HVAC System Fault Detection Diagnosis and Identification
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
{'SignBlockName': 'Ritchie B. Coryell', 'PO_EMAI': None, 'PO_PHON': None}
Although Energy Management and Control Systems have contributed                 significantly to the reduction (20-40%) of energy use in buildings              without sacrificing occupants' comfort, their full capabilities have            not been completely realized.  This is primarily due to their inability         to quickly detect and compensate for failures in the Heating                    Ventilating and Air Conditioning (HVAC) system.  In fact, no matter how         good the control scheme for the HVAC system might be, the presence of           undetected faults can completely wipe out any expected savings.  This           research focuses on the problem of fault detection and diagnosis of             HVAC systems.  The primary goal of this project is to develop an                efficient methodology based on extended Kalman filtering and Maximum            Likelihood system identification for the detection and diagnosis of             faults in HVAC systems and to demonstrate its effectiveness through             application to an air handler system.  The methodology is to be                 powerful enough to permit rapid on-line fault detection and diagnosis           and yet be implementable on a personal computer.  Also, color graphic           display capability is to be incorporated to aid the operator in                 monitoring the state of the system.  To enhance the Phase III                   commercialization effort that will follow, a prototype system will be           developed and tested.
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{'Name': 'Scientific Systems Inc', 'CityName': 'Cambridge', 'ZipCode': '021402325', 'PhoneNumber': '6176616364', 'StreetAddress': 'One Alewife Place', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': None, 'ORG_LGL_BUS_NAME': None, 'ORG_PRNT_UEI_NUM': None}
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{'Code': '5373', 'Text': 'SBIR Phase II'}
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