{"id":235070,"date":"2026-04-13T02:03:56","date_gmt":"2026-04-13T07:03:56","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2026\/04\/non-stationary-load-extrapolation-over-long-horizons-based-on-a-frequency-consistent-diffusion-model"},"modified":"2026-04-13T02:03:56","modified_gmt":"2026-04-13T07:03:56","slug":"non-stationary-load-extrapolation-over-long-horizons-based-on-a-frequency-consistent-diffusion-model","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2026\/04\/non-stationary-load-extrapolation-over-long-horizons-based-on-a-frequency-consistent-diffusion-model","title":{"rendered":"Non-Stationary Load Extrapolation over Long Horizons Based on a Frequency-Consistent Diffusion Model"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/non-stationary-load-extrapolation-over-long-horizons-based-on-a-frequency-consistent-diffusion-model.jpg\"><\/a><\/p>\n<p>\u3010\u3011 Full article: (Authored by Yu Bai and Fei Meng, from University of Shanghai for Science and Technology, China.) <\/p>\n<p>Engineering load signals support durability analysis because they reflect real service conditions. Long-duration load histories are essential for fatigue-life prediction and reliability assessment. However, long-term field measurements are often costly and difficult to obtain. Therefore, extending short measurements into representative long histories is practically important. This study proposes a frequency-consistent diffusion_model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals under turning conditions. load_extrapolation.<\/p>\n<hr>\n<p>\n<a name=\"abstract\">Abstract<\/a><\/p>\n<p>This study proposes a frequency-consistent diffusion model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals. Condition tokens and spectral-consistency constraints are introduced to preserve spectral and fatigue-related characteristics during tenfold extrapolation. The generated signals are evaluated using PSD, band-energy proportion, Range-Mean distribution, and unit pseudo-damage. Compared with DDPM, FCDM better preserves dominant frequencies, harmonic structure, and band-energy allocation. The dominant frequency error is 1.02%, and the mean harmonic error is 0.52%. FCDM also shows smaller band-energy allocation errors across all frequency bands. In addition, it reproduces the bimodal clustering pattern in the Range-Mean distribution more accurately. The unit pseudo-damage is 1.0978 for FCDM and 1.1280 for DDPM. These results indicate that FCDM improves spectral fidelity and fatigue-related consistency in long-sequence load extrapolation.<\/p>\n<p><a href=\"https:\/\/tinyurl.com\/mr34th86\/articles?searchcode=Diffusion+Model&searchfield=keyword&page=1\" target=\"_blank\">Diffusion Model<\/a>, <a href=\"https:\/\/tinyurl.com\/mr34th86\/articles?searchcode=+Load+Extrapolation&searchfield=keyword&page=1\" target=\"_blank\"> Load Extrapolation<\/a>, <a href=\"https:\/\/tinyurl.com\/mr34th86\/articles?searchcode=+Frequency-Consistency&searchfield=keyword&page=1\" target=\"_blank\"> Frequency-Consistency<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u3010\u3011 Full article: (Authored by Yu Bai and Fei Meng, from University of Shanghai for Science and Technology, China.) Engineering load signals support durability analysis because they reflect real service conditions. Long-duration load histories are essential for fatigue-life prediction and reliability assessment. However, long-term field measurements are often costly and difficult to obtain. Therefore, extending [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1902,1497],"tags":[],"class_list":["post-235070","post","type-post","status-publish","format-standard","hentry","category-bioengineering","category-energy"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/235070","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=235070"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/235070\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=235070"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=235070"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=235070"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}