By 2014, this project will develop the technology to significantly reduce residential fire deaths through demonstration of economical advanced detection systems and the proposal of enabling codes and standards provisions for residential applications. A systems approach with research in sensors and sensor modeling, data fusion, human interaction, and implementation strategies will enable early warning fire detection to significantly reduce egress time while also reducing nuisance (false positive) alarms. The ability to discriminate between the early stages of an unwanted fire and a range of nuisance sources that present themselves at much lower signal levels than current alarm conditions will require a combination of sensitive chemical, thermal, and particulate sensing techniques. NIST will measure particle concentrations, chemical species, and temperatures, and assess flame detection and other discriminating phenomena in the very early stages of fires including residential electrical fires and nuisance source events. Data gathered will be used to develop discriminating detection algorithms.
Objective: To significantly reduce residential fire deaths through development of measurement science to enable economical detection systems with more rapid response time and lower nuisance activations, and draft codes and standards provisions for residential applications by 2014.
What is the new technical idea? The combination of early warning fire detection and nuisance alarm resistance in residential smoke alarms could cut the fire death rate in half. Technology innovations needed for early warning fire detection to significantly reduce egress time will require a systems approach with research in sensors and sensor modeling, data fusion, and implementation strategies. However, a significant increase in fire sensitivity exacerbates the nuisance alarm problem which must be addressed simultaneously. The ability to discriminate between the early stages of a fire and a range of nuisance sources that present themselves at much lower signal levels than current alarm conditions will require sensitive chemical, thermal, and particulate sensing techniques. The formation of a working group in UL 217 Single and Multiple Station Smoke Alarms Standards Technical Panel will be proposed for the purposes of assessing performance objectives and establishing requirements for next generation intelligent alarm systems. A systems approach research plan aimed at achieving the performance objectives of advanced residential fire detection will be formulated. Beyond advances in sensing technologies, a key relationship that needs to be understood is the interaction of humans to information presented by fire detection systems (e.g. obvious nuisance alarm – ignore or disable, failure to awaken a sleeping individual, tolerance of a “learning” phase of an advanced alarm, etc.) For instance, an intelligent fire alarm system that knows when cooking appliances are turned on, what time it is, and where occupants are located and were located in the immediate past may inform occupants much differently than a fire alarm system that does not have this information. This project is aligned with NIST’s Strategic Roadmap on the Reduced Risk of Fire in Building and Communities (NIST SP 1130, 2012).
What is the research plan? While the range of identified fire sensing techniques is broad, spanning thermal, gas species, particulate, radiated energy, video image analysis, and even acoustic signatures, very early fire detection techniques lend themselves to particulate and in some cases gas species detection. Light scattering measurements are easily 5 orders of magnitude more sensitive than typical sensitivities of alarms available on the market today. In FY 13, measurements of the very early fire environment and select nuisance sources will be made. Multi-angle, multi-wavelength particle light scattering, chemical constituents (FTIR most likely, plus select specific gases), thermal, humidity and particle size distributions will be measured. An effort will be made to examine scattering signals to determine if it is possible to accurately discriminate between background particles and a mix of background particles and soot indicating transition to flaming. Background particle could be nuisance aerosols or smolder smokes. The ability to sense early indications of soot particles would provide critical information for very early warning fire detection. The data will be used to develop and test fire and nuisance source discriminating algorithms using down-selected measurements. An alternative strategy using a discriminating algorithm as a component of the fire detection system will be demonstrated in FY14.
Two new areas of focus in FY 13 are detection of electrically initiated fires, and flame detection in kitchen fire scenarios. The rationale for focusing attention in these two areas stems from their significant contributions to residential fire losses. In addition, due to recent changes in flammability standards and the fire safe cigarette standard the anticipated reduction in fire losses attributed to upholstered furniture fires will increase the relative contribution of all other residential fire loss causes.
Electrical failure or malfunction was indicated as contributing to ignition in 44,800 residential structural fires and 472 fire deaths in 2009 (Hall, Home Electric Fires, 2012). Early detection of electrical malfunction or failure via sensing of early degradation products could significantly impact the fire losses and deaths attributed to these ignition sources. Experiments will be conducted to characterize the degradation products (smoke and gases, such as HCl from PVC materials) from electrical components and wiring. This effort will add new data which will enable the development of advanced detection schemes that are able to sense electrical fire precursors before initiation of a flaming.
The performance of flame detectors including the Southwest Sciences SBIR device and a commercial detector head with integrated flame detection will be characterized against very small kitchen range and appliance fires and compared to standard smoke alarms. Flame detection may provide a “fool proof” way to discriminate cooking activities from real fire hazards at the earliest possible moment.
The specification of a nuisance alarm standard for UL 217 will continue in FY13 by presenting the NIST nuisance alarm test procedures to the Standards Technical Panel nuisance alarm working group. The working group is tasked with sending a proposal to the Standards Technical Panel on nuisance alarm testing for consideration. Continued development and support of nuisance alarm standards in FY 13 will provide continuity for standards proposals on advanced fire detection in FY 14. Work will be continued to establish requirements for next generation intelligent residential alarm systems by 2014.
Recent Results: Designed multi-angle, multi-wavelength scattering apparatus. Testing completed on aerosol exposure experiments of 8 residential smoke alarms. Analysis of kitchen nuisance alarm and fire tests conducted. Characterized the Oak Ridge National Laboratory prototype advanced detector in the NIST FE/DE and the small smoke box. The response of a commercial two-wavelength photoelectric detector was measured for a range of aerosol size distributions.
Sample sensor test board used during tests of residential smoke alarms. Photo credit: NIST
Start Date:October 1, 2011
Lead Organizational Unit:el
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