Example: MHKiT-MATLAB Loads Example

The following example will help familiarize you with some of the functions in the MHKiT Loads Module that you can use to assist you in your loads analysis.

Import Loads Data

In this example, since there is no known field loads data for MHK devices, this data comes from a land-based wind turbine. We have a database of 331 files, each containing 10 minutes of data sampled at 50Hz.
As a start, let's look at the data for one of these files to figure out what formatting we need to apply.
data=readtable('../examples/data/loads/data_loads_example.csv');
disp(data)
Timestamp Time uWind_80m WD_ModActive WD_Nacelle WD_NacelleMod LSSDW_Tq LSSDW_My LSSDW_Mz TTTq TT_ForeAft TT_SideSide TB_ForeAft TB_SideSide BL3_FlapMom BL3_EdgeMom BL1_FlapMom BL1_EdgeMom ActivePower yawoffset _________ ______ _________ ____________ __________ _____________ _________ ________ __________ __________ __________ ___________ __________ ___________ ___________ ___________ ___________ ___________ ___________ ___________ 42795 0 3.2268 1 157.3 157.28 -41.381 -234.49 -6.2074 -70.131 -936.25 -12.605 -330.41 1024.8 470.77 -165.54 33.428 -59.452 -5.2797 0.023247 42795 0.02 3.2211 1 157.3 157.28 -38.614 -233.72 -8.8862 -66.916 -942.68 -24.35 -315.45 873.21 469.24 -163.59 32.698 -62.301 -5.6712 0.023247 42795 0.04 3.2235 1 157.3 157.28 -39.718 -234.34 -7.9709 -67.86 -922.97 -22.486 -292.25 876.3 468.74 -166.02 35.496 -61.734 -5.5518 0.023247 42795 0.06 3.2233 1 157.3 157.28 -41.415 -235.65 -10.452 -72.372 -939.52 -33.031 -274.81 763.83 467.37 -164.65 37.952 -64.39 -4.6266 0.023247 42795 0.08 3.2239 1 157.3 157.28 -38.614 -234.76 -8.649 -76.53 -924.77 -29.228 -310.21 704.54 466.32 -161.23 37.431 -65.975 -4.7086 0.023247 42795 0.1 3.2237 1 157.3 157.28 -38.685 -234.85 -10.289 -79.037 -928.51 -37.091 -248.11 644.4 465.72 -160.3 39.067 -68.489 -5.3403 0.023247 42795 0.12 3.222 1 157.3 157.28 -41.381 -237.71 -11.59 -80.423 -920.73 -43.579 -278.46 559.84 461.51 -161.68 37.994 -70.071 -5.7066 0.023247 42795 0.14 3.234 1 157.3 157.28 -42.938 -238.39 -8.5455 -71.959 -919.24 -39.52 -247.49 460.04 462.19 -163.57 37.448 -72.963 -5.5534 0.023247 42795 0.16 3.232 1 157.3 157.28 -39.876 -238.05 -10.932 -84.876 -920.96 -45.469 -264.18 370.26 460.16 -161.21 37.48 -72.92 -4.6258 0.023247 42795 0.18 3.2342 1 157.3 157.28 -42.423 -236.12 -11.04 -86.085 -925.96 -51.507 -247.61 276.54 460.24 -156.73 49.564 -74.857 -4.7098 0.023247 42795 0.2 3.2327 1 157.3 157.28 -40.385 -236.92 -10.749 -80.128 -929.91 -55.847 -183.9 192.78 456.63 -156.82 46.41 -75.747 -5.3535 0.023247 42795 0.22 3.2323 1 157.3 157.28 -39.301 -236.26 -10.994 -72.814 -922.81 -49.589 -142.52 25.183 456.81 -153.82 52.56 -77.545 -5.678 0.023247 42795 0.24 3.233 1 157.3 157.28 -40.405 -235.01 -12.936 -81.484 -929.14 -61.118 -132.18 -31.927 454.1 -154.25 49.733 -76.644 -5.5293 0.023247 42795 0.26 3.2331 1 171.13 171.12 -37.675 -236.55 -12.856 -81.455 -939.77 -61.728 -118.43 -150.51 454.06 -150.75 55.268 -78.018 -4.6333 0.010813 42795 0.28 3.2318 1 171.13 171.12 -41.438 -237.99 -10.099 -89.948 -941.71 -73.891 -78.813 -264.61 453.19 -146.88 59.755 -79.71 -4.6842 0.010813 42795 0.3 3.2322 1 171.13 171.12 -42.62 -238.67 -12.318 -83.077 -941.33 -65.768 -62.099 -334.86 451.59 -148.58 60.169 -80.148 -5.341 0.010813 42795 0.32 3.234 1 171.13 171.12 -39.967 -238.8 -13.839 -94.696 -950.8 -71.843 -77.618 -495.15 448.91 -146.77 59.386 -80.139 -5.6712 0.010813 42795 0.34 3.6612 1 171.13 171.12 -40.103 -239.1 -13.476 -98.913 -943.27 -75.12 -52.048 -561.75 446.32 -147.77 59.736 -80.876 -5.5564 0.010813 42795 0.36 3.6631 1 171.13 171.12 -42.081 -238.28 -13.666 -101.77 -942.97 -87.104 -73.84 -610.4 444.93 -144.96 58.992 -83.202 -4.6213 0.010813 42795 0.38 3.6681 1 171.13 171.12 -42.764 -238.86 -14.95 -93.487 -947.89 -92.595 -50.76 -740.3 443.74 -144.83 63.688 -84.258 -4.7056 0.010813 42795 0.4 3.6722 1 171.13 171.12 -47.609 -239.02 -17.254 -99.532 -940.25 -98.267 -68.236 -869.03 443.75 -146.28 63.113 -86.918 -5.326 0.010813 42795 0.42 3.6635 1 171.13 171.12 -51.782 -240.06 -16.911 -100 -939.7 -99.524 -118.91 -909.82 441.58 -143.72 64.688 -86.971 -5.6524 0.010813 42795 0.44 3.6683 1 171.13 171.12 -52.142 -240.13 -17.648 -106.26 -946.11 -122.48 -136 -956.82 440.03 -143.84 63.123 -91.104 -5.5522 0.010813 42795 0.46 3.6693 1 171.13 171.12 -54.516 -239.15 -17.827 -101.66 -933.98 -119.53 -139.87 -1026.7 438.58 -139.55 66.405 -90.16 -4.5953 0.010813 42795 0.48 3.667 1 171.13 171.12 -55.713 -240.2 -18.007 -102.45 -941.81 -122.52 -208.01 -1143.4 439.38 -143.63 69.518 -90.627 -4.6928 0.010813 42795 0.5 3.6651 1 171.13 171.12 -54.955 -240.5 -18.531 -109.56 -933.36 -131.32 -206.46 -1204.5 439.31 -143.74 64.544 -90.738 -5.3463 0.010813 42795 0.52 3.6621 1 171.13 171.12 -54.169 -237.95 -18.367 -103.51 -933.44 -137.85 -241.73 -1289.2 438.05 -143.25 66.129 -90.833 -5.69 0.010813 42795 0.54 4.0771 1 171.13 171.12 -51.364 -238.79 -21.363 -101.48 -940.45 -135.95 -244.52 -1390.2 438.38 -149.87 65.034 -91.47 -5.5387 0.010813 42795 0.56 4.0795 1 171.13 171.12 -54.328 -237.91 -20.987 -110.65 -932.64 -142.2 -289.6 -1491.1 440.41 -145.94 68.951 -93.315 -4.633 0.010813 42795 0.58 4.0774 1 171.13 171.12 -58.873 -237.16 -18.746 -110.83 -934.79 -141.02 -300.61 -1573.5 438.79 -149.38 76.267 -92.511 -4.6875 0.010813 42795 0.6 4.076 1 171.13 171.12 -57.224 -234.44 -19.518 -108.17 -937.26 -150.63 -275.7 -1638.4 440.26 -150.64 74.86 -92.46 -5.3557 0.010813 42795 0.62 4.0768 1 171.13 171.12 -57.276 -235.13 -20.556 -110.12 -931.98 -158.24 -325.2 -1707.2 440.3 -151.95 76.54 -90.751 -5.6652 0.010813 42795 0.64 4.0737 1 171.13 171.12 -55.617 -233.06 -19.508 -114.31 -931.02 -157.78 -298.75 -1821.3 439.65 -155.67 73.739 -91.283 -5.5353 0.010813 42795 0.66 4.0739 1 171.13 171.12 -58.429 -230.55 -19.596 -113.6 -935.85 -152.57 -324.17 -1916.6 439.29 -150.73 79.438 -87.936 -4.6371 0.010813 42795 0.68 4.0745 1 171.13 171.12 -59.346 -231.08 -18.955 -102.01 -938.01 -152.49 -334.65 -2016.6 439.81 -154.59 82.673 -87.22 -4.7195 0.010813 42795 0.7 4.0789 1 171.13 171.12 -54.808 -230.07 -21.444 -110.94 -936 -153.1 -357.34 -2028.8 441.49 -155.8 80.674 -85.551 -5.3723 0.010813 42795 0.72 4.0757 1 171.13 171.12 -55.347 -228.81 -21.726 -109.94 -937.37 -154.63 -406.72 -2094.3 441.74 -153.13 81.467 -82.813 -5.6463 0.010813 42795 0.74 4.3979 1 171.13 171.12 -50.35 -228.59 -19.787 -112.21 -939.55 -153.93 -439.31 -2136.2 441.25 -152.2 81.487 -80.624 -5.521 0.010813 42795 0.76 4.3964 1 178.77 178.74 -48.558 -230.25 -21.554 -107.76 -942.86 -161.18 -501.08 -2232.2 442.52 -146.06 83.753 -77.866 -4.6356 0.025648 42795 0.78 4.3915 1 178.77 178.74 -46.469 -229.41 -22.55 -118.94 -938.48 -153.99 -539.1 -2231.3 443.19 -143.6 84.691 -76.443 -4.6913 0.025648 42795 0.8 4.3955 1 178.77 178.74 -45.192 -231.08 -21.109 -107.58 -934.3 -162.8 -547.77 -2294 441.91 -142.94 82.489 -76.525 -5.3877 0.025648 42795 0.82 4.3939 1 178.77 178.74 -45.007 -231.81 -23.258 -123.6 -934.32 -154.11 -616.49 -2314 443.08 -137.78 80.188 -75.769 -5.6776 0.025648 42795 0.84 4.3899 1 178.77 178.74 -42.001 -233.35 -23.142 -124.45 -943.86 -156.45 -622.35 -2351.8 441.44 -139.02 77.602 -74.606 -5.5055 0.025648 42795 0.86 4.391 1 178.77 178.74 -43.237 -233 -22.241 -129.97 -943.59 -156.98 -712.19 -2330.3 441.69 -132.65 85.591 -76.23 -4.6277 0.025648 42795 0.88 4.3916 1 178.77 178.74 -40.119 -233.95 -22.452 -130.82 -943.1 -167.1 -750.91 -2434 442.45 -133.9 86.398 -77.212 -4.7158 0.025648 42795 0.9 4.3952 1 178.77 178.74 -42.199 -235.44 -24.87 -131.5 -951.33 -163.1 -740.5 -2424.3 440.52 -132.63 86.46 -77.81 -5.4148 0.025648 42795 0.92 4.3972 1 178.77 178.74 -44.524 -234.55 -23.142 -129.2 -952.73 -171.22 -829.16 -2472.7 438.84 -131.17 85.417 -79.137 -5.7062 0.025648 42795 0.94 4.609 1 178.77 178.74 -42.331 -234.48 -23.904 -123.71 -956.3 -177.54 -862.11 -2474 439.4 -129.97 87.619 -83.08 -5.5609 0.025648 42795 0.96 4.6073 1 178.77 178.74 -46.772 -236.29 -23.124 -125.84 -960.44 -182.15 -877.94 -2526.3 439.24 -131.91 92.106 -85.604 -4.6503 0.025648 42795 0.98 4.6085 1 178.77 178.74 -46.504 -236.47 -22.542 -124.83 -967.94 -178.67 -889.71 -2515 437.18 -131.74 95.759 -86.519 -4.7052 0.025648 42795 1 4.608 1 178.77 178.74 -47.17 -237.11 -23.792 -126.31 -973.95 -169.39 -903.32 -2530.8 434.46 -132.14 95.232 -92.375 -5.4099 0.025648 42795 1.02 4.6059 1 178.77 178.74 -48.815 -237.44 -25.04 -115.9 -975.45 -178.91 -930.89 -2589.5 432.48 -131.85 100.15 -95.676 -5.6655 0.025648 42795 1.04 4.607 1 178.77 178.74 -46.721 -238.14 -23.782 -112.98 -980.39 -178.89 -974.96 -2551.3 431.19 -130.18 100.56 -98.422 -5.4773 0.025648 42795 1.06 4.6092 1 178.77 178.74 -47.025 -239.23 -20.953 -108.26 -985.85 -186.18 -1021.2 -2514 431.49 -127.09 104.99 -102.01 -4.6345 0.025648 42795 1.08 4.6102 1 178.77 178.74 -50.805 -239.33 -21.414 -114.07 -987.05 -178.18 -1042.5 -2531.5 432.85 -129.97 107.5 -103.32 -4.7376 0.025648 42795 1.1 4.6048 1 178.77 178.74 -52.583 -240.32 -20.072 -105.9 -986.78 -177.36 -1091 -2532 430.95 -129.34 107.94 -104.97 -5.4321 0.025648 42795 1.12 4.6085 1 178.77 178.74 -55.615 -240.71 -19.005 -103.72 -987.8 -176.83 -1098.4 -2526.1 431.34 -129.46 109.24 -109.38 -5.6828 0.025648 42795 1.14 4.8372 1 178.77 178.74 -53.036 -241.28 -19.02 -107.52 -995.48 -186.59 -1193.4 -2495.6 429.82 -126.29 109.63 -111.37 -5.4717 0.025648 42795 1.16 4.8357 1 178.77 178.74 -53.128 -242.24 -19.762 -114.07 -999.8 -174.56 -1248.8 -2438.1 429.88 -123.67 115.66 -114.69 -4.6175 0.025648 42795 1.18 4.8375 1 178.77 178.74 -58.803 -242.48 -19.747 -107.94 -1006.6 -172.55 -1282.9 -2416.6 427.69 -124.17 114.69 -115.87 -4.7146 0.025648 42795 1.2 4.8386 1 178.77 178.74 -57.267 -242.48 -18.419 -111.59 -994.39 -181.44 -1373.6 -2395.7 426.58 -122.78 114.69 -117.06 -5.3083 0.025648 42795 1.22 4.8346 1 178.77 178.74 -58.746 -243.1 -17.471 -119.79 -1003.1 -184.74 -1376.3 -2327.9 425.69 -119.12 114.51 -117.9 -5.6625 0.025648 42795 1.24 4.8373 1 178.77 178.74 -58.44 -242.57 -19.161 -116.52 -1000.8 -178.34 -1461 -2257.7 423.04 -116.62 113.93 -115.66 -5.4683 0.025648 42795 1.26 4.8403 1 193.02 192.96 -55.593 -243.96 -20.966 -122.12 -1003.9 -182.62 -1472.9 -2223.8 420.86 -114.06 120.17 -116 -4.6032 0.060275 42795 1.28 4.8348 1 193.02 192.96 -53.794 -242.6 -19.828 -111.92 -1004.8 -164.23 -1508.5 -2150.8 420.34 -109.36 119.72 -114.02 -4.7225 0.060275 42795 1.3 4.8337 1 193.02 192.96 -49.859 -242.42 -18.979 -117.11 -1002.2 -170.57 -1518.1 -2105.3 417.43 -107.07 119.89 -110.03 -5.4525 0.060275 42795 1.32 4.8352 1 193.02 192.96 -51.862 -243.56 -20.021 -110.15 -1002.8 -162.37 -1555.9 -2033.7 413.78 -101.98 119.06 -108.55 -5.6802 0.060275 42795 1.34 4.9563 1 193.02 192.96 -49.574 -241.63 -19.295 -113.19 -993.21 -159.97 -1563.4 -1986.6 412.62 -97.856 122.89 -106.18 -5.4585 0.060275 42795 1.36 4.9543 1 193.02 192.96 -48.745 -240.45 -19.972 -107.61 -1005.8 -154.89 -1616.4 -1924.7 410.75 -96.794 124.9 -102.98 -4.6119 0.060275 42795 1.38 4.9562 1 193.02 192.96 -44.734 -240.74 -19.716 -109.79 -1000.9 -144.94 -1637.1 -1911.1 408.76 -95.247 128.95 -101.22 -4.738 0.060275 42795 1.4 4.9583 1 193.02 192.96 -39.607 -238.14 -19.02 -104.57 -997.68 -126.51 -1648.7 -1811 406.18 -93.526 132.03 -99.44 -5.4732 0.060275 42795 1.42 4.9541 1 193.02 192.96 -38.355 -237.57 -20.571 -104.69 -1001 -139.39 -1697.7 -1752.7 404.96 -94.251 131 -98.02 -5.6723 0.060275 42795 1.44 4.9549 1 193.02 192.96 -36.482 -235.42 -19.377 -106.88 -996.92 -124.11 -1696.2 -1726.2 405.17 -96.747 132.84 -98.086 -5.4577 0.060275 42795 1.46 4.9529 1 193.02 192.96 -38.531 -237.3 -18.49 -94.961 -998.97 -119.62 -1730.7 -1606 405.71 -96.237 140.03 -96.834 -4.6378 0.060275 42795 1.48 4.9547 1 193.02 192.96 -38.717 -237.46 -19.391 -100.8 -999.03 -109.87 -1782.3 -1542.4 404.16 -92.586 142.17 -97.814 -4.7263 0.060275 42795 1.5 4.9537 1 193.02 192.96 -39.935 -235.14 -16.941 -102.6 -991.34 -109.11 -1807.5 -1478.9 403.14 -94.882 145.71 -97.046 -5.4438 0.060275 42795 1.52 4.9519 1 193.02 192.96 -39.635 -235.93 -15.508 -104.78 -995.18 -120.78 -1840.3 -1367.2 404.52 -96.299 142.32 -98.402 -5.6652 0.060275 42795 1.54 5.021 1 193.02 192.96 -38.709 -233.27 -20.668 -94.873 -990.93 -110.58 -1869.6 -1304.7 402.69 -96.055 145.78 -100.78 -5.44 0.060275 42795 1.56 5.0178 1 193.02 192.96 -40.776 -232.54 -17.443 -94.666 -989.4 -102.94 -1901 -1218.3 401.23 -94.563 150.49 -102.31 -4.6318 0.060275 42795 1.58 5.018 1 193.02 192.96 -38.914 -234.2 -18.705 -89.358 -987.32 -103.33 -1947.6 -1052.6 400.27 -95.703 151.74 -105.13 -4.7312 0.060275 42795 1.6 5.0182 1 193.02 192.96 -45.132 -235.97 -15.427 -94.017 -987.91 -106.05 -2002.4 -980.49 397.7 -94.348 156.26 -109 -5.4592 0.060275 42795 1.62 5.0219 1 193.02 192.96 -47.583 -233.55 -16.338 -99.591 -989.68 -98.867 -1967.5 -889.56 396.4 -94.761 157.18 -108.97 -5.6524 0.060275 42795 1.64 5.0234 1 193.02 192.96 -46.127 -233.92 -15.816 -91.245 -985.82 -101.35 -2000.8 -715.92 395.31 -98.1 157.3 -111.83 -5.4306 0.060275 42795 1.66 5.0202 1 193.02 192.96 -48.754 -234.21 -16.598 -79.508 -978.96 -98.448 -1986.7 -659.76 393.75 -95.644 162.26 -112.94 -4.6036 0.060275 42795 1.68 5.0183 1 193.02 192.96 -50.195 -232.21 -15.056 -87.677 -986.03 -99.7 -2004.6 -565.81 389.9 -93.357 164.27 -113.99 -4.6898 0.060275 42795 1.7 5.0223 1 193.02 192.96 -53.725 -235.82 -16.641 -86.321 -993.99 -99.398 -1972.7 -475.18 388.61 -94.595 166.85 -118.44 -5.501 0.060275 42795 1.72 5.0186 1 193.02 192.96 -57.388 -235.3 -15.256 -87.854 -987.82 -98.172 -1995.4 -384.22 386.83 -92.685 166.87 -119.62 -5.6802 0.060275 42795 1.74 4.9619 1 193.02 192.96 -57.063 -234.87 -16.797 -93.723 -997.92 -98.363 -1974.7 -260.24 386.65 -90.528 173.26 -119.93 -5.4141 0.060275 42795 1.76 4.9577 1 212.96 212.92 -61.316 -236.58 -14.136 -97.409 -994.63 -87.845 -1944.1 -206.26 383.35 -92.852 176.04 -121.89 -4.6077 0.045452 42795 1.78 4.9622 1 212.96 212.92 -59.781 -233.63 -18.738 -85.583 -999.61 -98.985 -1957.8 -89.191 380.91 -88.124 179.6 -124.72 -4.7455 0.045452 42795 1.8 4.9616 1 212.96 212.92 -59.765 -235.6 -15.697 -84.374 -999.44 -84.566 -1920.6 -25.241 378.67 -86.284 180.59 -127.82 -5.5101 0.045452 42795 1.82 4.9589 1 212.96 212.92 -58.479 -238.56 -13.618 -84.345 -1007.4 -78.548 -1956.4 113.77 375.04 -82.971 180.33 -129.23 -5.6667 0.045452 42795 1.84 4.9631 1 212.96 212.92 -57.095 -235.99 -15.485 -80.718 -1011 -73.42 -1921.8 202.97 374.98 -82.402 182.26 -132.45 -5.4016 0.045452 42795 1.86 4.961 1 212.96 212.92 -51.902 -237.09 -13.471 -85.613 -998.69 -70.23 -1944.9 232.51 374.3 -76.69 188.52 -129.21 -4.6025 0.045452 42795 1.88 4.9612 1 212.96 212.92 -47.069 -238.96 -12.514 -70.603 -1002.4 -55.845 -1906.3 349.42 373.56 -74.189 187.89 -132.83 -4.712 0.045452 42795 1.9 4.963 1 212.96 212.92 -49.698 -240.16 -9.5634 -69.276 -1012 -46.117 -1933.1 470.37 370.74 -71.783 190.32 -132.37 -5.4958 0.045452 42795 1.92 4.9585 1 212.96 212.92 -41.662 -240.41 -9.2707 -65.147 -994.01 -40.833 -1892 547.39 371.18 -66.299 190.17 -133.42 -5.6426 0.045452 42795 1.94 4.8059 1 212.96 212.92 -39.32 -239.62 -8.7185 -59.485 -1003.6 -35.836 -1916.3 639.64 367.67 -63.535 191.77 -133.51 -5.393 0.045452 42795 1.96 4.8109 1 212.96 212.92 -40.601 -239.72 -5.8227 -56.595 -996.42 -29.512 -1886.4 719.67 368.48 -59.359 195.09 -135.51 -4.6251 0.045452 42795 1.98 4.8054 1 212.96 212.92 -39.051 -241.76 -6.0167 -60.606 -999.83 -26.506 -1896.7 794.77 367.04 -60.46 196.73 -135.31 -4.7128 0.045452 42795 2 4.804 1 212.96 212.92 -41.998 -242.17 -6.154 -60.134 -991.61 -17.472 -1896.6 848.42 367.81 -57.342 200.13 -136.43 -5.4935 0.045452 42795 2.02 4.8078 1 212.96 212.92 -41.749 -244.1 -5.5029 -63.555 -1008.5 -14.556 -1856.2 961.47 363.59 -56.404 199.02 -137.21 -5.6768 0.045452 42795 2.04 4.8081 1 212.96 212.92 -38.908 -242.31 -6.0855 -54.649 -1006 -3.1575 -1839 1050.1 362.25 -55.642 200.91 -138.29 -5.3753 0.045452 42795 2.06 4.8067 1 212.96 212.92 -40.168 -240.39 -6.4482 -50.137 -1001.1 -10.186 -1775.2 1108.5 359.95 -52.474 205.21 -139.14 -4.61 0.045452 42795 2.08 4.8083 1 212.96 212.92 -40.497 -241.86 -6.3266 -59.632 -996.22 -10.864 -1734.3 1204.9 357.66 -54.957 204.52 -137.73 -4.732 0.045452 42795 2.1 4.8027 1 212.96 212.92 -40.101 -241.44 -4.0097 -52.496 -1001.8 -5.4925 -1678.9 1311.4 355.05 -52.626 205.17 -137.71 -5.5116 0.045452 42795 2.12 4.8096 1 212.96 212.92 -39.034 -240.89 -4.3595 -48.485 -1004.1 -0.89243 -1685.6 1362.4 352.82 -51.489 204.47 -138.45 -5.6764 0.045452 42795 2.14 4.5885 1 212.96 212.92 -38.803 -239.15 -6.4316 -59.544 -984.32 1.9368 -1655.4 1394.2 350.9 -50.832 208.82 -136.74 -5.3678 0.045452 42795 2.16 4.584 1 212.96 212.92 -41.13 -237.41 -4.772 -48.308 -992.57 1.8732 -1582.7 1441.3 348.93 -52.021 207.1 -138.05 -4.6051 0.045452 42795 2.18 4.5892 1 212.96 212.92 -39.359 -238.91 -4.2185 -45.89 -985.17 5.6004 -1565.8 1503.3 345.81 -50.237 205.34 -137.77 -4.7101 0.045452 42795 2.2 4.59 1 212.96 212.92 -38.304 -237.59 -3.92 -57.362 -986.51 5.8164 -1507.8 1549.2 344.98 -53.41 208.84 -136 -5.5191 0.045452 42795 2.22 4.5861 1 212.96 212.92 -38.652 -235.98 -3.7816 -60.93 -980.44 4.0535 -1501.2 1620.5 344.03 -54.736 202.71 -137.66 -5.6527 0.045452 42795 2.24 4.5864 1 212.96 212.92 -40.484 -235.5 -4.3754 -51.936 -964.08 15.424 -1498.4 1628.9 342.31 -52.343 206.73 -138.76 -5.4879 0.045452 42795 2.26 4.5883 1 212.38 212.47 -40.015 -235.45 -2.7633 -52.525 -973.97 16.196 -1456.9 1711.1 341.74 -55.185 213.72 -139.3 -4.6187 -0.091159 42795 2.28 4.5822 1 212.38 212.47 -41.479 -234 -4.1165 -53.852 -960.4 11.61 -1460.8 1730.4 341.86 -55.879 210.75 -139.5 -4.7098 -0.091159 42795 2.3 4.5891 1 212.38 212.47 -41.313 -235.06 -2.7995 -47.954 -970.37 10.812 -1434.1 1757.6 341.95 -53.965 211.14 -137.57 -5.5406 -0.091159 42795 2.32 4.586 1 212.38 212.47 -36.542 -235.03 -4.5453 -44.887 -959.84 11.736 -1384.1 1826.1 342.1 -55.39 213.19 -140.49 -5.664 -0.091159 42795 2.34 4.4064 1 212.38 212.47 -39.292 -232.75 -2.9972 -51.906 -958.96 18.291 -1382.5 1846.7 339.61 -56.395 216.71 -139.69 -5.3331 -0.091159 42795 2.36 4.4073 1 212.38 212.47 -41.948 -234.4 -3.7642 -45.713 -945.63 17.362 -1343.4 1862.7 337.92 -56.688 219.72 -141.11 -4.6251 -0.091159 42795 2.38 4.4098 1 212.38 212.47 -42.105 -233.92 -1.0651 -48.22 -951.33 23.908 -1302.4 1872.6 336.85 -54.106 223.51 -140.94 -4.7207 -0.091159 42795 2.4 4.4041 1 212.38 212.47 -42.3 -232.58 -1.5109 -38.193 -948.53 28.982 -1242.8 1876 335.29 -53.848 226.66 -141.36 -5.5613 -0.091159 42795 2.42 4.4063 1 212.38 212.47 -41.979 -229.67 -1.2158 -46.244 -939.87 22.899 -1174.8 1936.6 333.56 -56.037 229.68 -141.76 -5.6399 -0.091159 42795 2.44 4.4049 1 212.38 212.47 -37.956 -228.88 -2.9016 -41.791 -934.86 21.68 -1143.8 1886.3 331.16 -54.855 231.69 -142.14 -5.3346 -0.091159 42795 2.46 4.4074 1 212.38 212.47 -39.047 -228.21 -2.4042 -42.351 -939.24 8.0909 -1082.9 1908 327.93 -56.56 237.64 -139.97 -4.6273 -0.091159 42795 2.48 4.4005 1 212.38 212.47 -37.97 -228.02 -3.2823 -46.303 -935.87 28.487 -1037.9 1906.4 326.89 -55.318 237.86 -142.92 -4.7327 -0.091159 42795 2.5 4.4096 1 212.38 212.47 -38.946 -228.76 -1.6897 -34.094 -935.81 16.203 -991.65 1888.6 322.12 -54.481 237.97 -140.69 -5.4694 -0.091159 42795 2.52 4.4063 1 212.38 212.47 -38.239 -226.37 -3.8452 -37.456 -940.68 25.37 -948.04 1858.5 321.06 -54.026 241.06 -144.84 -5.6433 -0.091159 42795 2.54 4.2526 1 212.38 212.47 -39.174 -227.67 -2.6913 -41.319 -936.2 15.745 -912.83 1839.7 319.45 -52.455 246.93 -144.1 -5.3335 -0.091159 42795 2.56 4.2549 1 212.38 212.47 -39.734 -227.67 -3.916 -48.102 -940.68 20.723 -867.25 1837.3 316.69 -50.905 250.6 -148.06 -4.6183 -0.091159 42795 2.58 4.2526 1 212.38 212.47 -38.334 -226.67 -3.3531 -49.635 -936.66 15.344 -817.87 1796.6 315.72 -49.588 251.37 -150.74 -4.7402 -0.091159 42795 2.6 4.2497 1 212.38 212.47 -41.28 -229.68 -1.602 -45.536 -928.61 22.677 -799.23 1784.8 312.66 -49.976 252.23 -154.39 -5.5778 -0.091159 42795 2.62 4.2503 1 212.38 212.47 -42.801 -228.9 -4.5275 -45.979 -934.77 15.338 -757.32 1767.7 310.89 -51.598 250.7 -156.23 -5.6618 -0.091159 42795 2.64 4.2527 1 212.38 212.47 -40.106 -228.61 -4.7857 -47.925 -916.39 4.7008 -740.11 1733.7 308.15 -47.728 253.68 -159.15 -5.3158 -0.091159 42795 2.66 4.2494 1 212.38 212.47 -41.832 -229.02 -2.7473 -41.378 -928.14 7.9945 -719.89 1684.9 308.39 -48.964 258.03 -160.14 -4.6205 -0.091159 42795 2.68 4.2497 1 212.38 212.47 -41.334 -228.03 -3.3066 -44.209 -929.71 14.677 -644.87 1654.8 307.91 -45.424 256.92 -162.19 -4.7222 -0.091159 42795 2.7 4.2516 1 212.38 212.47 -43.089 -230.2 -1.5634 -50.903 -918.55 6.0062 -628.91 1561.3 307.9 -46.569 258.46 -162.02 -5.5869 -0.091159 42795 2.72 4.2518 1 212.38 212.47 -38.689 -230.12 -3.7854 -41.29 -925.61 3.855 -636.94 1547.9 307.63 -43.799 257.5 -161.79 -5.6411 -0.091159 42795 2.74 4.0887 1 212.38 212.47 -41.804 -229.45 -1.9198 -41.555 -927.1 0.48648 -576.66 1465.3 305.54 -41.931 260.35 -163.72 -5.2925 -0.091159 42795 2.76 4.0921 1 174.5 174.76 -38.631 -230.02 -2.6367 -47.306 -926.08 -11.09 -555.69 1433 307.19 -44.937 261.21 -163.06 -4.6345 -0.25741 42795 2.78 4.0883 1 174.5 174.76 -39.29 -230.48 0.64253 -34.212 -919.94 1.5104 -535.89 1366.7 304.76 -42.285 265.87 -162.87 -4.7414 -0.25741 42795 2.8 4.0914 1 174.5 174.76 -41.489 -230.51 -0.0040064 -40.552 -920.19 3.6618 -438.72 1298.1 304.67 -42.653 264.58 -163.16 -5.597 -0.25741 42795 2.82 4.0939 1 174.5 174.76 -40.924 -229.97 0.71767 -39.963 -924.18 -13.055 -413.18 1224.5 303.01 -44.252 263.15 -165.22 -5.6719 -0.25741 42795 2.84 4.094 1 174.5 174.76 -41.323 -229.6 -0.50097 -46.332 -922.34 -7.5049 -369.92 1104.9 302.2 -38.969 270.31 -163.11 -5.3324 -0.25741 42795 2.86 4.0887 1 174.5 174.76 -40.701 -226.17 0.57808 -38.577 -926.12 -12.954 -298.71 1051 301.8 -40.345 270.66 -162.84 -4.6055 -0.25741 42795 2.88 4.0915 1 174.5 174.76 -41.625 -228.59 2.4765 -45.448 -927.31 -17.424 -277.84 973.56 300.01 -40.891 272.21 -162.29 -4.7466 -0.25741 42795 2.9 4.0905 1 174.5 174.76 -41.053 -229.28 -0.56509 -48.072 -928.65 -20.832 -231.88 910.51 300.27 -40.246 269.78 -160.64 -5.6061 -0.25741 42795 2.92 4.0905 1 174.5 174.76 -45.789 -227.63 3.0933 -33.593 -922.82 -19.431 -223.24 847.38 299.91 -40.02 268.85 -159.07 -5.67 -0.25741 42795 2.94 3.8487 1 174.5 174.76 -41.037 -227.75 -0.49512 -43.295 -912.16 -39.044 -167.81 760.3 300.11 -37.488 274.25 -158.04 -5.2714 -0.25741 42795 2.96 3.8495 1 174.5 174.76 -43.523 -224.44 2.171 -38.223 -911.56 -35.995 -186.49 678.42 300.1 -40.136 270.65 -158.28 -4.6371 -0.25741 42795 2.98 3.8499 1 174.5 174.76 -46.415 -226.71 2.0092 -47.306 -922.34 -44.59 -166.1 600.46 300.56 -37.983 270.45 -156.78 -4.7519 -0.25741 42795 3 3.8514 1 174.5 174.76 -46.259 -228.12 0.47883 -39.019 -913.74 -39.042 -166.44 516.04 301.66 -38.125 268.64 -156.58 -5.6004 -0.25741 42795 3.02 3.8444 1 174.5 174.76 -45.138 -227.51 0.57423 -40.847 -907.7 -46.34 -168.65 441.66 302.22 -38.92 264.52 -158.69 -5.6663 -0.25741 42795 3.04 3.8488 1 174.5 174.76 -50.173 -228.88 0.27549 -48.987 -903.85 -55.257 -162.25 335.66 300.69 -37.274 266.63 -158.44 -5.2868 -0.25741 42795 3.06 3.8484 1 174.5 174.76 -51.133 -228.05 -1.59 -52.997 -915.72 -57.838 -161.83 271.7 304.42 -39.912 263.68 -160.33 -4.6153 -0.25741 42795 3.08 3.8451 1 174.5 174.76 -49.489 -227.82 -1.403 -56.565 -913.01 -63.579 -168.17 160.98 306.17 -41.433 266.44 -159.07 -4.7414 -0.25741 42795 3.1 3.8512 1 174.5 174.76 -49.566 -229.02 -1.2876 -51.552 -906.39 -60.078 -124.62 76.778 303.16 -41.294 263.61 -159.41 -5.6317 -0.25741 42795 3.12 3.8499 1 174.5 174.76 -47.798 -228.71 -2.4357 -55.917 -907.28 -70.665 -160.65 -7.6782 305.65 -43.075 263.18 -160.06 -5.6365 -0.25741 42795 3.14 3.7583 1 174.5 174.76 -47.695 -227.74 -4.2339 -59.898 -907.15 -73.922 -156.79 -92.787 306.25 -41.867 264.29 -161.37 -5.2703 -0.25741 42795 3.16 3.7591 1 174.5 174.76 -45.865 -227.93 -4.2743 -65.766 -910.14 -84.889 -133.19 -228.34 305.8 -44.909 259.94 -160.92 -4.6281 -0.25741 42795 3.18 3.7641 1 174.5 174.76 -46.749 -228.15 -4.5458 -57.391 -913.86 -80.289 -84.806 -284.58 304.33 -47.004 262.84 -163.53 -4.7493 -0.25741 42795 3.2 3.7574 1 174.5 174.76 -48.724 -229.17 -2.5726 -67.772 -909.96 -86.367 -69.992 -385.63 304.19 -49.639 260.71 -164.23 -5.6569 -0.25741 42795 3.22 3.759 1 174.5 174.76 -45.242 -227.88 -4.0031 -60.458 -915.71 -89.217 -62.609 -439.4 303.04 -51.27 257.87 -164.18 -5.6557 -0.25741 42795 3.24 3.7605 1 174.5 174.76 -47.934 -230.03 -4.6625 -77.297 -913.54 -91.79 -26.117 -563.94 301.88 -50.545 262.71 -164.43 -5.239 -0.25741 42795 3.26 3.7603 1 122.99 123.24 -44.17 -226.42 -6.9664 -72.932 -924.03 -86.734 -19.249 -662.57 302.32 -51.856 260.71 -166.22 -4.6303 -0.24469 42795 3.28 3.7607 1 122.99 123.24 -44.739 -228.7 -7.5814 -80.039 -931.2 -96.965 -69.977 -761.52 302 -49.864 260.98 -167.16 -4.7143 -0.24469 42795 3.3 3.7613 1 122.99 123.24 -48.125 -229.43 -7.073 -71.782 -921.11 -100.52 -44.435 -809.28 300.54 -47.727 260.62 -166.04 -5.6207 -0.24469 42795 3.32 3.757 1 122.99 123.24 -44.54 -226.01 -6.3062 -74.584 -921.97 -104.47 -44.719 -936.55 300.69 -47.126 258.62 -169.69 -5.6708 -0.24469 42795 3.34 3.7423 1 122.99 123.24 -43.649 -229.28 -10.61 -91.599 -930.12 -108.72 -68.641 -1039.8 299.52 -45.742 263.11 -170.04 -5.2236 -0.24469 42795 3.36 3.7421 1 122.99 123.24 -42.869 -230.74 -10.37 -85.2 -924.85 -113.03 -122.83 -1105.6 300.07 -45.147 263.44 -170.18 -4.6476 -0.24469 42795 3.38 3.741 1 122.99 123.24 -46.642 -233.78 -10.712 -98.677 -929.95 -116.76 -105.6 -1232 299.24 -42.219 264.25 -172.11 -4.7376 -0.24469 42795 3.4 3.7416 1 122.99 123.24 -45.835 -230.93 -13.574 -88.591 -927.79 -121.24 -148.11 -1269.3 298.83 -42.041 263.71 -171.79 -5.649 -0.24469 42795 3.42 3.7402 1 122.99 123.24 -48.897 -231.87 -13.279 -95.61 -926.02 -124.07 -215.9 -1375.5 296.15 -38.425 262.57 -175.25 -5.6437 -0.24469 42795 3.44 3.7388 1 122.99 123.24 -45.56 -234.2 -15.809 -104.69 -931.2 -130.87 -255.06 -1355.1 295.46 -35.576 265.9 -176.25 -5.2484 -0.24469 42795 3.46 3.7394 1 122.99 123.24 -46.199 -233.07 -15.39 -104.57 -931.67 -125.48 -236.68 -1509 294.55 -36.947 264.7 -176.18 -4.6168 -0.24469 42795 3.48 3.7446 1 122.99 123.24 -43.058 -233.5 -16.204 -93.958 -925.77 -138.36 -258.3 -1543.9 295.01 -36.019 264.1 -177.29 -4.7598 -0.24469 42795 3.5 3.7394 1 122.99 123.24 -46.309 -233.46 -14.904 -99.296 -936.07 -126.88 -259.51 -1625 293.32 -34.278 266.12 -178.82 -5.6625 -0.24469 42795 3.52 3.7408 1 122.99 123.24 -42.508 -233.23 -18.16 -105.75 -939.57 -144.14 -311.16 -1691 291.66 -33.22 264.48 -178.11 -5.6305 -0.24469 42795 3.54 3.7568 1 122.99 123.24 -46.14 -232.43 -16.462 -105.78 -934.09 -143.58 -291.5 -1764.1 290.5 -33.92 270.1 -176.76 -5.3474 -0.24469 42795 3.56 3.7565 1 122.99 123.24 -44.985 -234.21 -16.223 -109.62 -941.38 -145.06 -290.89 -1842.3 288.26 -33.821 266.52 -179.9 -4.6194 -0.24469 42795 3.58 3.7602 1 122.99 123.24 -43.907 -234.8 -17.255 -102.92 -944.14 -141.91 -301.83 -1901.6 287.46 -32.57 271.22 -179.97 -4.75 -0.24469 42795 3.6 3.7592 1 122.99 123.24 -42.379 -234.34 -16.9 -98.5 -938.34 -141.68 -322.33 -1945.1 286.41 -30.318 273.3 -179.98 -5.6554 -0.24469 42795 3.62 3.7567 1 122.99 123.24 -42.842 -232.69 -15.21 -94.46 -942.7 -149.04 -340.88 -1997.8 283.93 -32.877 276.14 -180.92 -5.6222 -0.24469 42795 3.64 3.761 1 122.99 123.24 -42.514 -231.17 -15.651 -95.551 -943.65 -147.75 -408.58 -2031.5 282.62 -30.806 280.9 -179.99 -5.2085 -0.24469 42795 3.66 3.7629 1 122.99 123.24 -42.653 -233.07 -16.416 -100.39 -944.31 -150.74 -431.38 -2113.5 283.1 -29.849 282.53 -181.78 -4.6326 -0.24469 42795 3.68 3.758 1 122.99 123.24 -46.175 -231.73 -14.593 -96.878 -944.8 -155.53 -472.66 -2146.5 283.68 -30.394 281.45 -179.9 -4.7493 -0.24469 42795 3.7 3.7616 1 122.99 123.24 -46.046 -232.01 -14.354 -97.586 -943.65 -155.05 -495.63 -2203.3 283.79 -28.939 282.58 -177.67 -5.5718 -0.24469 42795 3.72 3.7576 1 122.99 123.24 -43.845 -229.29 -16.411 -96.229 -945.46 -154.78 -500.04 -2220.5 283.46 -31.192 285.32 -178.08 -5.6275 -0.24469 42795 3.74 3.9138 1 122.99 123.24 -46.912 -229.88 -15.173 -95.02 -948.32 -159.79 -617.24 -2262.1 283.82 -28.869 288.66 -177.49 -5.1999 -0.24469 42795 3.76 3.9129 1 98.563 98.644 -46.786 -230.08 -13.014 -97.409 -942.1 -159.97 -670.83 -2308.6 284.61 -29.59 290.29 -174.8 -4.6348 -0.081098 42795 3.78 3.9097 1 98.563 98.644 -45.923 -231.02 -15.213 -90.951 -948.84 -165.64 -711.57 -2314.3 282.58 -25.355 289.88 -174.35 -4.7553 -0.081098 42795 3.8 3.9107 1 98.563 98.644 -49.391 -228.87 -10.834 -99.562 -943.28 -165.87 -752.49 -2304.7 283.32 -25.106 290.8 -172.21 -5.5767 -0.081098 42795 3.82 3.9124 1 98.563 98.644 -48.089 -230.01 -9.7997 -92.13 -942.04 -168.26 -812.4 -2340.7 281.15 -23.22 293.31 -172.19 -5.6467 -0.081098 42795 3.84 3.9054 1 98.563 98.644 -49.368 -229.41 -11.86 -85.023 -943.33 -166.43 -866.16 -2320.6 279.23 -23.216 294.98 -171.11 -5.1976 -0.081098 42795 3.86 3.9116 1 98.563 98.644 -47.625 -228.8 -8.9753 -94.371 -939.6 -172.05 -886.69 -2336.2 279.46 -19.683 292.87 -170.42 -4.6378 -0.081098 42795 3.88 3.9126 1 98.563 98.644 -50.528 -229.44 -10.987 -80.511 -949.28 -166.37 -889.24 -2308.4 278.2 -19.504 294.82 -169.83 -4.7444 -0.081098 42795 3.9 3.9092 1 98.563 98.644 -48.447 -228.15 -8.9787 -96.996 -949.91 -173.65 -974.47 -2350.4 279.05 -18.209 292.27 -164.95 -5.6855 -0.081098 42795 3.92 3.9099 1 98.563 98.644 -49.328 -230.12 -8.6342 -80.718 -950.62 -165.66 -980.84 -2297.1 279.06 -17.729 293.31 -166.97 -5.6569 -0.081098 42795 3.94 3.9846 1 98.563 98.644 -50.806 -228.74 -8.6795 -88.886 -954.48 -164.08 -998.08 -2279.2 279.55 -18.893 296.21 -164.63 -5.1886 -0.081098 42795 3.96 3.9875 1 98.563 98.644 -47.852 -228.41 -7.9187 -85.377 -955.7 -170.37 -1037.5 -2291.3 279.13 -18.084 290.94 -164.98 -4.6043 -0.081098 42795 3.98 3.987 1 98.563 98.644 -49.636 -228.57 -9.8347 -89.565 -967.33 -161.36 -1040.8 -2298.9 279.1 -18.891 293.42 -163.56 -4.7301 -0.081098 42795 4 3.986 1 98.563 98.644 -52.013 -228.43 -6.5201 -83.608 -965.42 -172.18 -1050.1 -2276.1 279.34 -17.479 294.93 -165.63 -5.702 -0.081098 42795 4.02 3.9819 1 98.563 98.644 -50.729 -230.36 -7.6433 -87.766 -967.77 -162.5 -1101.8 -2255.6 279.52 -17.022 293.25 -166.2 -5.6418 -0.081098 42795 4.04 3.9854 1 98.563 98.644 -48.33 -229.38 -9.3768 -86.144 -960.94 -160.53 -1126.5 -2222.4 280.17 -19.497 295.75 -167.47 -5.1807 -0.081098 42795 4.06 3.9831 1 98.563 98.644 -48.235 -230.46 -8.6593 -83.46 -972.24 -160.42 -1220.6 -2170.6 277.36 -17.714 295.36 -170.86 -4.6047 -0.081098 42795 4.08 3.9876 1 98.563 98.644 -47.904 -232.65 -9.5677 -81.956 -972.26 -160.25 -1228.3 -2093.5 278.01 -15.836 298.44 -172.63 -4.7545 -0.081098 42795 4.1 3.9848 1 98.563 98.644 -48.501 -234.62 -8.0854 -82.31 -978.47 -147.69 -1298.7 -2103.7 275.93 -12.357 295.85 -175.27 -5.6859 -0.081098 42795 4.12 3.9885 ...

Format Loads Data with datetime index

Our file above shows us that we have two references to time, but neither are in the right format. The "Timestamp" column is what will give us the datetime index that we are looking for, but we first need to convert it from Microsoft Excel format to unix time.
newtime = excel_to_datetime(data.Timestamp);
data.time = newtime
data = 30000×21 table
 TimestampTimeuWind_80mWD_ModActiveWD_NacelleWD_NacelleModLSSDW_TqLSSDW_MyLSSDW_MzTTTqTT_ForeAftTT_SideSideTB_ForeAftTB_SideSideBL3_FlapMomBL3_EdgeMomBL1_FlapMomBL1_EdgeMomActivePoweryawoffsettime
14.2795e+0403.22681157.3028157.2796-41.3807-234.4874-6.2074-70.1307-936.2470-12.6052-330.41081.0248e+03470.7747-165.541833.4277-59.4524-5.27970.023201-Mar-2017 01:28:40
24.2795e+040.02003.22111157.3028157.2796-38.6145-233.7159-8.8862-66.9163-942.6759-24.3505-315.4456873.2142469.2447-163.588032.6978-62.3006-5.67120.023201-Mar-2017 01:28:41
34.2795e+040.04003.22351157.3028157.2796-39.7180-234.3420-7.9709-67.8600-922.9710-22.4858-292.2521876.2995468.7365-166.018135.4958-61.7336-5.55180.023201-Mar-2017 01:28:41
44.2795e+040.06003.22331157.3028157.2796-41.4151-235.6456-10.4518-72.3720-939.5153-33.0309-274.8128763.8338467.3735-164.645637.9525-64.3901-4.62660.023201-Mar-2017 01:28:41
54.2795e+040.08003.22391157.3028157.2796-38.6145-234.7560-8.6490-76.5300-924.7715-29.2284-310.2134704.5378466.3188-161.233937.4307-65.9748-4.70860.023201-Mar-2017 01:28:41
64.2795e+040.10003.22371157.3028157.2796-38.6845-234.8474-10.2891-79.0366-928.5129-37.0909-248.1094644.4049465.7248-160.301539.0674-68.4894-5.34030.023201-Mar-2017 01:28:41
74.2795e+040.12003.22201157.3028157.2796-41.3807-237.7115-11.5904-80.4227-920.7288-43.5790-278.4642559.8398461.5141-161.684137.9935-70.0714-5.70660.023201-Mar-2017 01:28:41
84.2795e+040.14003.23401157.3028157.2796-42.9378-238.3895-8.5455-71.9591-919.2370-39.5198-247.4940460.0362462.1886-163.572937.4482-72.9629-5.55340.023201-Mar-2017 01:28:41
94.2795e+040.16003.23201157.3028157.2796-39.8764-238.0531-10.9318-84.8756-920.9632-45.4685-264.1785370.2577460.1646-161.207337.4802-72.9195-4.62580.023201-Mar-2017 01:28:41
104.2795e+040.18003.23421157.3028157.2796-42.4233-236.1212-11.0405-86.0847-925.9611-51.5074-247.6080276.5414460.2370-156.728749.5637-74.8570-4.70980.023201-Mar-2017 01:28:41
114.2795e+040.20003.23271157.3028157.2796-40.3851-236.9230-10.7490-80.1278-929.9106-55.8470-183.9013192.7835456.6259-156.824346.4102-75.7466-5.35350.023201-Mar-2017 01:28:41
124.2795e+040.22003.23231157.3028157.2796-39.3011-236.2586-10.9937-72.8143-922.8122-49.5893-142.524825.1835456.8086-153.819252.5603-77.5447-5.67800.023201-Mar-2017 01:28:41
134.2795e+040.24003.23301157.3028157.2796-40.4046-235.0124-12.9361-81.4843-929.1419-61.1183-132.1809-31.9271454.1006-154.254349.7332-76.6444-5.52930.023201-Mar-2017 01:28:41
144.2795e+040.26003.23311171.1340171.1232-37.6752-236.5468-12.8559-81.4548-939.7711-61.7283-118.4333-150.5126454.0640-150.751155.2679-78.0185-4.63330.010801-Mar-2017 01:28:41
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Loads Analysis

Now that we have our loads data in the correct format for MHKiT, we do some analysis.

Damage Equivalent Loads

Let's say that we wanted to investigate fatigue. We can do this by calculating short-term damage equivalent loads (DELs). To use this function, we need the variable we want to analyze and its corresponding material slope factor. In this instance, we want to just look at our tower base moment and our blade 1 root flap moment. Our tower is steel while our blade is composite so they will have different material slopes.
We call our function and apply the default inputs of using at least 100 bins for the load ranges and we let t=600 seconds so that we get an equivalent 1Hz DEL for our 10-minute file.
% use the fatigue function to calculate the damage equivalent load for this file
DEL_tower = damage_equivalent_load(data.TB_ForeAft,4,'bin_num',100,'data_length',600)
DEL_tower = 3.9126e+03
DEL_blade = damage_equivalent_load(data.BL1_FlapMom,10,'bin_num',100,'data_length',600)
DEL_blade = 1.4358e+03

Calculate Loads Statistics

Another important part of loads analysis is looking at statistics. Here, we use another function to help us calculate the mean, max, min, and std for this 10-minute file. Per standards, a valid statistical window has to be consecutive in time with the correct number of datapoints. So, if this 10 minute file did not meet this criteria, then no stats would be generated and a warning message would appear.
NOTE: Sometimes individual files may contain enough data for multiple statistical windows. This function can still handle this scenario as long as the correct inputs are specified.
% First we need to convert the Matlab table to a structure
data = removevars(data,{'Timestamp','Time'});
datast = table2struct(data,'ToScalar',true)
datast = struct with fields:
uWind_80m: [30000×1 double] WD_ModActive: [30000×1 double] WD_Nacelle: [30000×1 double] WD_NacelleMod: [30000×1 double] LSSDW_Tq: [30000×1 double] LSSDW_My: [30000×1 double] LSSDW_Mz: [30000×1 double] TTTq: [30000×1 double] TT_ForeAft: [30000×1 double] TT_SideSide: [30000×1 double] TB_ForeAft: [30000×1 double] TB_SideSide: [30000×1 double] BL3_FlapMom: [30000×1 double] BL3_EdgeMom: [30000×1 double] BL1_FlapMom: [30000×1 double] BL1_EdgeMom: [30000×1 double] ActivePower: [30000×1 double] yawoffset: [30000×1 double] time: [30000×1 datetime]
% calculate the means, maxs, mins, and stdevs of this file
stats = get_statistics(datast,50);
% show the mean results
disp(stats.mean)
uWind_80m: 7.7733 WD_ModActive: 1 WD_Nacelle: 178.6123 WD_NacelleMod: 178.6026 LSSDW_Tq: 127.2442 LSSDW_My: -252.2381 LSSDW_Mz: 3.5032 TTTq: 7.0326 TT_ForeAft: -846.6634 TT_SideSide: 271.4466 TB_ForeAft: 3.7850e+03 TB_SideSide: 7.1992 BL3_FlapMom: -494.8583 BL3_EdgeMom: 266.7904 BL1_FlapMom: -452.6527 BL1_EdgeMom: 21.2600 ActivePower: 234.5783 yawoffset: 0.0097
At this point, it would be nice to start visualizing some of this data. In order to do this, we need to calculate the stats and DELs for all the files in our database. In this case, it would be done through a loop that imports each file and applies all the functions we just saw. To speed things up, this was already done so we just need to import the results.
% load statistics results from csv
dmeans = table2struct(readtable('../examples/data/loads/data_loads_means.csv'),'ToScalar',true)
dmeans = struct with fields:
uWind_80m: [331×1 double] WD_ModActive: [331×1 double] WD_Nacelle: [331×1 double] WD_NacelleMod: [331×1 double] LSSDW_Tq: [331×1 double] LSSDW_My: [331×1 double] LSSDW_Mz: [331×1 double] TTTq: [331×1 double] TT_ForeAft: [331×1 double] TT_SideSide: [331×1 double] TB_ForeAft: [331×1 double] TB_SideSide: [331×1 double] BL3_FlapMom: [331×1 double] BL3_EdgeMom: [331×1 double] BL1_FlapMom: [331×1 double] BL1_EdgeMom: [331×1 double] ActivePower: [331×1 double] yawoffset: [331×1 double]
dmaxs = table2struct(readtable('../examples/data/loads/data_loads_maxs.csv'),'ToScalar',true);
dmins = table2struct(readtable('../examples/data/loads/data_loads_mins.csv'),'ToScalar',true);
dstd = table2struct(readtable('../examples/data/loads/data_loads_std.csv'),'ToScalar',true);

Plot Load Statistics

Now that we have all of our stats, let's make a scatter plot that can give us a visual. Using the statplotter function, we can quickly create a standard scatter plot showing how load variables trend with wind speed. Using this we can quickly spot expected trends and track down outliers.
figure = plot_statistics(dmeans.uWind_80m,dmeans.BL1_FlapMom,dmins.BL1_FlapMom,dmaxs.BL1_FlapMom,"y_stdev",dstd.BL1_FlapMom,"xlabel",'Wind Speed [m/s]',"ylabel",'Blade Flap Mom [kNm]');
figure2 = plot_statistics(dmeans.uWind_80m,dmeans.TB_ForeAft,dmins.TB_ForeAft,dmaxs.TB_ForeAft,"y_stdev",dstd.TB_ForeAft,"xlabel",'Wind Speed [m/s]',"ylabel",'Tower Base Mom [kNm]');
Another common step is to bin the statistical data. This can easily be done with the bin_stats function from the loads module shown below. A warning message will show if there are any bins that were not filled.
% create array containing wind speeds to use as bin edges
b_edges = 3:1:25 ;
% apply function for means, maxs, mins, and DELs
wind_means = bin_statistics(dmeans,dmeans.uWind_80m,b_edges);
Warning: some bins may be empty!
wind_max = bin_statistics(dmaxs,dmeans.uWind_80m,b_edges);
Warning: some bins may be empty!
wind_min = bin_statistics(dmins,dmeans.uWind_80m,b_edges);
Warning: some bins may be empty!
wind_DEL = bin_statistics(dmaxs,dmeans.uWind_80m,b_edges);
Warning: some bins may be empty!
 
wind_min.averages
ans = struct with fields:
uWind_80m: [22×1 double] WD_ModActive: [22×1 double] WD_Nacelle: [22×1 double] WD_NacelleMod: [22×1 double] LSSDW_Tq: [22×1 double] LSSDW_My: [22×1 double] LSSDW_Mz: [22×1 double] TTTq: [22×1 double] TT_ForeAft: [22×1 double] TT_SideSide: [22×1 double] TB_ForeAft: [22×1 double] TB_SideSide: [22×1 double] BL3_FlapMom: [22×1 double] BL3_EdgeMom: [22×1 double] BL1_FlapMom: [22×1 double] BL1_EdgeMom: [22×1 double] ActivePower: [22×1 double] yawoffset: [22×1 double]
Now let's make some more plots with the binned data. Here we use the binned data and corresponding standard deviations as inputs to the binplotter function.
bcenters = 3.5:1:24.5
bcenters = 1×22
3.5000 4.5000 5.5000 6.5000 7.5000 8.5000 9.5000 10.5000 11.5000 12.5000 13.5000 14.5000 15.5000 16.5000 17.5000 18.5000 19.5000 20.5000 21.5000 22.5000 23.5000 24.5000
plot_bin_statistics(bcenters,wind_means.averages.TB_ForeAft,wind_max.averages.TB_ForeAft,wind_min.averages.TB_ForeAft,wind_means.std.TB_ForeAft,wind_max.std.TB_ForeAft,wind_min.std.TB_ForeAft,"xlabel",'Wind Speed [m/s]',"ylabel",'TB_ForeAft',"title",'Binned Stats');