Research into multi-sensor detector capabilities and false alarm reduction Raman Chagger Principal Consultant, Fire Safety Group, BRE BRE Fire Conference, 18 th September 2018 Part of the BRE Trust
Introduction Losses from false fire alarms ~ 1 billion/year in the UK False alarms have consequences: FRS drain on/diverted resources Businesses disruptions/loss of productivity Public - reduced confidence/frustration Road traffic accidents
False alarm studies Study 1: The causes of false fire alarms in buildings Study 2: Live investigations of false fire alarms
False alarm studies Study 1: KCL 6 recommendations Potentially 49.5% reduction through the greater use of multi-sensors. Study 1: BMKFA Potentially 27.0% reduction through the greater use of multi-sensors. Study 2: SFRS 35 recommendations Potentially 35.1% reduction through the greater use of multi-sensors.
Multi-sensor detectors Multi-sensors utilise a number of sensors to provide more reliable detection Research with SFRS identified that no false alarms were caused from multi-sensor detectors One of the recommendations Further research is required to identify multisensors performance variabilities and capabilities. Heat Optical smoke Carbon Monoxide Photo courtesy of Tyco Fire Protection Products
Optical/heat multi-sensor detector research The BRE Trust, 12 manufacturers and the Fire Industry Association started a 3 phase research project Phase 1: Review of multi-sensor capabilities and variabilities. Identify tests Phase 2: Performing a broad range of test fires (compare with optical) Phase 3: Performing a broad range of common false alarm tests to identify resistance of multi-sensors. Aim of identifying relative benefits of multi-sensors over optical detectors
Video
Phase 1: Identification of false alarm tests False alarm tests explored: Dust (long term) Dust (short term) Smoke from cooking Steam Condensation Aerosols Smoke from toaster Cigarette smoke Synthetic (smoke machines) Insects Thermal shock
Phase 1: Development of false alarm tests Dust (long term) Dust (short term) Smoke from cooking Steam Condensation Aerosols (hairspray/deodorant) Smoke from toaster Cigarette smoke Synthetic (smoke machines) Insects Thermal shock Dust Water mist Aerosol Toast Cooking
Phase 1: Identification of fire tests Utilised the methodology from previous work into test fires for smoke alarms and detectors Testfire m:y Δ t (db/m) ( C) ABS (S) 3.04 2.9 Flame retardant PU foam (S) 1.88 2.5 TF2 Wood(S) 1.08 1.8 TF3 Cotton (S) 0.528 2.0 TF4 PU foam (F) 0.235 21 TF5N-heptane(F) 0.168 35 TF8Decalin(F) 0.25 6 Nylon (F) 0.168 5 Flame retardant PU foam (F) 0.094 5 TF1wooden crib (F) 0.079 24 (F) = Flaming; (S) = Smouldering
Phase 2: Fire tests 36 types of different optical heat multi-sensor detectors tested alongside 2 reference optical smoke detectors Multi-sensors categorised in terms of their false alarm resistance as basic, intermediate or advanced
Phase 2: Fire tests- Smouldering Flame Retardant PU Foam
Phase 3: False alarm tests- Toast
Phase 3: False alarm tests- Water mist
Phase 3: False alarm tests- Aerosol
Phase 3: False alarm tests- overview Multi-sensor response normalised to optical (%) 250% 200% 150% 100% 50% 0% 216% Multi-sensor detector average Optical smoke devices average 182% 191% Toast (db/m) Cooking (db/m) Water mist (db/m) False alarm test 248% Dust (db/m) 207% Aerosol (sec. db/m)
Phase 3: False alarm tests- example scenarios
Phase 3: False alarm and fire test comparison
Conclusion - Research has demonstrated that multisensor detectors can have the same response to fire but delayed response to false alarms - FIA and BRE are working towards the development of a Loss Prevention Standard for False Alarm Resistance - FIA guidance on false alarm reduction available from: http://www.fia.uk.com/cutfalse-alarm-costs.html - BRE briefing papers (+ videos) are available free of charge from: http://www.bre.co.uk/firedetectionresearch
Thanks S. Brown Consulting Services Ltd Thanks to UBM for use of images in this presentation