SEARCH · Engineering Papers

Results for “DETECTION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19

All sources NASA NTRS DOE OSTI

NASA NTRS2010

Automated Detection of Oscillating Regions in the Solar Atmosphere

Recently observed oscillations in the solar atmosphere have been interpreted and modeled as magnetohydrodynamic wave modes. This has allowed for the estimation of parameters that are otherwise hard to derive, such as the coronal magnetic-field strength. This work crucially relies on the initial detection of the oscillations, which is commonly done manually. The volume of Solar Dynamics Observatory (SDO) data will make manual detection inefficient for detecting all of the oscillating regions. An algorithm is presented that automates the detection of areas of the solar atmosphere that support spatially extended oscillations. The algorithm identifies areas in the solar atmosphere whose oscillation content is described by a single, dominant oscillation within a user-defined frequency range. The method is based on Bayesian spectral analysis of time series and image filtering. A Bayesian approach sidesteps the need for an a-priori noise estimate to calculate rejection criteria for the observed signal, and it also provides estimates of oscillation frequency, amplitude, and noise, and the error in all of these quantities, in a self-consistent way. The algorithm also introduces the notion of quality measures to those regions for which a positive detection is claimed, allowing for simple post-detection discrimination by the user. The algorithm is demonstrated on two Transition Region and Coronal Explorer (TRACE) datasets, and comments regarding its suitability for oscillation detection in SDO are made.

Ireland, J.↗

NASA NTRS2004

Oligodeoxynucleotide Probes for Detecting Intact Cells

A rapid, sensitive test using chemiluminescent oligodeoxynucleotide probes has been developed for detecting, identifying, and enumerating intact cells. The test is intended especially for use in detecting and enumerating bacteria and yeasts in potable water. As in related tests that have been developed recently for similar purposes, the oligodeoxynucleotide probes used in this test are typically targeted at either singlecopy deoxyribonucleic acid (DNA) genes (such as virulence genes) or the multiple copies (10,000 to 50,000 copies per cell) of 16S ribosomal ribonucleic acids (rRNAs). Some of those tests involve radioisotope or fluorescent labeling of the probes for reporting hybridization of probes to target nucleic acids. Others of those tests involve labeling with enzymes plus the use of chemiluminescent or chromogenic substrates to report hybridization via color or the emission of light, respectively. The present test is of the last-mentioned type. The chemiluminescence in the present test can be detected easily with relatively simple instrumentation. In developing the present test, the hybridization approach was chosen because hybridization techniques are very specific. Hybridization detects stable, inheritable genetic targets within microorganisms. These targets are not dependent on products of gene expression that can vary with growth conditions or physiological states of organisms in test samples. Therefore, unique probes can be designed to detect and identify specific genera or species of bacteria or yeast (in terms of rRNA target sequences) or can be designed to detect and identify virulence genes (genomic target sequences). Because of the inherent specificity of this system, there are few problems of cross-reactivity. Hybridization tests are rapid, but hybridization tests now available commercially lack sensitivity; typically, between 10(exp 6) and 10(exp 7) cells of the target organism are needed to ensure a reliable test. Consequently, the numbers of target bacteria in samples are usually amplified by overnight pre-enrichment growth. These tests are usually performed in laboratories by skilled technicians. The present test was designed to overcome the shortcomings of the commercial hybridization tests. The figure summarizes the major steps of the test. It is important to emphasize that the hybridization process used in this test differs from that of other hybridization tests in that it does not extract target nucleic acids. This process is based on intact-cell hybridization (so-called in situ hybridization ), wherein the intact cells act as immobilizing agents. The cells are identified and enumerated by measuring the chemiluminescence emitted from alkaline phosphatase-probe (AP-probe) hybridization; the chemiluminescence is detected or measured by use of photographic film or a luminometer, respectively.

Rosson, Reinhardt A.↗

NASA NTRS2012

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗

NASA NTRS2013

Radio Detection of the Fermi-LAT Blind Search Millisecond Pulsar J1311-3430

We report the detection of radio emission from PSR J1311.3430, the first millisecond pulsar (MSP) discovered in a blind search of Fermi Large Area Telescope (LAT) gamma-ray data. We detected radio pulsations at 2 GHz, visible for less than 10% of approximately 4.5 hr of observations using the Green Bank Telescope (GBT). Observations at 5 GHz with the GBT and at several lower frequencies with Parkes, Nan cay, and the Giant Metrewave Radio Telescope resulted in non-detections. We also report the faint detection of a steep spectrum continuum radio source (0.1 mJy at 5 GHz) in interferometric imaging observations with the Jansky Very Large Array. These detections demonstrate that PSR J1311.3430 is not radio quiet and provide additional evidence that radio-quiet MSPs are rare. The radio dispersion measure of 37.8 pc cm(exp -3) provides a distance estimate of 1.4 kpc for the system, yielding a gamma-ray efficiency of 30%, typical of LAT-detected MSPs. We see apparent excess delay in the radio pulses as the pulsar appears from eclipse and we speculate on possible mechanisms for the non-detections of the pulse at other orbital phases and observing frequencies.

Ray, P. S.↗

NASA NTRS2015

The Investigation of Perchlorate/Iron Phase Mixtures as A Possible Source of Oxygen Detected by the Sample Analysis at Mars (SAM) Instrument in Gale Crater, Mars

The Sample Analysis at Mars (SAM) instrument onboard the Curiosity rover detected O2 and HCl gas releases from the Rocknest (RN) eolian bedform and the John Klein (JK) and Cumberland (CB) drill hole materials in Gale Crater. Chlorinated hydrocarbons have also been detected by the SAM quadrupole mass spectrometer (QMS) and gas chromatography/mass spectrometer (GCMS). These detections along with the detection of perchlorate (ClO4-) by the Mars Phoenix Lander's Wet Chemistry Laboratory (WCL) suggesting perchlorate is a possible candidate for evolved O2 and chlorine species. Laboratory thermal analysis of individual per-chlorates has yet to provide an unequivocal temperature match to the SAM O2 and HCl release data. These detections along with the detection of perchlorate (ClO4-) by the Mars Phoenix Lander's Wet Chemistry Laboratory suggested perchlorate is a possible candidate for evolved O2 and chlorine species. Laboratory thermal analysis of pure perchlorates has yet to provide an unequivocal temperature match to the SAM O2 and HCl release data. Analog laboratory analysis of iron mineralogy detected in Gale materials that was physically mixed with Ca- and Mg-perchlorate has been shown to catalyze lower O2 release temperatures and approach some SAM O2 release data. Instead of physical mixtures used in previous work, the work presented here utilized perchlorate solutions added to Fe phases. This technique allowed for perchlorate to come in closer contact with the Fe-phase and may more closely mimic Mars conditions where humidity can increase enough to cause deliquescence of the highly hygroscopic perchlorate phases. The objective of this work is to: 1) Utilize a laboratory SAM analog instrument to evaluate the O2 release temperatures from Mg- and Ca-perchlorates solutions applied to Fephases detetected in Gale Crate; and 2) Determine if perchlorate solutions can provide improved matches with the SAM O2 temperature release profiles.

Sutter, B.↗

NASA NTRS2015

Detection of Operator Performance Breakdown as an Automation Triggering Mechanism

Performance breakdown (PB) has been anecdotally described as a state where the human operator "loses control of context" and "cannot maintain required task performance." Preventing such a decline in performance is critical to assure the safety and reliability of human-integrated systems, and therefore PB could be useful as a point at which automation can be applied to support human performance. However, PB has never been scientifically defined or empirically demonstrated. Moreover, there is no validated objective way of detecting such a state or the transition to that state. The purpose of this work is: 1) to empirically demonstrate a PB state, and 2) to develop an objective way of detecting such a state. This paper defines PB and proposes an objective method for its detection. A human-in-the-loop study was conducted: 1) to demonstrate PB by increasing workload until the subject reported being in a state of PB, and 2) to identify possible parameters of a detection method for objectively identifying the subjectively-reported PB point, and 3) to determine if the parameters are idiosyncratic to an individual/context or are more generally applicable. In the experiment, fifteen participants were asked to manage three concurrent tasks (one primary and two secondary) for 18 minutes. The difficulty of the primary task was manipulated over time to induce PB while the difficulty of the secondary tasks remained static. The participants' task performance data was collected. Three hypotheses were constructed: 1) increasing workload will induce subjectively-identified PB, 2) there exists criteria that identifies the threshold parameters that best matches the subjectively-identified PB point, and 3) the criteria for choosing the threshold parameters is consistent across individuals. The results show that increasing workload can induce subjectively-identified PB, although it might not be generalizable-only 12 out of 15 participants declared PB. The PB detection method based on signal detection analysis was applied to the performance data and the results showed that PB can be identified using the method, particularly when the values of the parameters for the detection method were calibrated individually.

multi-task environment↗

NASA NTRS2015

Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of commercial aviation on climate change. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. A set of contrail masks of varying sensitivity is produced to define the potential range of uncertainty in contrail coverage estimated by the CDA. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO GEOS-4 reanalysis has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from several months of MODIS observations during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data.

Duda, David P.↗

NASA NTRS2019

Lipid Decontamination Procedures for Life Detection Missions

Molecular biosignatures are key targets for current, proposed, and future life detection missions. With the high accuracy and low limit of detection (LOD) that new and future instruments will require, decontamination of life detection hardware is necessary to prevent false positives. Lipids are a molecular biosignature of interest, as they are ubiquitous to all life as we know it, can survive unaltered in the geologic record for longer than any other biomolecule (i.e. billions of years), and form through both biotic and abiotic processes. Lipids display origin-diagnostic molecular patterns that can reveal biotic or abiotic synthesis, so finding them and ascertaining their molecular features is important for potentially detecting evidence of life elsewhere. Traditional methods of decontamination, or contamination control (CC), primarily clean hardware through fabrication in sterile (cleanroom) environments, killing microbes, and removing/flushing contaminants off instrument and spacecraft components. However, research suggests that some standard cleaning methods are either unlikely to remove lipid contaminants or are incompatible with life detection instrument materials. To solve this problem, I propose to find, test, and verify a decontamination method that thoroughly cleans instruments by destroying lipid molecules, but is simultaneously compatible with major materials used in these instruments. I will study the effects of traditional CC methods (including Dry Heat Microbial Reduction and Vapor phase Hydrogen Peroxide) and experimental CC methods (Electron Beam Irradiation) on lipid molecules for application to life detection instrumentation. I will then develop a CC plan for a novel lipid detector (ExCALiBR, Extractor for Chemical Analysis of Lipid Biomarkers in Regolith) searching for lipids in either soil or icy world scenarios. This plan will uphold planetary protection regulation requirements and validate experimental analyses of in-situ life detection tests.

Decontamination↗

NASA NTRS2020

First Detections of Dichlorobenzene Isomers and Trichloromethylpropane from Organic Matter Indigenous to Mars Mudstone in Gale Crater, Mars: Results from the Sample Analysis at Mars Instrument Onboard the Curiosity Rover

Chromatographic analysis of the Cumberland mudstone in Gale crater by the Sample Analysis at Mars (SAM) instrument revealed the detection of two to three isomers of dichlorobenzene. Their individual concentrations were estimated to be in the 0.5–17 ppbw range relative to the sample mass. We also report the first detection of trichloromethylpropane and the confirmation of the detection of chlorobenzene previously reported. Supporting laboratory experiments excluded the SAM internal background as the source of those compounds, thus confirming the organic carbon and chlorine of the newly detected chlorohydrocarbons are indigenous to the mudstone sample. Laboratory experiments also demonstrated that the chlorohydrocarbons were mainly produced from chemical reactions occurring in the SAM ovens between organic molecules and oxychlorines contained in the sample. The results we obtained show that meteoritic organics and tested chemical species (a polycyclic aromatic hydrocarbon, an amino acid, and a carboxylic acid) were plausible organic precursors of the chlorinated aromatic molecules detected with SAM, thus suggesting that they could be among the organic molecules present in the mudstone. Results from this study coupled with previously reported detections of chlorinated aromatics (<300 ppbw) indigenous to the same mudstone highlight that organics can be preserved from the harsh surface conditions even at shallow depth. The detection of new chlorohydrocarbons with SAM confirms that organic molecules should have been available in an environment favorable to life forms, strengthening the habitability aspect of Gale crater. Key Words: Mars—Chlorinated organic molecules—In situ measurements—Sample Analysis at Mars— Mudstone—Gale crater. Astrobiology 20, 292–306.

Szopa, Cyril↗

NASA NTRS2024

Considerations for Qualifying Reliable Eddy Current Array Technique for Detection of Backwall Cracks

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection(POD) with 95% confidence for detection of cracklike flaws of a qualified size. In this case, the flaws are on backside of material. Eddy current array (ECA) probe or a single sensor eddy current probe in c-scanning mode is used for the flaw detection. Here, two geometries are considered for the test specimens. The two geometries are, a flat plate, and tube or pipe. The probe is assumed to be on outer diameter (OD)surface and the flaw is assumed to be at the inner diameter (ID) surface for tube inspection. The flaw and probe are on opposite side of wall thickness for inspection of plate material. The application may be used for acreage inspection or just for inspection of butt weld and heat affected zone (HAZ) in a tube, cylinder, or plate. The proposed approach is based on developing an instrument standardization or calibration procedure. Decision threshold of inspection procedure is determined using empirical qualification and noise data. The work explores essential parameters that are required to meet certain conditions to ensure reliable flaw detection. Physics-based simulation of eddy current array flaw detection is used to understand effect of essential parameters on signal response (amplitude and phase),and therefore flaw detectability. Simulation data is used to justify choice of calibration reference standard requirements and the qualification approach. An ECA technique qualification model is provided. The paper gives brief description of tasks to be completed for qualifying ECA technique for reliable detection of cracklike flaws.

Eddy current array inspection, nondestructive eval↗

DOE OSTI2020

Secured fault detection in a power substation

Systems and methods for fault detection and protection in electric power systems that evaluates electromagnetic transients caused by faults. A fault can be detected using sampled data from a first monitored point in the power system. Detection of fault transients and associated characteristics, including transient direction, can also be extracted through evaluation of sample data from other monitored points in the power system. A monitoring device can evaluate whether to trip a switching device in response to the detection of the fault and based on confirmation of an indication of detection of fault transients at the other monitored points of the power system. The determination of whether to trip or activate the switching device can also be based on other factors, including the timing of receipt of an indication of the detection of the fault transients and/or an evaluation of the characteristics of the detected transients.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

The NREL Sensor Laboratory: Status and Future Directions for Hydrogen Detection

The NREL Hydrogen Sensor Laboratory was commissioned in 2010 as a resource for the national and international hydrogen community to ensure the availability and proper use of hydrogen sensors. Since then, the Sensor Laboratory has provided unbiased verification of hydrogen sensor performance for sensor developers, end-users, and regulatory agencies and has also provided active support for numerous code and standards development organizations. Although sensor performance assessment remains a core capability, the mission of the NREL Sensor Laboratory has expanded toward a more holistic approach regarding the role of hydrogen detection and its implementation strategy for both assurance of facility safety as well as for process control applications. Active monitoring for detection of unintended releases has been identified by the NFPA 2 Storage Task Group as a viable approach for improving facility safety and lowering setbacks. The current research program for the Sensor Laboratory addresses both conventional and advanced developing detection strategies in response to the emerging large-scale markets, such as those envisioned by H2@Scale. These emerging hydrogen applications may require alternative detection strategies that supplement and may ultimately supplant the use of traditional sensors for monitoring hydrogen releases. Research focus areas for the NREL Sensor Laboratory now encompasses the characterization of released hydrogen behavior to optimize detection strategies for both indoor and outdoor applications, advanced methods of hydrogen leak detection such as hydrogen wide area monitoring approaches for large scale and distributed applications, the incorporation of active monitoring as a risk reduction strategy to improve safety at hydrogen facilities, and continuing support of hydrogen safety codes and standards. In addition to assurance of safety, detection will be critical for process control applications, such as hydrogen fuel quality verification for fuel cell vehicle applications and for monitoring and controlling of hydrogen-natural gas blend composition.

codes and standards↗

DOE OSTI2023

Secured fault detection in a power substation

Cui, Tao↗

DOE OSTI2024

Multi-channel optical detection system and method for multi-chamber assays

A multi-channel optical detection system includes a base unit adapted to receive a multi-chamber assay cartridge having a plurality of reaction chambers loaded with a sample and an optical detection reagent, and an optical detection unit having a multi-channel optical block having a plurality of detection channels each with an associated light source, and an optic sensor. The optical detection unit is connectable to the base unit so that interrogation ports of the detection channels are optically aligned with optically transparent windows of the reaction chambers of a loaded cartridge, so that upon initialization, light sources are activated to interrogate reaction products in the reaction chambers and detect the optical responses therefrom.

Dugan, Lawrence C.↗

DOE OSTI2021

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

42 ENGINEERING↗

DOE OSTI2022

The Use of Thermal Cameras for Pedestrian Detection

Visible-range camera sensors have been widely used for pedestrian detection. However, most of the methods, which employ visible-range color cameras, do not perform well under low-light and no-light conditions, e.g. during night time. Since the working principle of thermal camera sensors is mainly based on temperature and not light, they have been employed for person detection to overcome the drawbacks of visible-range sensors under these conditions. Every object gives off thermal energy, which is captured by a thermal camera sensor. When an object becomes hotter, it emits more thermal energy, and is therefore captured as much brighter or vice versa. Yet, compared to visible-range cameras, there are many additional challenges that need to be addressed when detecting pedestrians from thermal camera images. These challenges include bright hot objects close to humans, similar pixel values in an image due to weather conditions, or objects that block thermal cameras such as concrete or glass. Glass acts like a mirror for infrared radiation and reflects whatever is in front of the camera. Thus, novel methods are still required to accomplish pedestrian detection task from thermal camera images. To contribute to these efforts, we propose a new method and a modified object detection network incorporating saliency maps of thermal camera images. The features obtained from thermal images and their corresponding saliency maps are combined to obtain richer representations of pedestrian regions, and better detection performance. We perform extensive evaluations on five different datasets to compare the performance of the proposed approach with two baselines. Moreover, we evaluate and compare the transferability of these approaches by doing leave-one-out cross validation across different datasets. Furthermore, the results show that the proposed approach outperforms the baselines, and has better transferability properties across different thermal image datasets.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Evaluation of Station Performance of the Idaho National Laboratory Seismic Monitoring Network Using Network Detection Thresholds

The Idaho National Laboratory (INL) Seismic Monitoring Network is located in eastern Idaho and monitors a portion of the intermountain seismic belt. It has been in place for 50 yr and has undergone several major changes, the most recent of which has been the transition to the Antelope real‐time acquisition system and the implementation of automatic phase picking algorithms to aid in analysis. This study discusses the efforts to evaluate the performance of the INL seismic monitoring network (and other surrounding stations) using the new real‐time acquisition system. The method outlined by Wilson et al. (2021) is used to develop an empirical relationship between the observability of local earthquakes as a function of magnitude and distance. This relationship is used to produce detection thresholds for Pwaves for all stations of interest. The INL seismic network has two main goals: monitor tectonic‐and volcanic‐related events and measure ground motions for input into seismic hazard analysis. Because of these two overall objectives, several seismic stations have been installed near critical facilities and, therefore, are not as quiet as stations that are used primarily for earthquake detection. This is reflected in their detection thresholds, which are much smaller for stations away from facilities. This study shows that the INL Seismic Monitoring Network is able to detect earthquakes near INL facilities with M L > 1.2, with redundancies built in to ensure this sensitivity even if data became unavailable from some stations. This study also shows “holes” in the monitoring network where the detection of smaller earthquakes is highly dependent on sparsely placed seismic stations. In conclusion, the results of this study will be used to govern plans for expansion of earthquake monitoring in Idaho and the surrounding region and to fine‐tune the detection thresholds for individual stations.

58 - GEOSCIENCES↗

DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗