Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method

Jin, Guangying; Jin, Guangzhe

doi:10.3390/sym13122366

Cited by 7 publications

(5 citation statements)

References 63 publications

(59 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To evaluate the importance of the risk factors and in accordance with AHP [41,42], 30 experts, including professional designers of turnout gear, members of the National Fire Agency and local fire departments, members of the National Police Agency, and scholars of safety management, were asked to fill out a questionnaire (Supplementary Materials); 23 valid responses were collected. Using AHP, 28 risk factors were ordered from high to low risk based on their weight values.…”

Section: Ahp Expert Surveymentioning

confidence: 99%

Weighting of Firefighting Turnout Gear Risk Factors According to Expert Opinion

Chang

Luor

et al. 2022

Sustainability

View full text Add to dashboard Cite

Firefighters in Taiwan often wear expired protective clothing, which raises concerns regarding their safety. Extending the service life of fire protective clothing can improve firefighter safety and ensure environmental sustainability. In this study, an analytic hierarchy process was used to understand which risk factors should be prioritized in the design of firefighting turnout gear. We surveyed 30 experts in the field of firefighting and safety management on the importance of various risk factors related to turnout gear. A risk level of 70% was taken as the threshold of tolerable risk. The rankings of the weighted risk factors demonstrate that eliminating 12 of the 28 risk factors will result in 73% safety. These 12 factors are, in order of maximum risk, insufficient flame resistance, insufficient heat resistance, putting on the suit components in the wrong order, insufficient resistance to tears and punctures, poor agility, heavy overall weight, insufficient water resistance, lack of flame-retardant fibers, high levels of toxicity, insufficient internal circulation, no air filtration device, and poor air permeability. Consideration of these factors in the design of fire protective clothing can extend service life, help achieve sustainable development goals, and ensure firefighters’ safety.

show abstract

Section: Ahp Expert Surveymentioning

confidence: 99%

Weighting of Firefighting Turnout Gear Risk Factors According to Expert Opinion

Chang

Luor

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…One popular method for multi-criteria decision-making is the analytical hierarchy process (AHP), which involves the decomposition of the problem into a hierarchy of objectives, criteria, and alternatives. The AHP then assigns weights to each element in the hierarchy and uses them to rank the alternatives based on their overall desirability [ 23 ]. Figure 7 show the multi-level hierarchical structure for fuel-cell-stack fault-diagnosis sensor criteria weight definition.…”

Section: Selectionmentioning

confidence: 99%

Understanding the Role of Sensor Optimisation in Complex Systems

Suslu,

Ali,

Jennions

2023

Sensors

View full text Add to dashboard Cite

Complex systems involve monitoring, assessing, and predicting the health of various systems within an integrated vehicle health management (IVHM) system or a larger system. Health management applications rely on sensors that generate useful information about the health condition of the assets; thus, optimising the sensor network quality while considering specific constraints is the first step in assessing the condition of assets. The optimisation problem in sensor networks involves considering trade-offs between different performance metrics. This review paper provides a comprehensive guideline for practitioners in the field of sensor optimisation for complex systems. It introduces versatile multi-perspective cost functions for different aspects of sensor optimisation, including selection, placement, data processing and operation. A taxonomy and concept map of the field are defined as valuable navigation tools in this vast field. Optimisation techniques and quantification approaches of the cost functions are discussed, emphasising their adaptability to tailor to specific application requirements. As a pioneering contribution, all the relevant literature is gathered and classified here to further improve the understanding of optimal sensor networks from an information-gain perspective.

show abstract

“…The TOPSIS algorithm can be successfully applied for decision-making in different study areas, including complex network analysis [ 44 , 45 ], Internet of Things [ 46 , 47 , 48 ], neural networks [ 49 , 50 , 51 ], reverse logistics [ 52 , 53 ], and sensor selection [ 54 , 55 , 56 ]. According to [ 57 ], the mathematical formulation of the TOPSIS algorithm is composed of the steps: The decision matrix D is represented as

The elements

of the ordered decision matrix are calculated according to Equation (4).…”

Section: Multiple Criteria Decision Makingmentioning

confidence: 99%

Case Studies with the Contiki-NG Simulator to Design Strategies for Sensors’ Communication Optimization in an IoT-Fog Ecosystem

Ferreira

Azevedo

Estrella

et al. 2023

Sensors

View full text Add to dashboard Cite

With the development of mobile communications and the Internet of Things (IoT), IoT devices have increased, allowing their application in numerous areas of Industry 4.0. Applications on IoT devices are time sensitive and require a low response time, making reducing latency in IoT networks an essential task. However, it needs to be emphasized that data production and consumption are interdependent, so when designing the implementation of a fog network, it is crucial to consider criteria other than latency. Defining the strategy to deploy these nodes based on different criteria and sub-criteria is a challenging optimization problem, as the amount of possibilities is immense. This work aims to simulate a hybrid network of sensors related to public transport in the city of São Carlos - SP using Contiki-NG to select the most suitable place to deploy an IoT sensor network. Performance tests were carried out on five analyzed scenarios, and we collected the transmitted data based on criteria corresponding to devices, applications, and network communication on which we applied Multiple Attribute Decision Making (MADM) algorithms to generate a multicriteria decision ranking. The results show that based on the TOPSIS and VIKOR decision-making algorithms, scenario four is the most viable among those analyzed. This approach makes it feasible to optimally select the best option among different possibilities.

show abstract

Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method

Cited by 7 publications

References 63 publications

Weighting of Firefighting Turnout Gear Risk Factors According to Expert Opinion

Weighting of Firefighting Turnout Gear Risk Factors According to Expert Opinion

Understanding the Role of Sensor Optimisation in Complex Systems

Case Studies with the Contiki-NG Simulator to Design Strategies for Sensors’ Communication Optimization in an IoT-Fog Ecosystem

Contact Info

Product

Resources

About