Detection and use of anomalies in an industrial environment
US-2019325328-A1 · Oct 24, 2019 · US
US11636752B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11636752-B2 |
| Application number | US-202117240806-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 26, 2021 |
| Priority date | Apr 26, 2021 |
| Publication date | Apr 25, 2023 |
| Grant date | Apr 25, 2023 |
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A method for derivation of a machine signature includes receiving sensor information from a primary sensor, where the primary sensor is positioned to receive information from a portion of an industrial operation, and receiving sensor information from one or more secondary sensors. The secondary sensors are arranged to provide additional information about the industrial operation indicative of current operating conditions of the industrial operation. The method includes using the sensor information from the secondary sensors and machine learning to determine if the portion of the industrial operation is operating in a normal condition and, in response to determining that the portion of the industrial operation is operating normally, using sensor information from the primary sensor during the normal operating condition to derive a primary sensor signature for the sensor information from the primary sensor.
Opening claim text (preview).
What is claimed is: 1. A method comprising: receiving sensor information from a primary sensor, the primary sensor positioned to receive information from a portion of an industrial operation; receiving sensor information from one or more secondary sensors, the one or more secondary sensors are arranged to provide additional information about the portion of the industrial operation monitored by the primary sensor indicative of current operating conditions of the portion of the industrial operation; using the sensor information from the one or more secondary sensors and a machine learning algorithm to determine if the portion of the industrial operation is operating in a normal or abnormal condition; using the sensor information from the one or more secondary sensors to identify a transient condition and excluding sensor information of the primary sensor during the transient condition; and in response to determining that the portion of the industrial operation is operating in a normal condition, using sensor information from the primary sensor during the determined normal operating condition to derive a primary sensor signature for the sensor information from the primary sensor. 2. The method of claim 1 , further comprising: receiving additional sensor information from one of: the primary sensor positioned to receive information from the portion of the industrial operation used to derive the primary sensor signature; and another primary sensor positioned to receive information from a portion of an industrial operation similar to the portion of the industrial operation used to derive the primary sensor signature; determining if the additional sensor information exceeds the primary sensor signature by a threshold amount; and sending an alert in response to determining that the additional sensor information exceeds the primary sensor signature by the threshold amount. 3. The method of claim 2 , wherein the primary sensor signature comprises frequency information and determining if the additional sensor information exceeds the primary sensor signature by a threshold amount comprises determining if the additional sensor information at a frequency exceeds the primary sensor signature at the frequency by the threshold amount. 4. The method of claim 2 , wherein the portion of the industrial operation at least similar to the portion of the industrial operation used to derive the primary sensor signature is the portion of the industrial operation used to derive the primary sensor signature and the primary sensor used to receive the additional sensor information is the primary sensor used to derive the primary sensor signature. 5. The method of claim 1 , wherein the information from the primary sensor comprises a repeating pattern. 6. The method of claim 1 , further comprising: receiving sensor information from the one or more secondary sensors indicative of a change to operation of the portion of the industrial operation monitored by the primary sensor wherein the change to the operation comprises an additional normal operating condition; receiving additional sensor information from the primary sensor during the additional normal operating condition; and using the additional sensor information from the primary sensor during the determined additional normal operating condition and using the machine learning algorithm to derive an additional primary sensor signature for the sensor information from the primary sensor without sending an alert of an abnormal operating condition. 7. The method of claim 1 , wherein the machine learning algorithm updates the primary sensor signature in response to: receiving additional sensor information from the primary sensor and receiving additional sensor information from the one or more secondary sensors; and/or receiving sensor information from a primary sensor and receiving sensor information from one or more secondary sensors positioned to receive information from a portion of an industrial operation at least similar to the portion of the industrial operation used to derive the primary sensor signature. 8. The method of claim 1 , wherein the primary sensor comprises one of a vibration sensor, an acoustic sensor, a pressure sensor and a flow sensor. 9. The method of claim 1 , wherein: a secondary sensor of the one or more secondary sensors comprises one of a temperature sensor, a current sensor, a voltage sensor, a camera, a motion sensor, a vibration sensor, an acoustic sensor, a pressure sensor, a flow sensor and information from a programmable logic controller (“PLC”); one or more of the secondary sensors are of a different type than the primary sensor; one or more of the secondary sensors perform a different function than the primary sensor; and/or one or more of the secondary sensors comprise a virtual sensor comprising a sensing function based on sensor information from two or more other sensors. 10. A component comprising: a primary sensor module configured to receive sensor information from a primary sensor, the primary sensor positioned to receive information from a portion of an industrial operation; a secondary sensor module configured to receive sensor information from one or more secondary sensors, the one or more secondary sensors are arranged to provide additional information about the portion of the industrial operation monitored by the primary sensor indicative of current operating conditions of the portion of the industrial operation; a conditions module configured to use the sensor information from the one or more secondary sensors and a machine learning algorithm to determine if the portion of the industrial operation is operating in a normal or abnormal condition; a transient exclusion module configured to use the sensor information from the one or more secondary sensors to identify a transient condition and wherein the signature module is configured to exclude sensor information of the primary sensor during the transient condition; and a signature module configured to, in response to determining that the portion of the industrial operation is operating in a normal condition, use sensor information from the primary sensor during the determined normal operating condition to derive a primary sensor signature for the sensor information from the primary sensor, wherein said modules comprise one or more of hardware circuits, a programmable hardware device, and executable code, the executable code stored on one or more computer readable storage media. 11. The component of claim 10 , further comprising: an operations module configured to receive additional sensor information from one of: the primary sensor positioned to receive information from the portion of the industrial operation used to derive the primary sensor signature; and another primary sensor positioned to receive information from a portion of an industrial operation similar to the portion of the industrial operation used to derive the primary sensor signature; a violation module configured to determine if the additional sensor information exceeds the primary sensor signature by a threshold amount; and an alert module configured to send an alert in response to determining that the additional sensor information exceeds the primary sensor signature by the threshold amount. 12. The component of claim 10 , wherein the information from the primary sensor comprises a repeating pattern. 13. The component of claim 10 , wherein: the secondary sensor module is further configured to receive sensor information from the one or more secondary sensors indicative of a change to operation of the portion of the industrial operation monitored
Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods · CPC title
based on a qualitative model, e.g. rule based; if-then decisions · CPC title
Machine learning · CPC title
Level alarms, e.g. alarms responsive to variables exceeding a threshold · CPC title
adopting a different treatment of each operating region or a different mode of the monitored system, e.g. transient modes; different operating configurations of monitored system · CPC title
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