Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Artificial intelligence electrical line fire risk real-time early warning method and system

A technology of artificial intelligence and fire early warning, which is applied in fire alarms with electric action, fire alarms with smoke/gas action, fire alarms, etc. To prevent problems before they happen, electrical line fire early warning and other issues, to achieve high early warning efficiency, eliminate occasional abnormalities, and accurate fire early warning effects

Active Publication Date: 2020-05-12
上海枫昱能源科技有限公司
View PDF6 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the existing technology, most of them adopt single-dimensional monitoring and threshold alarm, such as smoke meters, temperature meters, circuit breakers, leakage detection and other products. When a fire occurs, the fire information can be monitored at the first time for fire alarm. Technology often has false alarms, missed alarms, or only makes alarms when serious problems occur. If the processing is not timely, it may cause a lot of losses, and bring huge damage to the life safety of personnel and the normal operation of the power system. potential safety hazards, and the above-mentioned existing technologies cannot effectively warn electrical circuit fires. Only when a fire occurs or is approaching, can key information be monitored for remedial measures, and it is impossible to prevent it before it happens.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Artificial intelligence electrical line fire risk real-time early warning method and system
  • Artificial intelligence electrical line fire risk real-time early warning method and system
  • Artificial intelligence electrical line fire risk real-time early warning method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0059] see figure 1 , the application provides an artificial intelligence electrical circuit fire risk real-time early warning method, comprising the following steps:

[0060] S1: Collect multi-dimensional data of each electrical circuit in real time. The multi-dimensional data includes the temperature rise of the measuring point, the temperature rise of the meter box, and the load current. Among them, the temperature rise of the measuring point and the temperature rise of the meter box are obtained through the collection of the temperature field. Point temperature, meter box temperature, ambient temperature;

[0061] S2: Perform abnormal judgment on multi-dimensional data to obtain the abnormal level of each electrical circuit;

[0062] S3: Calculate and obtain the fire warning risk value of each electrical circuit according to the abnormal level of each electrical circuit and the duration of the abnormal level.

[0063] The present embodiment is described in detail now:

...

Embodiment 2

[0113] see Figure 5 , the present application provides a real-time early warning system for artificial intelligence electrical circuit fire risk based on Embodiment 1, including:

[0114] One or more Internet of Things collection and perception terminals 1, the Internet of Things collection and perception terminal includes a load current detection module, a measurement point temperature detection module, a meter box temperature detection module, and an ambient temperature detection module to collect multi-dimensional data of electrical circuits in real time, The multi-dimensional data includes the temperature rise of the measuring point, the temperature rise of the meter box, and the load current. Among them, the temperature rise of the measuring point and the temperature rise of the meter box are obtained through the collection of the temperature field, and the temperature field includes the temperature of the measuring point, the temperature of the meter box, and the ambient...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an artificial intelligence electrical line fire risk real-time early warning method and system, and the method comprises the following steps: collecting multi-dimensional dataof each electrical line in real time, wherein the multi-dimensional data comprising measurement point temperature rise, meter box temperature rise and load current, and the measurement point temperature rise and the meter box temperature rise are obtained through temperature field collection; performing abnormality judgment on the multi-dimensional data to obtain an abnormality level of each electrical circuit; according to the abnormal level of each electrical line and the duration of the abnormal level, calculating to obtain a fire early warning risk value of each electrical line. The systemof the invention comprises one or more Internet of Things acquisition sensing terminals, an intelligent gateway in signal connection with the Internet of Things acquisition sensing terminals, and a data processing server in data communication with the intelligent gateway. The method and the system have the technical characteristics of wide early warning area, high early warning accuracy, high early warning efficiency, real-time early warning and intelligent early warning.

Description

technical field [0001] The invention belongs to the technical field of fire risk early warning, in particular to an artificial intelligence electrical circuit fire risk real-time early warning method and system. Background technique [0002] Fire is a particularly serious disaster phenomenon, and its effective control is an important symbol of social civilization and progress. Among many fire accidents, fires caused by electrical circuit problems occur frequently. According to statistics from the Public Security Fire Bureau, the number of electrical circuit fires accounted for 30% of the total fires from 2011 to 2016. Aging is a constant threat to public safety and social development. Once it occurs, it will cause irreversible consequences to the economy, technological innovation, and historical relics. [0003] In the existing technology, most of them adopt single-dimensional monitoring and threshold alarm, such as smoke meters, temperature meters, circuit breakers, leakag...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G08B31/00G08B17/00G08B17/06G08B17/10G08B21/18
CPCG08B31/00G08B17/00G08B17/06G08B17/10G08B21/185
Inventor 周群力黄宏声黄凤仪
Owner 上海枫昱能源科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products