Multi-Leaf Collimator Condition Monitoring via Current Sensing
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Solution Overview
Problem
Radiotherapy machines experience downtime due to unpredictable component degradation, leading to inconvenient and costly interruptions in treatment sessions, as existing predictive maintenance methods struggle to accurately identify and diagnose issues in the complex data generated by these machines.
Innovation Solution
A method for remotely evaluating the condition of beam limiting device components, such as multileaf collimators, by analyzing sensor data to determine when replacement or repair is necessary, allowing for scheduled maintenance and reducing downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing predictive maintenance methods are applied to radiotherapy machines, then maintenance scheduling may be improved, but the complexity of analyzing the large volume of sensor data from complex machines makes fault identification difficult
Solution Approach 1:
The patent introduces an intermediary system that acts as a bridge between the radiotherapy machine and maintenance personnel. This intermediary automatically collects sensor data, processes it through analysis algorithms, and presents simplified maintenance recommendations, thereby reducing the complexity burden on both the data analysis process and the end users while maintaining reliable predictive maintenance capabilities
2Ease of repair
If field service engineers are dispatched to diagnose faults after safety overrides occur, then fault resolution can be performed, but significant machine downtime is caused due to delayed detection and time-consuming on-site diagnostics
Solution Approach 1:
The patent implements preliminary action by continuously monitoring sensor data and automatically detecting fault conditions before they cause safety overrides or complete machine failures. The system performs preliminary diagnosis and prepares maintenance recommendations in advance, allowing scheduled maintenance during convenient downtime rather than causing unplanned interruptions to treatment schedules
3Productivity
If remote diagnostic techniques are used to assess component condition, then machine downtime may be reduced, but the abundance of data and complex interrelationships between components make remote fault determination non-trivial
Solution Approach 1:
The patent implements feedback mechanisms where sensor data from various components is continuously collected and fed into analysis algorithms that compare current readings against historical data and expected patterns. The system provides feedback loops that automatically update component health assessments and generate maintenance recommendations, making remote fault determination systematic and reliable rather than relying on manual analysis of complex data interrelationships
Data Source
AI summary
Disclosed herein is a method of determining whether repair or replacement of a multi-leaf collimator for a radiotherapy device should be scheduled. The multi-leaf collimator comprises a leaf bank comprising a plurality of leaves, a leaf bank support configured to support the leaf bank, a leaf bank guide, and a guide actuation means configured to extend the leaf bank along the leaf bank guide into the path of a radiation beam. The device further comprises current sensing means configured to produce a signal indicative of the current supplied to the guide actuation means. The method comprises receiving signals from the current sensing means; processing the signals; and based on the processing, determining whether repair or replacement of the multi-leaf collimator should be scheduled.