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A Method of Equipment Status Prediction Based on Massive Data Mining

A technology of equipment status and prediction method, applied in the direction of electrical digital data processing, digital computer parts, instruments, etc., can solve the problems of loss, low efficiency, large manpower and material resources, etc., and achieve low overhead, high efficiency, early warning and diagnosis good effect

Inactive Publication Date: 2016-09-07
STATE GRID CORP OF CHINA +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

There are several problems with these traditional methods: 1. Regular testing requires a lot of manpower and material resources, and the efficiency is very low. 2. Some unnecessary equipment is also tested, resulting in a waste of resources. 3. Downtime testing may bring huge economic loss

Method used

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  • A Method of Equipment Status Prediction Based on Massive Data Mining
  • A Method of Equipment Status Prediction Based on Massive Data Mining
  • A Method of Equipment Status Prediction Based on Massive Data Mining

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Embodiment Construction

[0025] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0026] The implementation of the algorithm is divided into two steps. One is to use the historical data of equipment operation to establish the equipment operation state model, which is realized by clustering algorithm; the other is to use the equipment state model obtained through clustering, combined with the real-time state of equipment operation The data is used to make regression predictions on the current operating state. After that, some alarm rules are combined to realize the online real-time early warning of the equipment. The overall application model of the algorithm is shown in the attached figure 1 shown.

[0027] Algorithm step 1: learning algorithm. The algorithm takes the data samples reflecting the historical operation status of the equipment as the training data set, reads the data vector (Data Vector) in the training set ...

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Abstract

The invention belongs to the field of data mining based on mass data of industrial equipment and provides an equipment status predication method. According to the equipment status predication method, useful knowledge is sufficiently mined from historical data, the equipment status can be effectively predicted in combination with actual conditions of equipment, knowledge learning can be finished with higher efficiency on the premise of lower overhead, and a predication and diagnosis result of the equipment status can be provided in real time. The mass data mining-based equipment status predication method plays a favorable role for enterprises to realize status monitoring, warming diagnosis and the like of large-scale equipment.

Description

technical field [0001] The invention belongs to the field of data mining based on massive data of industrial equipment, in particular to an equipment state prediction algorithm based on massive data mining. Background technique [0002] The development of modern large-scale industrial enterprises is inseparable from equipment. The stable and continuous operation of these devices is closely related to the interests of the enterprise, and their failure or even abnormal shutdown will bring unimaginable losses to the enterprise. Therefore, during its operation, it is very important to discover possible faults in advance and to prevent and eliminate them. There are some traditional methods for this, such as regular manual inspections, equipment shutdowns for routine inspections, etc. There are several problems with these traditional methods: 1. Regular testing requires a lot of manpower and material resources, and the efficiency is very low. 2. Some unnecessary equipment is als...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F15/18G06K9/62
Inventor 唐胜胡洁
Owner STATE GRID CORP OF CHINA