A Critical Review on the Application and Problems Caused by False Alarms

Sharma, Vishal; Varma, Arun S.; Singh, Atul; Singh, Divyansh; Yadav, Bikarama Prasad

doi:10.1007/978-981-10-5903-2_38

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…The detection concentration was 2.0000007% obs/m, and the detection accuracy was higher than that of the PPM. 4 Conclusions (1) The limit of the smoke particle concentration measured by the detector reaches the PPM. The designed capacitive detection cell effectively improves the sensitivity of the detector and can measure the concentration of smoke particles effectively at the PPM level.…”

Section: Fig 12 Interference Experiments Detector Signal Output Diagrammentioning

confidence: 99%

“…This approach can effectively control the further development of fires and minimize losses of all kinds of fires. Unfortunately, there are more than 100,000 cases of no alarm generation or alarm failure [1], and more than 200,000 false alarms were responded to by fire departments [2]. These factors lead to unnecessary losses, waste of firefighting resources, and declining public confidence.…”

Section: Introductionmentioning

confidence: 99%

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Research on a capacitive particle analysis smoke detector

Wang,

Zhao,

Zhang

et al. 2024

Preprint

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Smoke detectors face the challenges of increasing accuracy, sensitivity, and high reliability in complex use environments to ensure the timeliness, accuracy, and reliability of very early fire detection. The improvement and innovation of the principle and algorithm for smoke particle concentration detection provide opportunities for improving the performance of the detector. This study represents a new refinement of the smoke concentration detection principle based on capacitive detection of cell structures, and detection signals are processed by a multiscale smoke particle concentration detection algorithm to calculate smoke concentration. Through experiments, it was found that the detector provides effective detection of smoke particle concentrations ranging from 0 to 10% obs/m; moreover, when the detection accuracy is greater than a certain number of parts per million (PPM), the sensitivity of the detector can reach the PPM level; furthermore, the detector can detect smoke particle concentrations higher than the PPM level accuracy even in an environment with a certain concentration of petroliferous and dust particles of different sizes.

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Section: Fig 12 Interference Experiments Detector Signal Output Diagrammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on a capacitive particle analysis smoke detector

Wang,

Zhao,

Zhang

et al. 2024

Preprint

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“…In a series of works on the issue of fire detectors, attention is drawn to their false triggering. Paper [15] argues that there were more than 300,000 false triggerings recorded in the UK in two years. Such false triggering is the result of improper installation, negligent maintenance, as well as environmental impact, and anthropogenic factors.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Substantiating the pulse method for determining the time parameter of fire detectors with a thermoresistive sensing element

Abramov

Basmanov

Kozak

2021

EEJET

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This paper substantiates the pulse method for determining the time parameter for fire detectors with a thermoresistive sensing element ‒ the time constant. The method is based on using the Joule-Lenz effect, which manifests itself when an electric current pulse passes through the thermoresistive sensing element of fire detectors. Thermal processes in such a sensing element are described by a mathematical model that belongs to the class of equations of mathematical physics. The solution to the differential equation of this class was derived using the Hankel integral transformation and is represented as a series relative to the Bessel functions. The resulting solution is used to construct a mathematical model of a thermoresistive sensing element in the form of a transfer function, which takes the form of the transfer function of the inertial link. To trigger the thermoresistive sensing element of fire detectors, a single pulse of electric current in the shape of a rectangular triangle is used. The integral Laplace transformation was applied to mathematically describe the response of a thermoresistive sensing element to the thermal effect of such a test influence. To obtain information about the time parameter of fire detectors with a thermoresistive sensing element, the ratio of its output signals is used, which are measured in the a priori defined moments. A two-parametric expression was built to determine the time parameter of fire detectors; a verbal interpretation of the pulse method to determine it was provided. The implementation of this method ensures the invariance of the time parameter of fire detectors with a thermoresistive sensing element relative to the amplitude of a single pulse of an electric current, as well as relative to the parameter that is included in its transfer coefficient.

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“…A strategy for Integration of alarm system implementation and operational practices has been proposed and the potential use of cyber-physical systems in alarm systems and industrial automation has been suggested. The latest trends and developments in fire alarms have been analyzed by [9]. The study pointed out that most false alarms were the result of poor installation, imperfect maintenance, and human factors.…”

Section: A Brief Literature Review On Performance Assessment Of Alarmmentioning

confidence: 99%

Performance evaluation and design for variable threshold alarm systems through semi-Markov process

et al. 2020

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In large industrial systems, alarm management is one of the most important issues to improve the safety and efficiency of systems in practice. Operators of such systems often have to deal with a numerous number of simultaneous alarms. Different kinds of thresholding or filtration are applied to decrease alarm nuisance and improve performance indices, such as Averaged Alarm Delay (ADD), Missed Alarm and False Alarm Rates (MAR and FAR). Among thresholdbased approaches, variable thresholding methods are well-known for reducing the alarm nuisance and improving the performance of the alarm system. However, the literature suffers from the lack of an appropriate method to assess performance parameters of Variable Threshold Alarm Systems (VTASs). This study introduces two types of variable thresholding and proposes a novel approach for performance assessment of VTASs using Priority-AND gate and semi-Markov process. Application of semi-Markov process allows the proposed approach to consider industrial measurements with non-Gaussian distributions. In addition, the paper provides a genetic algorithm based optimized design process for optimal parameter setting to improve performance indices. The effectiveness of the proposed approach is illustrated via three numerical examples and through a comparison with previous studies.

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A Critical Review on the Application and Problems Caused by False Alarms

Cited by 7 publications

References 14 publications

Research on a capacitive particle analysis smoke detector

Research on a capacitive particle analysis smoke detector

Substantiating the pulse method for determining the time parameter of fire detectors with a thermoresistive sensing element

Performance evaluation and design for variable threshold alarm systems through semi-Markov process

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