Energy router life prediction method and device based on artificial intelligence
A technology of life prediction and artificial intelligence, applied in the field of information processing, can solve problems such as energy waste, and achieve the effect of improving reliability
Active Publication Date: 2021-12-10
TECHNICAL INST OF PHYSICS & CHEMISTRY - CHINESE ACAD OF SCI
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Problems solved by technology
The energy router is a kind of power equipment that integrates information technology and power electronic conversion technology. It realizes the efficient utilization and transmission of distributed energy. Its high reliability is an important guarantee for the normal maintenance and operation of the energy network system. Make a unified limit on the running time, and replace all of them when it expires, which will cause a large number of usable energy routers to be replaced, resulting in a waste of energy
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[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.
[0045] Such as figure 1 An artificial intelligence-based energy router life prediction method described in an embodiment of the present invention includes the following steps:
[0046] 110. Construct a life prediction model based on the residual network, and use the historical abnormal data of the energy router under test as training data to train the life prediction model.
[0047] 120. Construct a life prediction data set by using abnormal data in real-...
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The invention relates to an energy router life prediction method based on artificial intelligence, which comprises the steps of: constructing a life prediction model based on a residual network, training the life prediction model by taking historical abnormal data of a tested energy router as training data, and constructing a life prediction data set according to abnormal data in real-time operation of the energy router with the same equipment model as a tested energy router; and predicting the life prediction data set by using the trained life prediction model to obtain the residual service life of the tested energy router. According to the energy router life prediction method, a static prediction model for the life of the energy router is avoided, the reliability of life prediction of the energy router is improved, and the related early warning level is established according to the life prediction value of the energy router to remind a worker to replace the energy router in time. The invention further relates to an energy router life prediction device based on artificial intelligence.
Description
technical field [0001] The present invention relates to the technical field of information processing, in particular to an artificial intelligence-based energy router life prediction method and device. Background technique [0002] With the development of distributed energy and micro-grid technologies, a large number of energy supply or energy consumption devices need to be connected to the energy transmission network, and the energy router can realize the interconnection, scheduling and control of various energy networks. The energy router is a kind of power equipment that integrates information technology and power electronic conversion technology. It realizes the efficient utilization and transmission of distributed energy. Its high reliability is an important guarantee for the normal maintenance and operation of the energy network system. If the energy router A unified limit is set for the running time, and all of them will be replaced when it expires, which will cause a...
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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08G06K9/62
CPCG06Q10/04G06Q50/06G06N3/08G06N3/047G06N3/045G06F18/2415G06F18/214
Inventor 徐少山沈俊李振兴王浩高新强徐田园
Owner TECHNICAL INST OF PHYSICS & CHEMISTRY - CHINESE ACAD OF SCI