Power Generator Arc Event Detection via Self-Diagnosis
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Solution Overview
Problem
Current systems for monitoring and maintaining power sources and generators in industrial processes, such as plasma processing, lack effective methods to detect and optimize for arc events, leading to defects and inefficient preventative maintenance schedules.
Innovation Solution
A system that utilizes onboard capabilities of power generators to collect and analyze data on operating characteristics and fault events, determining the magnitude and severity of arcing events, and providing notifications for quality control and maintenance optimization without the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sensors are added to sense process characteristics, then measurement capability is improved, but device complexity and process interference increase
Solution Approach 1:
The power generator performs self-diagnosis by analyzing its own operating data (current, voltage, power) to detect arc events. The existing onboard sensors and control system are utilized to monitor for anomalies indicating arcing, eliminating the need for additional dedicated arc detection sensors.
Solution Approach 2:
The existing power generator control system is made multi-functional by enabling it to perform both its primary power delivery function and secondary arc detection function. The same sensors and processing units that monitor power parameters for control purposes are also used to detect arc events.
2Productivity
If preventative maintenance intervals are extended, then productivity is improved, but reliability decreases
Solution Approach 1:
The system continuously monitors power generator operating characteristics and provides feedback about component health status. By analyzing trends in electrical parameters and detecting anomalies, the system can predict when maintenance is actually needed, allowing maintenance to be scheduled based on actual condition rather than fixed intervals.
Solution Approach 2:
The system performs preliminary detection of degradation trends and predicts potential failures before they occur. By identifying early signs of component deterioration through electrical parameter analysis, maintenance can be scheduled proactively at the optimal time, preventing failures while avoiding unnecessary maintenance.
3Manufacturing precision
If arc events are not detected, then device complexity is reduced, but manufacturing precision deteriorates due to undetected defects
Solution Approach 1:
The power generator autonomously monitors its own operating parameters to detect arc events that could affect product quality. The existing control system analyzes electrical characteristics to identify arcing conditions, providing quality assurance without requiring external monitoring equipment.
Solution Approach 2:
Electrical parameters (current, voltage, power) serve as intermediaries to indirectly detect arc events. Rather than directly sensing physical arc characteristics, the system uses readily available electrical measurements as proxies to infer the presence and severity of arcing conditions.
Data Source
AI summary
A system, method and software for generating and receiving information about the AC, DC, RF, voltage, and other characteristics and information provided by components in a system. The information can provide insight into the operational characteristics and functionality of the components, as well as the process and system the components are being used within. This information may be used for preventative maintenance of the components, and to detect changes, issues, failures, events, problems, etc. in the process and system.