Infrastructure Operation Data Analysis for Non-Uniform Distribution Detection
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Solution Overview
Problem
Existing infrastructure monitoring systems face challenges in optimizing specification settings and performing statistical analysis on non-uniformly distributed data from facilities that operate continuously, making it difficult to detect abnormalities and perform automatic analysis due to varying conditions such as seasonality and load factors.
Innovation Solution
A system that automatically analyzes infrastructure operation data by determining whether to execute an analysis based on operation state and conditions, calculating statistics for previous and succeeding operation periods, and analyzing significant differences using equality verification, control level verification, and change rate verification, with the ability to set verification boundaries and correct for skewness and kurtosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional statistical methods (t-test, f-test) are used for equality verification, then basic statistical analysis can be performed, but the analysis accuracy is insufficient for non-uniformly distributed infrastructure data with varying seasonal and load factor conditions
Solution Approach 1:
The patent transforms the statistical analysis approach by changing from traditional parametric tests (t-test, f-test) to non-parametric methods (Kolmogorov-Smirnov test, Mann-Whitney U test) that do not assume normal distribution. This parameter change in the statistical methodology enables accurate analysis of non-uniformly distributed infrastructure data while maintaining adaptability to varying seasonal and load factor conditions
Solution Approach 2:
The system dynamically selects appropriate statistical tests based on the characteristics of the input data. The analysis unit determines whether to apply equality verification, control level verification, or change rate verification depending on data distribution patterns, making the analysis method adaptable to different operational conditions and data types
2Productivity
If automatic analysis is executed for continuously operating facilities, then real-time monitoring capability is improved, but false detections increase due to unexpected operation events and temporary non-operation errors
Solution Approach 1:
The system performs preliminary validation checks before executing automatic analysis. The analysis unit verifies whether sufficient operation data has been collected and whether the facility has been operating continuously for the required minimum period. This preliminary action prevents false detections by ensuring data quality and operational stability before analysis begins
Solution Approach 2:
The system incorporates feedback mechanisms where analysis results and operational patterns are continuously monitored. When unexpected operation events or temporary non-operations occur, the system adjusts its analysis parameters and thresholds based on historical patterns, reducing false detections while maintaining real-time monitoring capability
3Measurement precision
If specification settings are customized for different infrastructure types, then analysis accuracy for specific facilities is improved, but the system complexity increases making optimization difficult
Solution Approach 1:
The patent implements a universal analysis framework that can handle multiple infrastructure types (power plants, water treatment facilities, manufacturing facilities) through a single standardized system. The analysis unit automatically adapts to different facility types and sensor configurations without requiring complex custom settings, achieving both detection precision and system simplicity through multi-functional design
Data Source
AI summary
In a system of automatically analyzing infrastructure operation data, the system includes: an infrastructure operation determination unit configured to determine whether or not to execute an automatic analysis on infrastructure operation data; a data reception unit configured to receive operation data of a previous operation period and operation data of a succeeding operation period according to the automatic analysis execution; a statistics calculation unit configured to calculate statistics for the operation data of the previous operation period and the operation data of the succeeding operation period; and a significant difference analysis unit configured to analyze a significant difference between the operation data of the previous operation period and the operation data of the succeeding operation period based on the statistics.