{"id":23283,"date":"2024-11-18T12:33:56","date_gmt":"2024-11-18T04:33:56","guid":{"rendered":"https:\/\/www.1ai.net\/?p=23283"},"modified":"2024-11-18T12:33:56","modified_gmt":"2024-11-18T04:33:56","slug":"ai-%e5%8f%af%e5%90%ac%e5%87%ba%e7%94%b5%e6%b1%a0%e8%b5%b7%e7%81%ab%e5%be%81%e5%85%86%ef%bc%8c%e5%87%86%e7%a1%ae%e7%8e%87%e8%be%be-94","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/23283.html","title":{"rendered":"AI can 'hear' signs of battery fires with 94% accuracy"},"content":{"rendered":"

lithium (chemistry)batteries<\/a>Fire has always been a major safety concern for electric vehicles and electronic devices, and scientists have been exploring various methods to prevent such accidents.<\/p>\n

\"b6429d7fj00sn4pzn0050d000bi006rp\"<\/p>\n

Recently, a new study proposed a way to use sound to warn lithium-ion batteries of an impending fire. The researchers noted that lithium-ion batteries undergo a chemical reaction process before catching fire, resulting in a gradual increase in internal pressure and the battery begins to expand. Since the battery casing is usually hard and cannot accommodate this expansion, a safety valve in the battery ruptures to release the pressure.<\/p>\n

In the process.The rupture of a safety valve makes a distinctive clicking and hissing sound, sort of like opening the cap of a soda bottle.<\/strong><\/p>\n

Researchers at the National Institute of Standards and Technology (NIST) have trained a machine learning algorithm that recognizes this distinctive rupture sound. To train the algorithm, the researchers worked with a lab at Xi'an University of Science and Technology to collect audio data from 38 exploding batteries. They then adjusted the speed and pitch of this audio to generate over 1,000 unique audio samples that were used to train the algorithm.<\/p>\n

The test results show thatThe algorithm recognizes the rupture sound of an overheated battery with an accuracy of 94%.<\/strong>. The researchers used a variety of background noises, including footsteps, slamming doors and opening bottles, to test the robustness of the algorithm and found that only a few noises were able to interfere with the algorithm's judgment.<\/p>\n

The researchers say the technology has the potential to develop a new type of fire alarm that could be installed in places such as homes, offices, warehouses and electric vehicle parking lots to give advance warning and provide ample time for people to evacuate.<\/p>","protected":false},"excerpt":{"rendered":"

LITHIUM BATTERY FIRES HAVE BEEN A MAJOR SAFETY HAZARD FOR ELECTRIC CARS AND ELECTRONICS, AND SCIENTISTS HAVE BEEN EXPLORING WAYS TO PREVENT SUCH ACCIDENTS. IN RECENT DAYS, A NEW STUDY HAS PROPOSED A METHOD OF USING SOUND TO ALERT LITHIUM ION BATTERIES TO IMMINENT FIRE. THE RESEARCHERS NOTED THAT LITHIUM ION BATTERIES WERE SUBJECT TO A CHEMICAL REACTION PROCESS BEFORE THE FIRE, WHICH LED TO A GRADUAL RISE IN INTERNAL PRESSURE AND AN EXPANSION OF THE BATTERIES. SINCE THE SHELL OF THE BATTERY IS USUALLY HARD ENOUGH TO ADJUST TO THIS EXPANSION, THE SAFETY VALVE IN THE BATTERY BREAKS TO RELEASE THE PRESSURE. IN THE PROCESS, THE BREAK-UP OF THE SAFETY VALVES CREATES A UNIQUE ACRIMONY AND HISSING, SOMEWHAT LIKE THE OPENING OF A SODA BOTTLE CAP. RESEARCHERS AT THE NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST) OF THE UNITED STATES HAVE TRAINED A MACHINE LEARNING ALGORITHM TO RECOGNIZE THIS UNIQUE CRACK\u3002<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[411,4954],"collection":[],"class_list":["post-23283","post","type-post","status-publish","format-standard","hentry","category-news","tag-ai","tag-4954"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/23283","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=23283"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/23283\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=23283"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=23283"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=23283"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=23283"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}