Electrical System Residual Lifetime Prediction Using Load Spectra
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Solution Overview
Problem
Current methods for predicting the residual lifetime of electrical systems, such as switchgear, are costly and time-consuming, often relying on expensive scheduled downtime and destructive tests, with maintenance planning being challenging due to unknown safe service times and large safety margins.
Innovation Solution
An apparatus comprising an input unit for sensor data from sensors measuring physical parameters of electrical system components, a processing unit that assigns data to classes and determines a load spectrum, and applies aging models to predict the residual lifetime of components, enabling continuous and accurate maintenance planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scheduled maintenance is performed at regular intervals to ensure safety, then system reliability is improved, but maintenance costs and downtime increase
Solution Approach 1:
The patent transitions from fixed-time maintenance intervals to condition-based maintenance by continuously monitoring physical parameters (temperature, humidity, vibration, current) of electrical components. The processing unit analyzes these parameters to determine actual component condition and predicts residual lifetime, enabling maintenance to be performed based on real component state rather than predetermined schedules, thus reducing unnecessary maintenance costs while maintaining reliability
Solution Approach 2:
The system implements continuous feedback through sensors that monitor component parameters in real-time. The processing unit receives sensor data, analyzes component condition, and provides feedback about predicted residual lifetime and maintenance needs. This closed-loop feedback enables dynamic adjustment of maintenance schedules based on actual component degradation, optimizing the balance between reliability and maintenance costs
2Measurement precision
If thorough inspections are performed at regular intervals to predict residual lifetime, then prediction accuracy is improved, but inspection costs and downtime increase
Solution Approach 1:
The system replaces periodic thorough inspections with continuous monitoring of component parameters through sensors. The processing unit continuously analyzes sensor data to track component degradation in real-time, providing ongoing prediction of residual lifetime without requiring scheduled shutdowns for inspection. This continuous action maintains high prediction accuracy while eliminating the time loss associated with periodic inspections
Solution Approach 2:
The patent replaces manual thorough inspections with automated sensor-based monitoring and electronic data processing. Sensors continuously measure physical parameters, and the processing unit automatically analyzes this data to predict residual lifetime, substituting mechanical inspection processes with electronic measurement and computation systems, thereby improving prediction accuracy while reducing inspection time and costs
3Reliability
If large safety margins are applied in device design to ensure reliability, then system reliability is improved, but device cost increases
Solution Approach 1:
The system replaces static safety margins with dynamic condition monitoring and prediction. Instead of designing components with fixed oversized safety margins, the system continuously monitors actual component parameters and adjusts maintenance and operational decisions based on real-time condition assessment. This dynamic approach allows for optimized component design with appropriate safety margins while maintaining reliability through active monitoring and predictive maintenance
Data Source
AI summary
An apparatus for prediction of the residual lifetime of an electrical system includes: an input unit; a processing unit; and an output unit. The input unit provides at least one sensor data from at least one sensor to the processing unit, the at least one sensor data including a measurement of at least one physical parameter of at least one component of an electrical system. Each sensor data is associated with a corresponding sensor and relates to a measurement of one physical parameter of a corresponding component of the electrical system. Each sensor data extends over a plurality of time windows and is assigned to a certain data class, such that sensor data at a particular time window has a value that falls into one of the data classes. For each sensor data the processing unit assigns the sensor data at each time window into a corresponding measurement window.