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Elevator fault early-warning method based on Internet of Things technology and coupled graph neural network

An Internet of Things technology and neural network technology, applied in the field of elevator fault early warning, can solve the problems of difficult precision and accuracy of the model, the imbalance of elevator fault data and non-fault data, etc.

Pending Publication Date: 2021-05-07
ZHEJIANG NEW ZAILING TECH CO LTD
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  • Abstract
  • Description
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Problems solved by technology

However, due to the serious data imbalance between elevator fault data and non-fault data, it is difficult for common models to achieve ideal precision and accuracy at the same time.

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  • Elevator fault early-warning method based on Internet of Things technology and coupled graph neural network
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  • Elevator fault early-warning method based on Internet of Things technology and coupled graph neural network

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Embodiment Construction

[0032] In order to more clearly describe the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings that are used in the embodiments. Apparently, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to these drawings without creative efforts.

[0033] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, and the embodiments cannot be repeated here one by one, but the embodiments of the present invention are not therefore limited to the following embodiments.

[0034] see figure 1 , the elevator failure warning method based on the Internet of Things technology and the coupling graph neural network of the present invention uses the Internet of Things technology to collect data in the elevator in real time, and transmits t...

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Abstract

The invention relates to an elevator fault early-warning method based on the Internet of Things technology and a coupled graph neural network. The elevator fault early-warning method based on the Internet of Things technology and the coupled graph neural network comprises the following steps: a, acquiring data in an elevator car in real time, and transmitting the collected data to a cloud; b, preprocessing the data, and carrying out feature extraction; and c, utilizing a pre-trained coupled graph neural network model for analyzing the data acquired in real time at the cloud, and carrying out early-warning on elevator faults in advance. According to the invention, early-warning for the elevator faults is realized in advance through the coupled neural network model, and therefore the elevator fault early-warning method has higher accuracy and precision compared with a traditional mode under the conditions that data are unbalanced and fault data are few.

Description

technical field [0001] The invention relates to an elevator fault early warning method based on Internet of Things technology and a coupling graph neural network. Background technique [0002] With the increase of modern high-rise buildings, elevators have become an important means of transportation. As the service life of the elevator increases, more and more elevator failures occur. Due to many elevator brands and various types of failures, it is difficult to predict elevator failures in advance. [0003] In the prior art, the establishment of statistical analysis and regular maintenance is usually used to realize the early intervention of the elevator failure. With the development of big data, machine learning and artificial intelligence technology, some technologies have begun to combine big data and use deep neural networks to provide early warning of elevator failures. Common models mainly include: tree model (Xgboost, GBDT, etc.), support vector product, LSTM, etc....

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B66B5/02B66B5/00
CPCB66B5/02B66B5/0018
Inventor 朱帅黄中平李壮贾春华吴磊磊蔡巍伟
Owner ZHEJIANG NEW ZAILING TECH CO LTD
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