Wavelength fixing mechanism

The data is collected to establish the wavelength fixing mechanism for short-pitch rail corrugation. Average wavelengths are measured on each of the heavily corrugated rail track curves using a ruler. Train speeds are downloaded from a few locomotive black boxes. The speeds data is extracted into an excel spreadsheet. The blackbox downloads data every minute and captures Global Positioning System (GPS) coordinates for the location where the train speeds were captured. Together with train speeds, corrugation wavelengths are used to calculate corrugation frequencies for each track curve. The average corrugation frequencies were saved for correlation to a locomotive traction wheelset natural frequencies. Experimental Modal Analysis was conducted to obtain the point Frequency Response Functions (FRF) of the class D39200 locomotive wheelset. The wheelset resonance modes were obtained and a fundamental resonance mode at 108 Hz is found have a more closer correlation to corrugation frequencies for each track curve. The GPS coordinates were used on Google Earth Pro to view the terrain and gradients of the track curves. The blackbox data downloaded also recorded whether the train was in traction or braking during recording of the data, together with that information, the gradient on Google Earth Pro was used to determine the direction of the train. The excel spreadsheets named with locomotive numbers contain the GPS data downloaded in decimal form, whilst the files with a CSV format shows the GPS data that has been converted to degrees, minutes and seconds. A Finite Element Model was developed to validate the resonance modes of the traction wheelset and also to investigate the mode shapes of the wheels and axle on vibrational excitation. The axle and wheel drawings for the D39200 wheelset used for the model are attached. Modala Analysis was conducted on the rail to capture the vibration phase midspan between two sleepers. The vibration phase was captured for rail on FY and PY-type concrete sleepers; and also on steel sleepers. This exercise was done to investigate the correlation of the vibration phase of the wheels to that of the rail on different types of sleepers. Two excel files named "Rail on steel sleeper vs PY or FY type concrete sleeper". This data also has the captured vibration phase data for the wheels.本数据集用于建立短节距钢轨波磨（short-pitch rail corrugation）的波长固定机制。研究人员采用直尺对每一处波磨严重的轨道曲线段的平均波长进行测量。从多台机车黑匣子中导出列车运行速度数据，并将其整理至Excel电子表格。该黑匣子以每分钟一次的频率采集数据，并记录列车速度采集时刻对应的全球定位系统（GPS, Global Positioning System）坐标。结合列车运行速度与波磨波长数据，可计算各轨道曲线段的波磨频率。将平均波磨频率保存，用于与机车牵引轮对的固有频率开展相关性分析。针对D39200型机车轮对开展实验模态分析（Experimental Modal Analysis），以获取其点频响函数（Frequency Response Functions, FRF）。获取该轮对的共振模态后发现，108Hz处的基频共振模态与各轨道曲线段的波磨频率具有更高的相关性。借助Google Earth Pro软件分析所得GPS坐标，可查看各轨道曲线段的地形与坡度。导出的黑匣子数据还记录了数据采集时段列车处于牵引还是制动状态，结合该信息与Google Earth Pro获取的轨道坡度，可判定列车运行方向。以机车编号命名的Excel电子表格存储了十进制格式的GPS数据，而CSV格式的文件则存储了转换为度分秒格式的GPS数据。构建有限元模型（Finite Element Model），以验证牵引轮对的共振模态，并探究轮对在振动激励下车轮与轴的振型。本研究所用D39200型轮对的轴与车轮工程图纸已随附。针对钢轨开展模态分析，以获取两轨枕间跨中位置的振动相位。分别采集了FY型、PY型混凝土轨枕以及钢枕配套钢轨的振动相位数据。该项实验旨在探究不同轨枕类型下车轮与钢轨的振动相位相关性。另有两个命名为"Rail on steel sleeper vs PY or FY type concrete sleeper"的Excel电子表格，其中同时存储了车轮振动相位的采集数据。