System and method for identifying and recovering from a temporary sensor failure

Patent metadata

Field	Value
Publication number	US-2017191862-A1
Application number	US-201514985816-A
Country	US
Kind code	A1
Filing date	Dec 31, 2015
Priority date	Dec 31, 2015
Publication date	Jul 6, 2017
Grant date	—

Abstract

A sensor system for identifying a transient sensor failure in an industrial system and for recovering from an erroneous estimation of an expected mass flow rate resulting from the transient sensor failure. The sensor system includes one or more sensors for measuring at least one fluid property of the industrial system. The sensor system includes an enhanced flow soft sensing (EFSS) computing device configured to determine an estimated mass flow rate. The EFSS computing device is also configured to generate expected measurements to be received from one or more sensors. If an error value is not within predetermined parameters, the transient sensor failure is detected. The EFSS computing device is further configured to identify a resurgence of the sensor from the transient sensor failure. An erroneous expected mass flow rate then converges toward a correct expected mass flow rate.

First claim

What is claimed is:

1 . A sensor system for identifying a transient sensor failure in an industrial system and recovering from an erroneous estimation of an expected mass flow rate resulting from the transient sensor failure, the sensor system including one or more sensors for measuring at least one fluid property of the industrial system, said sensor system comprising:
an enhanced flow soft sensing (EFSS) computing device configured to determine an estimated mass flow rate, said EFSS computing device comprising a processor and a memory coupled to said processor, said EFSS computing device in communication with the one or more sensors, said EFSS computing device configured to:
generate, based on at least a historical estimated mass flow rate and a correction term, an expected mass flow rate;
generate, based on at least the expected mass flow rate, expected measurements to be received from the one or more sensors;
receive measurements from the one or more sensors;
compare the expected measurements with the measurements received from the one or more sensors to determine an error value;
compare the error value to predetermined parameters, wherein if the error value is not within the predetermined parameters, the transient sensor failure of a sensor is detected, thereby generating the erroneous estimation of the expected mass flow rate; and
identify a resurgence of the sensor from the transient sensor failure, wherein the erroneous expected mass flow rate converges toward a correct expected mass flow rate.

2 . The sensor system in accordance with claim 1 , wherein the measurements received from the one or more sensors include at least a vector of pressure and temperature measurements.

3 . The sensor system in accordance with claim 1 , wherein the convergence of the erroneous expected mass flow rate toward the correct expected mass flow rate is based on at least the correction term.

4 . The sensor system in accordance with claim 1 , wherein the correction term is based upon at least measurement errors and an internal model.

5 . The sensor system in accordance with claim 1 , wherein the expected measurements are based upon the expected mass flow rate and an internal model.

6 . The sensor system in accordance with claim 1 , wherein the predetermined parameters are obtained through a probability distribution of a difference between the expected measurements and the measurements received from the one or more sensors.

7 . The sensor system in accordance with claim 1 , wherein said EFSS computing device is coupled to a user interface, said EFSS computing device further configured to transmit a notification to the user interface that the transient sensor failure was detected.

8 . A method for identifying transient sensor failure in an industrial system and recovering from an erroneous estimation of an expected mass flow rate resulting from the transient sensor failure, said method implemented using an enhanced flow soft sensing (EFSS) computing device configured to determine an estimated mass flow rate, said method comprising:
generating, based on at least a historical estimated mass flow rate and a correction term, an expected mass flow rate; generating, based on at least the expected mass flow rate, expected measurements to be received from one or more sensors; receiving measurements from the one or more sensors; comparing the expected measurements with the measurements received from the one or more sensors to determine an error value; comparing the error value to predetermined parameters, wherein if the error value is not within the predetermined parameters, the transient sensor failure of a sensor is detected, thereby generating an erroneous estimation of the expected mass flow rate; and identifying a resurgence of the sensor from the transient sensor failure, wherein the erroneous expected mass flow rate converges toward a correct expected mass flow rate.

9 . The method in accordance with claim 8 , wherein the measurements received from the one or more sensors include at least a vector of pressure and temperature measurements.

10 . The method in accordance with claim 8 , wherein the convergence of the erroneous expected mass flow rate toward the correct expected mass flow rate is based on at least the correction term.

11 . The method in accordance with claim 8 , wherein the correction term is based upon at least measurement errors and an internal model.

12 . The method in accordance with claim 8 , wherein the expected measurements are based upon the expected mass flow rate and an internal model.

13 . method in accordance with claim 8 , wherein the predetermined parameters are obtained by means of a probability distribution of a difference between the expected measurements and the measurements received from the one or more sensors.

14 . The method in accordance with claim 8 , wherein said EFSS computing device is coupled to a user interface, said method further comprising transmitting a notification to the user interface that the transient sensor failure was detected.

15 . An enhanced flow soft sensing (EFSS) computing device configured to detect a transient sensor failure in an industrial system and recover from an erroneous estimation of an expected mass flow rate resulting from the transient sensor failure, said EFSS computing device further configured to determine an estimated mass flow rate, said EFSS computing device comprising:
a processor in communication with a memory and one or more sensors, said processor configured to:
generate, based on at least a historical estimated mass flow rate and a correction term, an expected mass flow rate;
generate, based on at least the expected mass flow rate, expected measurements to be received from the one or more sensors;
receive measurements from the one or more sensors;
compare the expected measurements with the measurements received from the one or more sensors to determine an error value;
compare the error value to predetermined parameters, wherein if the error value is not within the predetermined parameters, the transient sensor failure of a sensor is detected, thereby generating an erroneous estimation of the expected mass flow rate; and
identify a resurgence of the sensor from the transient sensor failure, wherein the erroneous expected mass flow rate converges toward a correct expected mass flow rate.

16 . The EFSS computing device in accordance with claim 15 , wherein the measurements received from the one or more sensors include at least a vector of pressure and temperature measurements.

17 . The EFSS computing device in accordance with claim 15 , wherein the convergence of the erroneous expected mass flow rate toward the correct expected mass flow rate is based on at least the correction term.

18 . The EFSS computing device in accordance with claim 15 , wherein the correction term is based upon at least measurement errors and an internal model.

19 . The EFSS computing device in accordance with claim 15 , wherein the expected measurements are based upon the expected mass flow rate and an internal model.

20 . The EFSS computing device in accordance with claim 15 , wherein the predetermined parameters are obtained by means of a probability distribution of a difference between the expected measurements and the measurements received from the one or more sensors.

21 . The EFSS computing device in accordance with claim 15 , wherein said EFSS computing device is coupled to a user interface, said EF

Assignees

• Gen Electric

Inventors

• Gonzaga Carlos
• Parolini Luca

Classifications

• F05D2270/00

  Control · CPC title

• F01D15/00 Primary

  Adaptations of machines or engines for special use; Combinations of engines with devices driven thereby · CPC title

• E21B47/06 Primary

  Measuring temperature or pressure · CPC title

• E21B47/001

  for underwater installation · CPC title

• G01F25/00 Primary

  Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume · CPC title