Electric Equipment Ageing Monitoring via Dynamic Environmental Stress
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Solution Overview
Problem
Current methods for monitoring the ageing of electric equipment are not precise and do not account for unpredictable variations in operating conditions, leading to inaccurate predictions of equipment lifespan.
Innovation Solution
A method and device that involve entering and storing ageing computation data, measuring physical quantities such as temperature, humidity, and vibrations, and computing ageing acceleration factors to provide a more accurate evaluation of equipment state, including the computation of mechanical and electronic part ageing, and communication of ageing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional lifetime computation methods are used based on stable operating conditions, then the computation process is simple, but the prediction precision of equipment ageing is poor
Solution Approach 1:
The patent applies dynamics by transitioning from static lifetime computation based on stable conditions to dynamic monitoring that continuously adapts to unpredictable variations in operating conditions. The system computes ageing acceleration factors in real-time based on measured environmental parameters (temperature, humidity, salinity, vibrations) and operational data, allowing the ageing prediction to dynamically reflect actual equipment stress conditions rather than relying on fixed assumptions.
Solution Approach 2:
The patent implements parameter changes by introducing multiple environmental parameters (temperature, humidity, salinity, vibrations) and operational parameters (current values, operation counts) that were previously ignored. These parameters are measured and used to compute ageing acceleration factors, fundamentally changing the computation from a simple time-based model to a multi-parameter stress-based model that accurately reflects real-world equipment degradation.
2Reliability
If linear ageing assumption is made based on initially computed lifetime, then the computation is straightforward, but the realism of ageing prediction is insufficient
Solution Approach 1:
The patent applies feedback by continuously measuring environmental conditions and operational parameters, then using this feedback to compute ageing acceleration factors that adjust the ageing prediction. The system establishes a closed-loop monitoring mechanism where actual operating conditions feed into the computation model, and the results provide feedback on equipment state, enabling realistic prediction that adapts as conditions change throughout the equipment's lifetime.
Solution Approach 2:
The patent implements preliminary action by pre-storing ageing computation data organized by equipment type, which serves as a foundation for subsequent real-time computations. This preliminary preparation of reference data, characteristics, and computation models enables the system to quickly process measured parameters and generate accurate ageing predictions without requiring complex real-time analysis of all possible scenarios.
3Measurement precision
If environmental variations are not considered in lifetime computation, then the computation model is simple, but the accuracy of remaining lifetime evaluation is poor
Solution Approach 1:
The patent applies segmentation by dividing the ageing computation into distinct components: environmental condition monitoring (temperature, humidity, salinity, vibrations), operational parameter monitoring (operation counts, current values), and separate ageing acceleration factor computations for different stress types. This segmentation allows the complex monitoring system to be organized into manageable modules, each measuring specific parameters and contributing to the overall ageing prediction in a structured manner.
Data Source
AI summary
A monitoring method, device, and electric installation for monitoring ageing of at least one electric equipment unit. The monitoring method includes entering and storing ageing computation data by type of equipment, measuring physical quantities representative of environmental conditions of the electric equipment unit, the measuring of the physical quantities including measuring humidity content with a humidity sensor and measuring salinity content with a salinity sensor, computing ageing according to the measured physical quantities including the humidity content and the salinity content, and according to the stored ageing computation data, and generating electric equipment ageing data that indicates the ageing of the electric equipment unit.