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Data-driven unsupervised algorithm for analyzing sensor data to detect abnormal valve operation

A sensor parameter, abnormal technology, applied in machine/engine, electrical testing/monitoring, testing/monitoring control system, etc., can solve problems such as difficult diagnosis and time-consuming

Active Publication Date: 2018-10-09
THE BOEING CO
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Typically, diagnosis of abnormal operation of valves in aircraft is difficult and time consuming

Method used

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  • Data-driven unsupervised algorithm for analyzing sensor data to detect abnormal valve operation
  • Data-driven unsupervised algorithm for analyzing sensor data to detect abnormal valve operation
  • Data-driven unsupervised algorithm for analyzing sensor data to detect abnormal valve operation

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Embodiment Construction

[0013] Aspects disclosed herein provide techniques for detecting failure of a shutoff valve in an aircraft (or other type of vehicle) using an n-second window of sensor data related to the shutoff valve. An n-second window of sensor data is captured as part of the parameterized flight data. In general, aspects disclosed herein use unsupervised learning algorithms to analyze data provided by sensors in previous flights to identify data values ​​(and associated parameters) that indicate that the shut-off valve is operating abnormally. Once the parameters and data values ​​are identified, aspects disclosed herein analyze an n-second window of real-time flight data following valve opening and / or closing during flight. Aspects disclosed herein may generate an indication of abnormal operation if an n-second window of real-time flight data indicates that a given valve is operating abnormally. In some aspects, indications of abnormal operation are transmitted from the aircraft to a r...

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Abstract

The invention relates to a data-driven unsupervised algorithm for analyzing sensor data to detect abnormal valve operation. A computer-implemented method, system, and computer program product are provided. A plurality of maintenance messages (MMSGs) are identified. Each MMSG is associated with at least one shut-off valve. A sensor parameter is identified based on an analysis of sensor parameters associated with the shut-off valves of each MMSG. A threshold value for the sensor parameter is identified as being associated with abnormal operation of the respective shut-off valves. A sensor associated with a first shut-off valve captures values for the sensor parameter during a first and second predefined time period, the first and second predefined time periods associated with an opening anda closing of the first shut-off valve. Upon determining that a difference between the maximum values of the sensor values captured during the first and second predefined time periods exceeds the firstthreshold value, a determination is made that the first shut-off valve is operating abnormally.

Description

technical field [0001] Aspects described herein relate to valves in aircraft, and more particularly to methods and systems for detecting abnormal valve operation based on data-driven unsupervised algorithms for analyzing sensor data. Background technique [0002] Typically, diagnosis of abnormal operation of valves in an aircraft is difficult and time consuming. Furthermore, conventional methods aim at diagnosing abnormal operation of a particular valve or a particular type of valve. Contents of the invention [0003] According to one aspect, a computer-implemented method includes identifying a plurality of maintenance messages (MMSGs). Each of the plurality of MMSGs is associated with at least one of the plurality of shutoff valves in the vehicle. The method also includes identifying a first sensor parameter based on an analysis of a plurality of sensor parameters associated with at least one shutoff valve associated with each MMSG. Additionally, a first threshold for ...

Claims

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Application Information

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IPC IPC(8): G05B23/02
CPCG05B23/0221G05B23/0235G06Q10/20G06Q10/1097G05B23/0283G05B23/024G05B23/0259G05B23/0218G05B23/0205F16K37/0075F01D21/003F01D21/00G01M99/005F16K37/0083G07C5/0808G01M15/14G05B23/0254B64F5/60F16K37/0091
Inventor R·N·桑德斯瓦尔T-C·鲁F·D·贝兹
Owner THE BOEING CO
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