GB/T 40285-2021 in English
VALIDTechnical specification for dam safety analysis and evaluation system of smart hydropower plant
- Issued on:2021-05-21
- Implemented on:2021-12-01
- File Format:PDF
- Delivery:Via email within 1~3 business days
$185.00
| Standard No: | GB/T 40285-2021 |
| Document status: | VALID |
| Title in English: | Technical specification for dam safety analysis and evaluation system of smart hydropower plant |
| Title in Chinese: | 智能水电厂大坝安全分析评估系统技术规范 |
| Language: | English |
| File Format: | Electronic (PDF) |
| Delivery: | Via email within 1~3 business days |
| Issued on: | 2021-05-21 |
| Implemented on: | 2021-12-01 |
| ICS Classification: | 27.140-Hydraulic energy engineering |
| Chinese Classification: | F07-Computer application |
| Professional Classification: | GB-National Standard |
| Related Keywords: | dam safety analysis
smart hydropower plant introduction analysis hybrid model analysis evaluation system regression analysis |
| Related Topics: | full analysis
the dam Dam Standard hydropower plant evaluation system High Energy Analysis System Systematic analysis of the atmosphere High Energy Analysis System Performance Analysis Evaluation GBT40285 GB/T 40285-2021 Smart power plant |
《GB/T 40285-2021智能水电厂大坝安全分析评估系统技术规范》由524（中国电力企业联合会）归口，主管部门为中国电力企业联合会。
Introduction
Analysis of the standard technical framework
This standard builds a three-layer technical architecture including monitoring data acquisition equipment, analysis and evaluation components, and integrated management and control platform. The system needs to realize the full process automation from data acquisition to safety warning, among which the core indicators such as gross error identification precision ≥ 95% and abnormal diagnosis response time ≤ 3 minutes are directly related to the system reliability.
Intelligent grading system
| Grading dimensions | Primary intelligence | Intermediate intelligence | Advanced intelligence |
|---|---|---|---|
| Diagnosis compliance rate | Human-led | ≥80% expert compliance rate | ≥90% expert compliance rate |
| Learning ability | Preset rules | Automatic parameter optimization | Knowledge base self-evolution |
| Response speed | 5 minutes | 3 minutes | Real-time warning |
Key technical implementation points
1. Multi-source data fusion
Taking the Three Gorges Project as an example, the system needs to integrate data from 12 types of monitoring equipment, such as piezometers and GNSS monitoring stations, and achieve normalization of heterogeneous data through the data cleaning process specified in Appendix B.
2. Abnormal diagnosis algorithm
When using hybrid model analysis, it should be combined with:
- Statistical model (regression analysis)
- Deterministic model (finite element simulation)
- Machine learning (LSTM time series prediction)
Network security protection requirements
According to GB/T36572, the system needs to achieve:
- One-way transmission isolation of monitoring data
- Digital signature verification of assessment results
- Access control Level 3 security protection certification
Standard Evolution Trend
Compared with the 2015 version of the industry standard, this specification has the following major breakthroughs:
- Added BIM+GIS 3D visualization requirements
- Clarified the application of machine learning in parameter inversion
- Refine the evaluation time efficiency indicators under extreme working conditions (completed within 30 minutes)
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