Metallurgical analysis of the ‘cause’ arc beads pattern characteristics under different short-circuit currents
Introduction
Data from US fire departments indicate an estimated 45,210 home structure fires annually between 2010 and 2014, in which several types of electrical failure or malfunction contributed to ignition. These fires caused 420 deaths, 1370 injuries, and USD1.4 billion in direct property damages annually (Babrauskas, 2008, 2017a). Electric arc beads pose an ignition hazard in flammable gas mixtures exist, which commonly cause large fire and explosion accidents, especially during the powder process industries (Klippel et al., 2015, Li et al., 2020). Moreover, electrical equipment failure arc ignition of flammable materials is the main cause of industries fires. Arc faults are more difficult than other electrical faults to detect and quickly fix and can readily cause serious consequences. The overload is severe enough to melt the wire, such as in short-circuit faults, which typically eject hot particles and have centre temperatures approximately 6500–12,000 K (Rallis and Mangaya, 2002). Melted metal particles can ignite flammables or other combustibles, expand the combustion range, and increase fire risk (Babrauskas, 2001; He et al., 2016; Kobayashi et al., 2017; Yuan et al., 2018; Dubaniewicz and DuCarme, 2016). Therefore, for electrical fire investigation, the arc beads patterns as a vital evidence, which is particularly essential to accurately identify patterns characteristics.
Research on metal melting patterns formed by arcs concentrates primarily on copper and aluminium wires in electrical systems. In 1971, Takaki used the metallographic method to distinguish between short-circuited beads and globules (Takaki, 1971). Subsequently, numerous scholars have used stereo microscopes, metallographic microscopes, scanning electron microscopes, Raman spectroscopes, and other instruments to systematically analyse the short-circuit and fire-melting beads of copper and aluminium wires (Gray et al., 1983; Babrauskas, 2003a; Ao et al., 2014; Wright et al., 2015). In 2012, China issued the national standard ‘GB/T16840 electrical fire pattern evidence technical identification method’ to distinguish typical characteristics and methods of copper and aluminium wire arc high-temperature melting metal patterns (GB/T 16840, 2012). In 2015, Wang studied the beads of copper wire with the density and metallographic methods (Wang et al., 2015a). Singh proposed that arcing results in obvious CuO or Cu2O grain structures near the end, gradually decreasing from the end (Sai et al., 2008). Most studies have examined the residual patterns of copper–aluminium wire ends, but few have investigated the particle patterns of hot beads. At present, the University of California, Berkeley is a research leader in investigating fires caused by hot particles and has cooperated in in-depth research with the University of Science and Technology of China (Wang et al., 2015b, 2015c; Yang et al., 2016). In 2011, Rory heated steel balls of various sizes to a certain temperature to study the effects of particle size on ignition and determined the critical conditions of the temperature and size of metal particles required for open flame combustion and smouldering (Hadden et al., 2011). In 2015, the James team at the University of California, Berkeley, heated variously sized metal particles of stainless steel, copper, and aluminium to different temperatures and analysed the ignition capacity of hot particulate matter for underlying fibre flammables (Zak, 2015; Urban et al., 2015, 2017, 2018, 2019). Relevant studies have generally focused on heating metal particles to certain temperatures for experimental research. These simplified theoretical models neglect that metal splashing out of the arc molten pool is still in a high-temperature liquid state and must undergo a series of processes, such as metal liquid cooling, solidification, and metal oxidation. These processes have a considerable effect on ignition capacity, thereby affecting the evolution of pattern characteristics of arc beads.
Because they are located at the bottom of the collapsed accumulation layer, arc beads are minimally damaged by fire, and their pattern characteristics are easy to retain. Therefore, arc beads are crucial to proving the occurrence of electrical faults. This study investigated the causal factors of arc bead pattern characteristics by applying metallographic analysis of copper wire exposed to various short-circuit currents and analysed the differences among metallographic characteristics, corresponding oxide content, and beads sizes.
Section snippets
Samples
A 2.5-mm2 polyvinyl chloride-insulated solid copper wire, which is the most common and widely used wire, bypassed excessive currents (100, 160, 200, and 240 A) through a cord until it short-circuited and ignited arc beads. The minimum arc current was ca. 100 A, and studies (Ramljak et al., 2014) indicated approximately 200 A would generate beads with stable typical crystal structure. This paper researched producing beads due to electrical faults, called ‘cause’ beads (‘cause’ beads, fire caused
Results and discussion
The direct measurements from each test were the arc beads pattern. In addition, beads size and currents were recorded. Therefore, the analysis, that currents and size of beads had which metallurgical structure character, helped identify the results of electrical fire investigation.
Conclusions
This study examined the cause of metallographic structure characteristics of arc beads in copper wire and the oxide distribution at various short-circuit currents. In addition, supplement and improve the metallographic structure characteristics of ‘cause’ beads, and combined with the characteristic parameters of arc beads (size, current, oxide), the ‘cause’ beads would basically be identified. This study was relevant to fire material evidence extraction and cause identification. The conclusions
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Key R&D Program of China (No. 2018YFC0807900), Shaanxi Province Key R&D Program (No. 2017ZDXM-SF-092), Xi'an University of Science and Technology School Peak Program (2040519002), Innovation Capability Support Project of Shaanxi Province (2018PT-33), and Shaanxi Higher Education Teaching Reform Research Program (19BY062).
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