{"id":6429,"date":"2022-02-02T08:22:46","date_gmt":"2022-02-02T08:22:46","guid":{"rendered":"https:\/\/vikinganalytics.se\/?p=6429"},"modified":"2023-03-28T09:27:52","modified_gmt":"2023-03-28T09:27:52","slug":"vibration-monitoring-of-rotating-machinery-in-ships-an-ai4eu-project","status":"publish","type":"post","link":"https:\/\/www.vikinganalytics.se\/vibration-monitoring-of-rotating-machinery-in-ships-an-ai4eu-project\/","title":{"rendered":"Vibration monitoring of rotating machinery in ships \u2013 An AI4EU project"},"content":{"rendered":"<p><span data-contrast=\"auto\"><a href=\"https:\/\/www.ai4europe.eu\/\">AI4EU<\/a>\u00a0is a European Union Artificial Intelligence project which aims to bring together the AI community and facilitate knowledge transfer from research to business application.\u00a0 It provides an experiments platform that promotes the sharing and deployment of AI models.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In 2021, Viking Analytics has been selected by AI4EU as a solution provider in AI technologies. We worked with a Challenge Owner to develop a solution in vibration monitoring of rotating equipment in ships.\u00a0\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p aria-level=\"2\"><strong>Challenge\u00a0<\/strong><\/p>\n<p><span data-contrast=\"auto\">The challenge owner commercializes a Digital Health Monitoring System for the condition monitoring of rotating machinery in ships. They carry out the condition monitoring using vibration analysis and use it to monitor critical machines, such as motors, pumps, and fans. Their goal is to provide better maintenance scheduling to reduce unnecessary interventions in the machines, prevent accidents and increase the resting time of the vessel crew.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Monitoring the health of the machine is a complex problem given that many faults can be combined and affect the typically monitored parameters in different ways. In ships, the main challenge is that it requires a vibration monitoring expert on board, which may not be feasible given the increase in overhead costs. Furthermore, data transmission is expensive and difficult due to synchronization issues and the limited internet coverage at sea.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p aria-level=\"2\"><strong>Asset Monitoring\u00a0<\/strong><\/p>\n<p><span data-contrast=\"auto\">The challenge focused on fans. Ships normally do not have many different types of fans, so the equipment was classified in three categories mainly. In total, data was received from 1160 assets. Each asset had two or three tri-axial vibration sensors on them. Given the constraints on data transmission, only 1-second-long measurements per axis and measuring point were available.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p aria-level=\"2\"><strong>Solution\u00a0<\/strong><\/p>\n<p><span data-contrast=\"auto\">Our approach<\/span><span data-contrast=\"auto\">\u00a0took<\/span><span data-contrast=\"auto\">\u00a0advantage of the number of machines and the fact that it remains constant across all ships. Thus, the proposed solution is valuable in ranking the assets most likely to have an atypical behavior. Once the asset that might require further inspection is selected, it also identifies the measuring point and\/or axis that the expert could start to examine.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The proposed solution is based on Viking Analytics\u2019\u00a0<a href=\"https:\/\/vikinganalytics.se\/multiviz-vibration-api\/\">MultiViz Vibration<\/a>\u00a0and its feature called Blacksheep Detection, which is used for the identification of assets on a population. Some modifications were performed on the basis algorithm and optimization algorithm to rank the assets by the number of atypical measurements. As the measurements were recorded with a high resolution, it was possible to split the 1-second-long measurements into smaller signals defined by a number of rotations on the asset. Then, all the signals from all measurement points and axis were concatenated to represent a single source.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The results of the Blacksheep Detection are a list of the assets according to how atypical each of them is likely to become. Then, each individual asset was subjected to Mode Identification Analysis. Given that all measurement points and axis were transformed into a single source, Mode Identification enables the expert to identify which measurement point and axis may be worth inspecting first.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335551550&quot;:6,&quot;335551620&quot;:6,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<figure id=\"attachment_35611\" class=\"wp-caption aligncenter\" aria-describedby=\"caption-attachment-35611\"><img decoding=\"async\" class=\"wp-image-35611 size-full\" src=\"https:\/\/vikinganalytics.se\/wp-content\/uploads\/2022\/01\/Blacksheep_AI4EU_.jpg\" sizes=\"(max-width: 800px) 100vw, 800px\" srcset=\"https:\/\/vikinganalytics.se\/wp-content\/uploads\/2022\/01\/Blacksheep_AI4EU_.jpg 800w, https:\/\/vikinganalytics.se\/wp-content\/uploads\/2022\/01\/Blacksheep_AI4EU_-300x225.jpg 300w, https:\/\/vikinganalytics.se\/wp-content\/uploads\/2022\/01\/Blacksheep_AI4EU_-768x576.jpg 768w, https:\/\/vikinganalytics.se\/wp-content\/uploads\/2022\/01\/Blacksheep_AI4EU_-500x375.jpg 500w\" alt=\"\" width=\"800\" height=\"600\" \/><figcaption id=\"caption-attachment-35611\" class=\"wp-caption-text\"><em>Blacksheep Detection results for a fan category. Each thin line represents a different asset. Their identifying codes have been removed to avoid identification.<\/em><\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p><span data-contrast=\"auto\">Using Blacksheep Detection to identify the atypical assets and Mode Identification over the measurement point simplifies the work of the expert<\/span><span data-contrast=\"auto\">,\u00a0<\/span><span data-contrast=\"auto\">who now is\u00a0<\/span><span data-contrast=\"auto\">able<\/span><span data-contrast=\"auto\">\u00a0to prioritize the assets that are most likely to have an issue and provide an assessment of them. This allows for a more efficient work routine for experts that analyze the data and effective scheduling of maintenance activities.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI4EU\u00a0is a European Union Artificial Intelligence project which aims to bring together the AI community and facilitate knowledge transfer from research to business application.\u00a0 It provides an experiments platform that promotes the sharing and deployment of AI models.\u00a0\u00a0 In 2021, Viking Analytics has been selected by AI4EU as a solution provider in AI technologies. We [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":6430,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[24],"tags":[],"class_list":["post-6429","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Vibration monitoring of rotating machinery in ships \u2013 An AI4EU project - Viking Analytics - MultiViz AI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.vikinganalytics.se\/vibration-monitoring-of-rotating-machinery-in-ships-an-ai4eu-project\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Vibration monitoring of rotating machinery in ships \u2013 An AI4EU project - Viking Analytics - MultiViz AI\" \/>\n<meta property=\"og:description\" content=\"AI4EU\u00a0is a European Union Artificial Intelligence project which aims to bring together the AI community and facilitate knowledge transfer from research to business application.\u00a0 It provides an experiments platform that promotes the sharing and deployment of AI models.\u00a0\u00a0 In 2021, Viking Analytics has been selected by AI4EU as a solution provider in AI technologies. 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