Heat flow model for building fault detection and diagnosis

• US 8,606,554 B2
• Filed: 10/18/2010
• Issued: 12/10/2013
• Est. Priority Date: 10/19/2009
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Zimmermann, Gerhard, Lu, Yan, Lo, George
• Primary Examiner(s): Rivas, Omar Fernandez
• Assistant Examiner(s): CALLE, ANGEL J.
• Application Number:
  US12/906,186
• Publication Number:
  US 20110093424A1
• Time in Patent Office: 1,149 Days
• Field of Search: 703/5, 703/9, 700/276, 700/277, 715/734
• US Class Current: 703/5
• 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 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 that correspond to the BIM for each HVAC equipment type respectively;

creating connectivity among the retrieved 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 node rules which are conditioned inequalities based on node specific configuration data that defines the functionality of a physical HVAC component; and

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

2. The method according to claim 1 further comprising generating the HFM graph in an eXtensible Markup Language (XML) format.

3. The method according to claim 1 further comprising editing the HFM graph for missing parameters, conditions and switches not found in the BIM.

4. The method according to claim 1 wherein the BIM is an Industrial Foundation Class (IFC).

5. The method according to claim 1 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.

6. The method according to claim 1 wherein each HFM graph node 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 estimated parameter ranges.

7. 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 linkage 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 from the predefined HFM node types, the 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.

8. The system according to claim 7 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.

9. The system according to claim 7 wherein the dynamic physical behavior parameters are temperature, humidity, flow and pressure.

10. The system according to claim 8 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.

11. The system according to claim 7 wherein the BIM files further comprise Industrial Foundation Class (IFC) files.

12. The system according to claim 11 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.

13. The system according to claim 12 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.

14. The system according to claim 13 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.

15. The system according to claim 7 wherein the FDD generator generates an HFM model in XML format.

16. The system according to claim 7 wherein the HFM node library contains HFM node object models that can be hierarchically composed and decomposed.

17. The system according to claim 8 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 perform state estimation and propagate resulting parameter ranges to adjacent nodes.

18. A non-transitory computer readable medium having recorded thereon a computer program comprising code means for, when executed on a computer, instructing the computer to generate a Heat Flow Model (HFM) node used in a Heating, Ventilation and Air Conditioning (HVAC) HFM fault detection graph that models the dynamic physical behavior parameters of temperature T, humidity H, flow rate Q and pressure P of a physical HVAC component comprising:

a FwdIn edge configured to receive parameter ranges A_j that represent physical data upstream of the node;

a RevIn edge configured to receive parameter ranges B_j that represent physical data downstream of the node;

one or more DataIn edges, each DataIn edge configured to receive dynamic HVAC control system data wherein the control system data is used with node specific configuration data that defines the functionality of the physical HVAC component to calculate a node rule tolerance, downstream estimate parameter ranges A_j+1 and upstream estimate parameter ranges B_j+1;

a FwdOut edge configured to output the downstream estimate parameter ranges A_j+1 that represent the affect that the physical HVAC component has on the received parameter ranges A_j;

a RevOut edge configured to output the upstream estimate parameter ranges B_j+1 that represent the affect that the physical HVAC component has on the received parameter ranges B_j; and

two or more RulesOut edges, each RulesOut edge configured to output a failure rule decision from a conditioned inequality wherein a first failure rule compares a downstream estimated parameter range A_j+1 maximum with a like FwdIn edge parameter range A_j minimum and a second failure rule compares an upstream estimated parameter range B_j+1 maximum with a like RevIn edge parameter range B_j minimum and if the first or second rule is true, a fault exists in the physical HVAC component.

19. The non-transitory computer readable medium according to claim 18 wherein the FwdIn edge parameter ranges A_j are propagated from an adjacent upstream HFM node and the RevOut edge estimated parameter ranges B_j+1 are propagated to the adjacent upstream HFM node, and the FwdOut edge estimated parameter ranges A_j+1 are propagated to an adjacent downstream HFM node and the RevIn edge parameter ranges B_j are propagated from the adjacent downstream HFM node.

20. The non-transitory computer readable medium according to claim 18 wherein the FwdIn edge parameter ranges A_j, the FwdOut estimated parameter ranges A_j+1, the RevIn edge parameter ranges B_j and the RevOut edge estimated parameter ranges B_j+1 are vectors expressed as a minimum and a maximum of an estimated parameter range, the estimated temperature parameter range defined by Tmin, Tmax values, the estimated flow parameter range defined by Qmin, Qmax values, the estimated humidity parameter range defined by Hmin, Hmax values and the estimated pressure parameter range defined by pmin, pmax values.