问答系统的意图识别.

• Authors : 王雨萱¹ ; 万卫兵¹ ; 程锋¹

• Source: Science Technology & Engineering. 2024, Vol. 24 Issue 18, p7746-7759. 14p.

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Data-driven multivariate time series prediction of in-vehicle equipment failure rates

• Authors : Yongfei Guo; Yonggang Chen; Haiyong Wang

Subjects: Vehicle-mounted equipment; Failure rate prediction; Multivariate variational modal decomposition

• Source: Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-22 (2024)

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Machine learning based equipment failure prediction

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HVAC system with equipment failure warning

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A FRAMEWORK FOR MANAGEMENT OF LEAKS AND EQUIPMENT FAILURE IN OIL WELLS

• Authors : Dennis, T. L.; Anireh, V. I. E.; Emmah, V. T.

• Source: International Journal of Engineering and Computer Science. 13:26300-26309

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Risk Assessment for Energy Stations Based on Real-Time Equipment Failure Rates and Security Boundaries.

• Authors : Luo, Yongheng¹ (AUTHOR); Li, Zhonglong¹ (AUTHOR); Li, Sen¹ (AUTHOR)

Subjects: *RISK assessment; *ENERGY security; *ECONOMIC securityCHINA

• Source: Sustainability (2071-1050). Sep2023, Vol. 15 Issue 18, p13741. 27p.

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Data and source validation for equipment output data or equipment failure prediction using blockchains

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