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Professional Motorsport Data Analysis: Frequency & Logging Rates

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Frequency & Logging Rates

03.47

00:00 - As much as it might occasionally be useful, it's simply not practical for our datalogging systems to be recording all measurements at an extremely high rate.
00:10 If we had infinite storage on the logger and huge processing power on both the logger and the computer we're doing the analysis on then this wouldn't be a problem but because that's not possible, we need to manage our frequency and logging rates.
00:25 We spent some time learning the basics of logging rates and how they should be applied in our data analysis fundamentals course.
00:32 But put simply, this is the rate at which we record the measurements of each channel or how often we record the sample.
00:40 This is typically expressed in hertz which is the number of samples recorded per second.
00:45 So 1 Hz is 1 recording per second and 10 Hz is 10 recordings per second.
00:51 The logging frequency is typically different for each channel and we'll be taking a closer look at why that is soon.
00:58 But for this reason, we typically configure the logger to log each channel at the minimum or coarsest useful frequency.
01:06 This helps to keep the log files small and also puts less strain on the computer that you're using for your analysis.
01:13 If you start using many complex math functions as part of your analysis, this is going to become more important.
01:21 Some simple logging systems will have a constant logging rate for all channels.
01:25 Which will generally be quite a low frequency around the 10 to 20 Hz range.
01:29 This allows the manufacturer to produce a more affordable product by using simpler hardware and software and it also requires less configuration by the user.
01:39 For many of the channels like vehicle speed, throttle, brake and steering angle, a constant logging frequency of 20 Hz is perfectly sufficient for most situations.
01:50 If however we're logging something more sophisticated like damper position or load cells, this wouldn't be a suitable logging frequency when it comes to more advanced analysis like damping forces or frequency domain analysis.
02:04 Don't worry too much about the intricacies of these logging scenarios for now.
02:08 We'll be taking a closer look in an upcoming module.
02:11 If you'd like to have a look at some basic recommended logging rates for commonly used sensors, you'll find a useful guide you can download from the related resources section underneath this video.
02:22 Which, for clarity's sake, is the same guide provided in the fundamentals course.
02:27 Keep in mind that these rates are only a ballpark and it depends on your own situation and what you're interested in analysing as to whether these rates will be suitable but if you're not sure what to use to start with, these will get you going.
02:40 Let's look at an example of how sampling a basic signal at different frequencies affects what we see in the logged data.
02:48 The real signal is shown in black and the logged data in red.
02:53 You can see how at low logging frequencies, the logged data does not represent anything close to the real signal.
03:00 If we trusted this data, then we'd be thinking the behaviour was totally different from what's actually happening.
03:07 As we increase the logging frequency, the logged data approaches something closer to the real signal.
03:13 The features we're interested in capturing will determine how high the logging rate needs to be for each channel.
03:19 In the most basic sense, we need to think about things like how fast the signal is changing and what logging rate we need to capture those changes in a useful way.
03:28 If we were using the channel for some math like differentiation or frequency analysis, then we'd need to think about the logging rate required to make meaningful calculations.
03:39 And don't worry, we're going to be getting into the maths side of things later in the module.

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