High-voltage circuit breaker fault detection method based on convolution nerve network algorithm
A convolutional neural network and high-voltage circuit breaker technology, which is applied to circuit breaker testing, instruments, and electrical measurement, can solve problems such as neural networks not working properly, inability to explain the reasoning process and reasoning basis, and insufficient data.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment
[0139] Take t0 as the zero point of the command time to extract the fault characteristic parameters I1, I2, I3, t1, t2, t3, t4, t5 to monitor the status of the circuit breaker, and obtain ten sets of fault sample data. These ten sets of fault sample data include normal mechanism ( A), the operating voltage is too low (B), the closing iron core is jammed at the beginning (C), the operating mechanism is jammed (D), and the closing iron core empty stroke is too large (E). The data collection status is shown in Table 1. Shown
[0140] Table 1 Failure sample data
[0141]
[0142] The characteristic curve of closing / opening coil current is as Figure 4 As shown, we can see:
[0143] (1) Phase I, t=t0~t1; the coil starts to be energized at t0, and the core starts to move at t1; t0 is the time when the circuit breaker opening and closing commands are issued, and it is the timing starting point for the opening and closing actions of the circuit breaker; T1 is The current and magnetic flux...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com