Commissioning of sensors

• US 7,117,129 B1
• Filed: 03/11/2005
• Issued: 10/03/2006
• Est. Priority Date: 03/11/2005
• Status: Active Grant

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Bash, Cullen E., Sharma, Ratnesh K., Patel, Chandrakant D.
• Primary Examiner(s): Wachsman, Hal D.
• Application Number:
  US11/078,087
• Publication Number:
  US 20060206291A1
• Time in Patent Office: 571 Days
• Field of Search: 702/194, 702/45, 702/47, 702/50, 702/104, 702/105, 702/98, 702/99, 702/100, 702/113, 702/114, 702/116, 702/127, 702/130, 702/136, 702/138, 702/140, 702/179, 702/183, 702/186, 702/190
• US Class Current: 702/194
• CPC Class Codes: G05B 13/027 using neural networks only
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: H05K 7/20836 Thermal management, e.g. server temperature control

Abstract

A method for commissioning sensors includes determining correlation data between the sensors and a plurality of actuators. The correlation data is based upon conditions detected by the sensors at a plurality of actuator settings. Correlation indexes are calculated from the correlation data, where a correlation index for a sensor is a function of the plurality of actuator settings and a particular actuator. In addition, each of the sensors is assigned to at least one of a plurality of actuator families based upon the calculated correlation indexes of the sensors to thereby commission the sensors.

Claims

1. A method for commissioning sensors, said method comprising:

determining correlation data between the sensors and a plurality of actuators, wherein the correlation data is based upon conditions detected by the sensors at a plurality of actuator settings, wherein the plurality of actuator settings comprise various flow rate distributions;

calculating correlation indexes from the correlation data, wherein a correlation index for a sensor is a function of the plurality of actuator settings and a particular actuator; and

assigning each of the sensors to at least one of a plurality of actuator families based upon the calculated correlation indexes of the sensors, to thereby commission the sensors.

2. The method according to claim 1, wherein the step of calculating the correlation indexes comprises feeding the correlation data into a neural network and determining the correlation indexes based upon a model created by the neural network.

3. The method according to claim 2, further comprising:

for each sensor, determining whether the correlation index exceeds a predefined threshold for a particular actuator family at a particular plurality of actuator settings; and

wherein the step of assigning each of the sensors comprises assigning at least one of the sensors to at least one of the plurality of actuator families in response to the correlation index for the at least one sensor exceeding the predefined threshold.

4. The method according to claim 1, wherein the step of calculating the correlation indexes comprises feeding the correlation data into a curve fitting algorithm and determining the correlation indexes based upon equations determined through the curve fitting algorithm.

5. The method according to claim 4, further comprising:

for each sensor, determining whether the correlation index exceeds a predefined threshold for a particular actuator family at a particular plurality of actuator settings; and

wherein the step of assigning each of the sensors comprises assigning at least one of the sensors to at least one of the plurality of actuator families in response to the correlation indexes for the at least one sensor exceeding the predefined threshold.

6. The method according to claim 1, wherein the sensors comprise temperature sensors, the method further comprising:

setting the plurality of actuators to a first distribution level;

recording temperatures of the sensors at a first time;

varying a supply air temperature of an actuator of the plurality of actuators;

recording temperatures of the sensors at a second time; and

wherein the step of determining correlation data comprises determining a correlation between the sensors and the plurality of actuators based upon the recorded temperatures and the settings of the plurality of actuators.

7. The method according to claim 1, wherein the sensors comprise pressure sensors, the method further comprising:

setting the plurality of actuators to a first distribution level;

recording pressures of the sensors at a first time;

varying a supply air flow rate of an actuator of the plurality of actuators;

recording pressures of the sensors at a second time; and

wherein the step of determining correlation data comprises determining a correlation between the sensors and the plurality of actuators based upon the recorded pressures and the settings of the plurality of actuators.

8. The method according to claim 1, wherein the sensors comprise absolute humidity sensors, the method further comprising:

setting the plurality of actuators to a first distribution level;

recording absolute humidities of the sensors at a first time;

varying humidification of airflow supplied by an actuator of the plurality of actuators;

recording absolute humidities of the sensors at a second time; and

wherein the step of determining correlation data comprises determining a correlation between the sensors and the plurality of actuators based upon the recorded absolute humidities and the settings of the plurality of actuators.

9. The method according to claim 1, further comprising:

filtering sensors assigned to multiple actuator families.

10. The method according to claim 9, wherein the step of filtering sensors assigned to multiple actuator families further comprises:

identifying sensors belonging to multiple actuator families;

for each sensor belonging to multiple actuator families;

comparing correlation differences in the correlation indexes of the sensor and each of the multiple actuator families to which each of the sensors belong;

determining whether the correlation differences exceed a correlation difference threshold; and

assigning the sensor to the actuator family to which the sensor has the highest correlation index in response to the correlation differences exceeding the correlation difference threshold.

11. The method according to claim 10, further comprising:

sorting the sensors belonging to multiple actuator families according to whether the sensors require heating or cooling;

identifying a location and magnitude of a control sensor in each of the multiple actuator families;

determining whether the control sensor for a particular actuator family in the multiple actuator families is a control sensor for another actuator family; and

for each control sensor, assigning the control sensor to the particular actuator family in response to the control sensor not being the control sensor for another actuator family.

12. The method according to claim 11, further comprising:

for each remaining control sensor, determining whether the setpoints of the actuators in the multiple actuator families exceed a predefined temperature difference threshold;

determining whether the temperature of the control sensor is above or below a setpoint temperature;

assigning the actuator family having the actuator whose supply air temperature is the farthest away from the temperature of the control sensor as a primary family;

assigning a remaining actuator family as a secondary family; and

adjusting the assignment of each of the sensors to the actuator one of the primary and secondary families.

13. The method according to claim 12, wherein the step of adjusting the assignment of each of the sensors further comprises removing all sensors in both the primary and secondary families having the same sign as the control sensor from the secondary family to thereby give control over the temperature of the control sensor to the actuator having the highest supply air temperature in response to the temperature of the control sensor being above the setpoint temperature.

14. The method according to claim 12, wherein the step of adjusting the assignment of each of the sensors further comprises removing all sensors in both the primary and secondary families having the opposite sign as the control sensor from the primary family to thereby give control over the temperature of the control sensor to the actuator having the lowest supply air temperature in response to the temperature of the control sensor being below the setpoint temperature.

15. A system for commissioning sensors, said system comprising:

a plurality of variously located sensors;

a plurality of actuators, wherein the plurality of actuators are operable to vary conditions detected by the plurality of sensors;

a controller configured to implement at least one algorithm configured to;

determine correlation data between the sensors and the plurality of actuators;

calculate correlation indexes of the sensors from the correlation data; and

assign each of the sensors to at least one of a plurality of actuator families based upon the calculated correlation indexes of the sensors.

16. The system according to claim 15, wherein the controller is further configured to determine the correlation indexes based upon a model created by a neural network, wherein the neural network is formed through a neural network teaching algorithm based upon the correlation data.

17. The system according to claim 15, wherein the controller is further configured to determine the correlation indexes based upon equations determined through a curve fitting algorithm, wherein the curve fitting algorithm is calculated based upon the correlation data.

18. The system according to claim 15, wherein the sensors are operable to detect at least one of temperature, pressure, and humidity.

19. The system according to claim 15, wherein the plurality of actuators comprise computer room air conditioning units.

20. The system according to claim 15, wherein the controller is further configured to filter sensors that are assigned to multiple actuator families and to give control over the temperature of the sensors assigned to multiple actuator families to an actuator of one of the multiple actuator families to substantially increase the efficiencies of the actuators.

21. A data center comprising:

means for sensing conditions at a plurality of locations in the data center;

means for actuating, wherein the means for actuating is configured to vary conditions detected by the means for sensing;

means for calculating correlation indexes between the means for sensing and the means for actuating; and

means for assigning the means for sensing to at least one means for actuating family based upon the correlation indexes calculated by the means for calculating.

22. The data center according to claim 21, further comprising:

means for assigning control to the means for actuating when the means for sensing is assigned to multiple means for actuating families.

23. A computer readable storage medium on which is embedded one or more computer programs, said one or more computer programs implementing a method for commissioning sensors with a plurality of actuators, said one or more computer programs comprising a set of instructions for:

determining correlation data between the sensors and the plurality of actuators, wherein the correlation data is based upon conditions detected by the sensors at a plurality of actuator settings;

calculating correlation indexes from the correlation data, wherein a correlation index for a sensor is a function of the plurality of actuator settings and a particular actuator; and

assigning each of the sensors to at least one of a plurality of actuator families based upon the calculated correlation indexes of the sensors to thereby commission the sensors.

24. The computer readable storage medium according to claim 23, wherein said one or more computer programs further comprising comprises a set of instructions for:

filtering sensors assigned to multiple actuator families.