Heat Flow Model for Building Fault Detection and Diagnosis

• US 20110093424A1
• Filed: 10/18/2010
• Published: 04/21/2011
• Est. Priority Date: 10/19/2009
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Lu, Yan, Lo, George, Zimmermann, Gerhard
• Granted Patent: US 8,606,554 B2
• Time in Patent Office: Days
• US Class Current: 706/47
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05B 23/0243 model based detection method, e.g. first-principles knowledge model

Abstract

Systems and methods are described that provide a Heat Flow Model (HFM) graph modeling methodology. Embodiments automatically translate formal HVAC system descriptions from a Building Information Model (BIM) into HFM graphs, and compile the graphs into executable FDD systems. During an engineering phase, a user interface is used to enter parameters, conditions, and switches not found in the BIM. During a runtime phase, real-time data from an HVAC control system is input to the generated FDD system (HFM graph) for fault detection and diagnosis.

Claims

1. A Heat Flow Model (HFM) node used in a Heating, Ventilation and Air Conditioning (HVAC) fault detection graph comprising:

a FwdIn edge configured to receive parameter ranges from a downstream direction;

a FwdOut edge configured to output parameter ranges in the downstream direction;

a RevIn edge configured to receive parameter ranges from an upstream direction;

a RevOut edge configured to output parameter ranges in the upstream direction; and

node specific configuration data that defines the functionality of the node.

2. The HFM node according to claim 1 further comprising one or more RulesOut edges configured to output a failure rule decision wherein the node specific data further comprises a failure rule corresponding to each RulesOut edge wherein, for the downstream direction, a failure rule compares an estimated parameter range with a FwdIn edge parameter range and for the upstream direction, a failure rule compares an estimated parameter range with a RevIn edge parameter range, and if the estimated parameter range is not within the received parameter range, a failure is output.

3. The HFM node according to claim 2 wherein the node specific configuration data further comprises FwdIn edge parameter range tolerances and RevIn edge parameter range tolerances.

4. The HFM node according to claim 3 wherein for the downstream direction, an estimated parameter range is a product of a RevIn edge parameter range and a RevIn edge parameter range tolerance, and for the upstream direction, an estimated parameter range is a product of a FwdIn edge parameter range and a FwdIn edge parameter range tolerance.

5. The HFM node according to claim 2 further comprising one or more DataIn edges, each configured to receive a dynamic HVAC control system variable, and the node specific configuration data further comprises DataIn edge dynamic HVAC control system variable parameter tolerance values.

6. The HFM node according to claim 5 wherein for the downstream and upstream directions, an estimated parameter range is a product of a DataIn edge dynamic HVAC control system variable and its dynamic HVAC control system variable parameter tolerance value.

7. The HFM node according to claim 1 wherein the FwdOut edge parameter ranges and RevOut edge parameter ranges represent the behavior of a physical HVAC component that corresponds with the node type.

8. The HFM node according to claim 1 wherein the FwdIn edge parameter ranges are propagated from an adjacent upstream HFM node and the RevOut edge parameter ranges are propagated to the adjacent upstream HFM node, and the FwdOut edge parameter ranges are propagated to an adjacent downstream HFM node and the RevIn edge parameter ranges are propagated from the adjacent downstream HFM node.

9. The HFM node according to claim 1 wherein the FwdOut and RevOut edge parameter ranges are expressed as a minimum and a maximum of an estimated parameter range.

10. The HFM node according to claim 9 wherein the FwdOut and RevOut edge parameters are temperature, flow humidity and pressure.

11. The HFM node according to claim 10 wherein the temperature parameter range is defined by Tmin,Tmax values, the flow parameter range is defined by Qmin,Qmax values, the humidity parameter range is defined by Hmin,Hmax values and the pressure parameter range is defined by pmin,pmax values.

12. The HFM node according to claim 2 wherein a failure rule is a conditioned inequality.

13. A method of using a Heat Flow Model (HFM) graph for detecting HVAC system faults for a building comprising:

translating formal HVAC system descriptions from a Building Information Model (BIM) for the building as HFM nodes;

retrieving HVAC component attributes from the BIM for each HFM node;

retrieving predefined HFM nodes from an HFM node library;

creating connectivity among different HFM nodes from BIM connectivity data;

compiling the HFM nodes into an HFM graph;

inputting real-time data from the building HVAC control system to the HFM graph for fault detection;

detecting building HVAC system faults using rules defined based on first principles that are related to the HFM nodes; and

mapping rule violations from the HFM nodes to the building HVAC control system failures.

14. The method according to claim 13 further comprising generating the HFM graph in an eXtensible Markup Language (XML) format.

15. The method according to claim 13 further comprising editing the HFM graph for missing parameters, conditions and switches not found in the BIM.

16. The method according to claim 13 wherein the BIM is an Industrial Foundation Class (IFC).

17. The method according to claim 13 wherein the HFM graph is a one-to-one correspondence with a component structure of the physical building HVAC system and the HFM graph nodes model the dynamic physical behavior of temperature, humidity, flow rate and pressure parameters of the physical building HVAC components as derived from the BIM.

18. The method according to claim 13 wherein each node in the HFM graph estimates upstream and downstream physical behavior values that correspond to their building HVAC components with dynamic output instrument sensor and control data from the building HVAC control system and propagates the upstream and downstream physical behavior values through the HFM graph as parameter ranges.

19. A building Heating, Ventilation and Air Conditioning (HVAC) fault detection system comprising:

an interface configured to access a Building Information Model (BIM) file library and import the building HVAC system BIM files;

an HFM node library configured to store a plurality of different predefined HFM node types wherein an HFM node models the dynamic physical behavior parameters of air and water flows in predefined HVAC components as derived from the BIM files;

a Graphic User Interface (GUI) configured to input and edit HFM node and linkage configuration data during an HFM graph assembly;

a compiler coupled to the interface and GUI, configured to compose together the BIM file data with the additional configuration data; and

a Fault Detection and Diagnosis (FDD) generator coupled to the compiler and HFM node library, configured to compare the BIM file types for the building HVAC system with the predefined HFM node types and select HFM nodes that correspond and generate an HFM graph wherein the HFM graph is by mass air flow path corresponding to the building HVAC system components and behavior.

20. The system according to claim 19 further comprising:

an FDD engine configured to instantiate the HFM graph as a runtime system for the building HVAC control system; and

an interface configured to access the building HVAC control system, wherein the FDD engine executes the HFM graph with HVAC control system process and control variable data and applies rules for detecting HVAC system faults.

21. The system according to claim 19 wherein the dynamic physical behavior parameters are temperature, humidity, flow and pressure.

22. The system according to claim 20 wherein an HFM node estimates upstream and downstream physical behavior parameters of connected HVAC components with the dynamic output data from the HVAC control system using instrument process and control variables and propagates the results through the HFM graph as parameter ranges.

23. The system according to claim 19 wherein the BIM files further comprise Industrial Foundation Class (IFC) files.

24. The system according to claim 23 wherein the IFC files provide a set of definitions for IFC object element types encountered in an HVAC mechanical and control system, and a text-based structure for storing the object element type definitions in a data file wherein the IFC object elements define basic properties and attributes used in the HFM node graph.

25. The system according to claim 24 wherein an IFC object element comprises two parts, an IFC element and an IFC port, wherein an element is a component that can be coupled to an adjacent element using one or more ports, and the IFC elements include flow segments, flow fittings, moving devices and flow controllers.

26. The system according to claim 25 wherein the compiler is further configured to identify all the HFM nodes from the IFC elements and retrieve attributes to create node estimation models and create the connectivity among different nodes from IFC connectivity data.

27. The system according to claim 19 wherein the FDD generator generates an HFM model in XML format.

28. The system according to claim 19 wherein the HFM node library contains HFM node object models that can be hierarchically composed and decomposed.

29. The system according to claim 20 wherein for each HFM node, based on received measurements and flow information from upstream and downstream HFM nodes, the FDD engine is further configured to performs state estimation and propagates resulting parameter ranges to adjacent nodes.