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Patent Agency Ranking
公开(公告)号：US11933774B1
公开(公告)日：2024-03-19
申请号：US18060111
申请日：2022-11-30
Applicant: Picarro Inc.
Inventor： Sean MacMullin , Chris W. Rella , Aaron Van Pelt , Alex Balkanski , Yonggang He , Sze M. Tan , David Steele , Tim Clark
CPC classification number: G01N33/0075 , G01M3/04 , G01N33/0047
Abstract: In some embodiments, data from multiple vehicle-based natural gas leak detection survey runs are used by computer-implemented machine learning systems to generate a list of natural gas leaks ranked by hazard level. A risk model embodies training data having known hazard levels, and is used to classify newly-discovered leaks. Hazard levels may be expressed by continuous variables, and/or probabilities that a given leak fits within a predefined category of hazard (e.g. Grades 1-3). Each leak is represented by a cluster of leak indications (peaks) originating from a common leak source. Hazard-predictive features may include maximum, minimum, mean, and/or median CH4/amplitude of aggregated leak indications; estimated leak flow rate, determined from an average of leak indications in a cluster; likelihood of leak being natural gas based on other indicator data (e.g. ethane concentration); probability the leak was detected on a given pass; and estimated distance to leak source.
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公开(公告)号：US10962438B2
公开(公告)日：2021-03-30
申请号：US16826265
申请日：2020-03-22
Applicant: Picarro Inc.
Inventor： David Steele , Chris W. Rella , Sze M. Tan , Aaron Van Pelt
Abstract: In some embodiments, a natural gas leak detection system generates display content including indicators of remote and local potential leak source areas situated on a map of an area of a gas concentration measurement survey performed by a vehicle-borne device. The remote area may be shaped as a wedge extending upwind from an associated gas concentration measurement point. The local area graphically represents a potential local leak source area situated around the gas concentration measurement point, and having a boundary within a predetermined distance (e.g. 10 meters) of the gas concentration measurement point. The local area may be represented as a circle, ellipse, or other shape, and may include an area downwind from the measurement point. Size and/or shape parameters of the local area indicator may be determined according to survey vehicle speed and direction data, and/or wind speed and direction data characterizing the measurement point.
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公开(公告)号：US11525819B1
公开(公告)日：2022-12-13
申请号：US17249795
申请日：2021-03-12
Applicant: Picarro Inc.
Inventor： Sean MacMullin , Chris W. Rella , Aaron Van Pelt , Alex Balkanski , Yonggang He , Sze M. Tan , David Steele , Tim Clark
Abstract: In some embodiments, data from multiple vehicle-based natural gas leak detection survey runs are used by computer-implemented machine learning systems to generate a list of natural gas leaks ranked by hazard level. A risk model embodies training data having known hazard levels, and is used to classify newly-discovered leaks. Hazard levels may be expressed by continuous variables, and/or probabilities that a given leak fits within a predefined category of hazard (e.g. Grades 1-3). Each leak is represented by a cluster of leak indications (peaks) originating from a common leak sources. Hazard-predictive features may include maximum, minimum, mean, and/or median CH4/amplitude of aggregated leak indications; estimated leak flow rate, determined from an average of leak indications in a cluster; likelihood of leak being natural gas based on other indicator data (e.g. ethane concentration); probability the leak was detected on a given pass; and estimated distance to leak source.
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公开(公告)号：US10948471B1
公开(公告)日：2021-03-16
申请号：US15996069
申请日：2018-06-01
Applicant: Picarro Inc.
Inventor： Sean MacMullin , Chris W. Relia , Aaron Van Pelt , Alex Balkanski , Yonggang He , Sze Tan , David Steele , Tim Clark
Abstract: In some embodiments, data from multiple vehicle-based natural gas leak detection survey runs are used by computer-implemented machine learning systems to generate a list of natural gas leaks ranked by hazard level. A risk model embodies training data having known hazard levels, and is used to classify newly-discovered leaks. Hazard levels may be expressed by continuous variables, and/or probabilities that a given leak fits within a predefined category of hazard (e.g. Grades 1-3). Each leak is represented by a cluster of leak indications (peaks) originating from a common leak sources. Hazard-predictive features may include maximum, minimum, mean, and/or median CH4/amplitude of aggregated leak indications; estimated leak flow rate, determined from an average of leak indications in a cluster; likelihood of leak being natural gas based on other indicator data (e.g. ethane concentration); probability the leak was detected on a given pass; and estimated distance to leak source.
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公开(公告)号：US10598562B2
公开(公告)日：2020-03-24
申请号：US14948287
申请日：2015-11-21
Applicant: Picarro Inc.
Inventor： David Steele , Chris W. Rella , Sze M. Tan , Aaron Van Pelt
Abstract: In some embodiments, a natural gas leak detection system generates display content including indicators of remote and local potential leak source areas situated on a map of an area of a gas concentration measurement survey performed by a vehicle-borne device. The remote area may be shaped as a wedge extending upwind from an associated gas concentration measurement point. The local area graphically represents a potential local leak source area situated around the gas concentration measurement point, and having a boundary within a predetermined distance (e.g. 10 meters) of the gas concentration measurement point. The local area may be represented as a circle, ellipse, or other shape, and may include an area downwind from the measurement point. Size and/or shape parameters of the local area indicator may be determined according to survey vehicle speed and direction data, and/or wind speed and direction data characterizing the measurement point.
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