{"id":9281,"date":"2023-01-31T15:46:33","date_gmt":"2023-01-31T13:46:33","guid":{"rendered":"https:\/\/monitorering.ki.dk\/?post_type=glossary&#038;p=9281"},"modified":"2023-01-31T15:46:34","modified_gmt":"2023-01-31T13:46:34","slug":"fft-fast-fourier-transform","status":"publish","type":"glossary","link":"https:\/\/monitorering.ki.dk\/en\/glossary\/fft-fast-fourier-transform\/","title":{"rendered":"FFT (Fast Fourier Transform)"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In the context of structural health monitoring, the Fast Fourier Transform (FFT) is an algorithm used to analyze the frequency content of a measured signal, such as vibration data collected from a structure. The FFT can be used to identify the natural frequencies of a structure, which can indicate the presence of damage or defects. It is a computational tool to convert time domain data into frequency domain data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the graph below we are looking at accelerometer data form an accelerometer on a suspension bridge hanger. From the data it can be hard to tell at which frequency the largest movements are occurring in the hanger. Using an FFT analysis the data now shows energy in the movement at each frequency step. In Figure 2 we see how there are spikes at every frequency with more energy showing the different natural frequencies of the hanger.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"238\" src=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-1024x238.png\" alt=\"FFT Fast Fourier Transform\" class=\"wp-image-9282\" srcset=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-1024x238.png 1024w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-300x70.png 300w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-768x178.png 768w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-100x23.png 100w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1-1396x324.png 1396w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-1.png 1447w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption class=\"wp-element-caption\">Figure 1: Acceleration from a suspension bridge hanger<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">In the acceleration data from the hanger in Figure 2 the FFT suggests that the first mode is at roughly 0.6 Hz. The reason the first mode is not the largest peak on the graph is due to the placement of the accelerometer close to the bottom of the cable.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"225\" src=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-1024x225.png\" alt=\"FFT Fast Fourier Transform\" class=\"wp-image-9284\" srcset=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-1024x225.png 1024w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-300x66.png 300w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-768x169.png 768w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-100x22.png 100w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2-1396x307.png 1396w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-2.png 1459w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption class=\"wp-element-caption\">Figure 2: FFT analysis on the same acceleration data<\/figcaption><\/figure>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"220\" src=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-1024x220.png\" alt=\"FFT Fast Fourier Transform\" class=\"wp-image-9286\" srcset=\"https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-1024x220.png 1024w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-300x64.png 300w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-768x165.png 768w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-100x21.png 100w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3-1396x300.png 1396w, https:\/\/monitorering.ki.dk\/wp-content\/uploads\/2023\/01\/FFT-3.png 1444w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption class=\"wp-element-caption\">Figure 3: FFT with the first mode highlighted to the left, and the peak value highlighted to the right.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>In the context of structural health monitoring, the Fast Fourier Transform (FFT) is an algorithm used to analyze the frequency content of a measured signal, such as vibration data collected from a structure. The FFT &#8230; <\/p>\n<div><a href=\"https:\/\/monitorering.ki.dk\/en\/glossary\/fft-fast-fourier-transform\/\" class=\"more-link\">Read More<\/a><\/div>\n","protected":false},"author":2,"featured_media":0,"menu_order":0,"template":"","meta":{"_monsterinsights_skip_tracking":false,"footnotes":""},"class_list":["post-9281","glossary","type-glossary","status-publish","hentry","no-post-thumbnail"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>FFT (Fast Fourier Transform) - KI Monitoring Monitoring<\/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:\/\/monitorering.ki.dk\/en\/glossary\/fft-fast-fourier-transform\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"FFT (Fast Fourier Transform) - KI Monitoring Monitoring\" \/>\n<meta property=\"og:description\" content=\"In the context of structural health monitoring, the Fast Fourier Transform (FFT) is an algorithm used to analyze the frequency content of a measured signal, such as vibration data collected from a structure. 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