LIDAR Gas Plume Detection With Adaptive Speckle Noise Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing gas concentration measurement technologies face challenges in accurately distinguishing between anomalous gas concentrations and noise, leading to high false positive rates and missed detections, particularly in varying ambient conditions.
Innovation Solution
A method and apparatus using a light detection and ranging (LIDAR) system with adaptive thresholding and speckle noise modeling to filter out noise and identify gas plumes, incorporating plume detection to enhance confidence in anomalous gas concentration measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If passive remote sensors are used for large-area gas concentration measurements, then high measurement rates and rapid area coverage are achieved, but detection reliability, sensitivity, and false positive rates deteriorate
Solution Approach 1:
The patent introduces an adaptive thresholding mechanism that acts as an intermediary between the passive sensor measurements and the final detection output. This threshold dynamically adjusts based on ambient conditions and noise levels, filtering out false positives while preserving true detections, thereby improving detection reliability without sacrificing the high measurement rates of passive sensors
Solution Approach 2:
The patent implements dynamic threshold adjustment based on real-time noise modeling and ambient conditions. The detection threshold is not fixed but adapts continuously to changing environmental factors, allowing the system to maintain high sensitivity during favorable conditions while filtering noise during challenging conditions, thus resolving the contradiction between measurement rate and detection reliability
2Productivity
If passive remote sensors are used for large-area gas concentration measurements, then rapid area coverage is achieved, but sensitivity and false positive rates worsen
Solution Approach 1:
The patent performs preliminary noise characterization and threshold calibration before actual gas detection measurements. By pre-modeling the noise properties of the passive sensor system under various ambient conditions, the system establishes appropriate detection thresholds in advance, enabling sensitive detection without requiring post-processing adjustments that would slow down area coverage
3Measurement precision
If active LIDAR sensors are used for gas concentration measurements, then detection sensitivity and spectral selectivity are improved, but device complexity increases
Solution Approach 1:
The patent extracts and processes only the specific spectral signatures of target gases from the LIDAR return signals, rather than analyzing the entire spectrum. By focusing computational resources on the relevant absorption lines and using targeted detection algorithms, the system achieves high sensitivity for specific gas species while reducing overall computational complexity compared to full-spectrum analysis
4Reliability
If adaptive thresholding with noise modeling is applied to filter measurements, then false positives are reduced, but processing complexity increases
Solution Approach 1:
The patent changes the parameters of the threshold from fixed to adaptive, where the threshold value is dynamically adjusted based on modeled noise characteristics. By parameterizing the threshold in terms of noise standard deviations or signal-to-noise ratios, the system achieves sophisticated false positive filtering through relatively simple computational operations that scale with the data size
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
Enhances the detection of anomalous gas concentrations by reducing false positives and negatives, allowing for precise localization and quantification of gas leaks.
Implementation Method 1
lidar techniques such as wavelength modulation spectroscopy (WMS), differential absorption lidar (DIAL) and tunable diode laser absorption spectroscopy (TDLAS)
Implementation Method 2
obtaining, using a light detection and ranging (LIDAR) system, a set of gas concentration measurements from a target area
Data Source
AI summary
Embodiments of the disclosure are drawn to apparatuses and methods for anomalous gas concentration detection. A spectroscopic system, such as a wavelength modulated spectroscopy (WMS) system may measure gas concentrations in a target area. However, noise, such as speckle noise, may interfere with measuring relatively low concentrations of gas, and may lead to false positives. A noise model, which includes a contribution from a speckle noise model, may be used to process data from the spectroscopic system. An adaptive threshold may be applied based on an expected amount of noise. A speckle filter may remove measurements which are outliers based on a measurement of their noise. Plume detection may be used to determine a presence of gas plumes. Each of these processing steps may be associated with a confidence, which may be used to determine an overall confidence in the processed measurements/gas plumes.