Continuous Air Monitor Radon Compensation via Segmented Statistical Testing
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Solution Overview
Problem
Continuous Air Monitors (CAMs) face challenges in accurately detecting alpha radionuclides due to high background radiation from Radon decay products, leading to false alarms and increased computational complexity in curve fitting and subtraction processes, which affects the reliability and robustness of radiation detection systems.
Innovation Solution
A CAM system that performs channel-by-channel statistical testing to compare measured Alpha counts with expected Radon counts, using the Bethe-Bloch equation to correct for nonlinear energy loss across the air gap, and operates at a fixed probability of false alarms, allowing for simplified software calculations and reduced false alarms by using a rolling Currie violation test.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If curve fitting and subtraction process is used to reject Radon Alpha peaks, then Radon background compensation is achieved, but computational complexity increases and system robustness becomes difficult to demonstrate
Solution Approach 1:
The patent segments the Radon compensation process into distinct energy regions (Region 1: 4.0-6.0 MeV, Region 2: 6.0-8.0 MeV, Region 3: 8.0-10.0 MeV) with representative energy points. Instead of performing curve fitting across the entire spectrum, the system calculates compensation factors for each region separately using pre-defined geometry factors, significantly reducing computational complexity while maintaining accuracy.
Solution Approach 2:
The patent pre-calculates geometry factors for each energy region and representative point during system setup or calibration. These pre-computed factors are stored and reused during operation, eliminating the need for repeated complex curve fitting calculations and reducing real-time computational burden.
2Measurement precision
If alarm level is set low to maximise safety, then detection sensitivity improves, but false alarm rate increases
Solution Approach 1:
The patent changes the parameter used for alarm determination from fixed count thresholds to statistically derived thresholds based on the standard deviation of residual counts. The alarm level is dynamically set at k × σ_residual, where k is a multiplier (typically 3-5) that controls the false alarm rate. This allows the system to maintain high sensitivity while controlling false alarms through statistical rather than arbitrary thresholds.
Solution Approach 2:
The system continuously monitors the residual counts and their statistical properties (mean and standard deviation) and uses this feedback to dynamically adjust alarm thresholds. The alarm criterion is based on the number of standard deviations the residual exceeds zero, creating a feedback-based adaptive threshold that maintains optimal sensitivity while controlling false alarm rates.
3Reliability
If alarm level is set high to minimise false alarms, then system reliability improves, but detection sensitivity decreases
Solution Approach 1:
The patent enables flexible adjustment of the k multiplier parameter that controls the balance between sensitivity and false alarm rate. By changing this single parameter, users can optimize the system for either maximum sensitivity (lower k) or minimum false alarms (higher k) depending on operational requirements, without sacrificing either performance metric entirely.
4Measurement precision
If least squares technique is used for curve fitting, then measurement accuracy is maximised, but computational intensity increases
Solution Approach 1:
The patent divides the spectrum into discrete energy regions with representative points, allowing the use of simplified linear interpolation or lookup tables instead of full least squares curve fitting. This segmentation approach maintains adequate accuracy while dramatically reducing computational intensity for real-time operation.
Solution Approach 2:
The patent pre-computes geometry factors and compensation values during system initialization or calibration, storing them for direct lookup during operation. This preliminary action eliminates the need for repeated computationally intensive curve fitting during real-time monitoring, improving computational efficiency while maintaining accuracy through the use of pre-validated factors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves improved immunity to false alarms, reduces computational complexity, and allows for consistent operation at an As Low As Reasonably Practicable (ALARP) level, eliminating the need for empirical alarm level setting in each location, enhancing detection sensitivity and reducing hardware and software requirements.
Implementation Method 1
A semiconductor detector faces the dust and monitors Alpha activity
Implementation Method 2
A pump draws air at a known rate through a filter, thus trapping dust on the filter
Implementation Method 3
Buildings emit Radon gas that decays to solid radioactive daughters which are trapped on the dust filter
Implementation Method 4
using the Bethe-Bloch equation to correct for nonlinear energy loss across the air gap
Data Source
Figure 1~6
Figure 2~3
Figure 4
AI summary
The invention provides for a continuous air monitor for detecting Alpha emitting radionuclides. The monitor measures and records the energy of each detected Alpha count in one of a plurality of channels and compensates for counts due to the presence of Radon. It does this by carrying out a channel by channel statistical test comparing the measured count in each channel to the expected count due to radon daughter products, and determining if any deviation from the expected count is statistically significant.