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【電子工作基礎編】ノイズを除去する4つのフィルタ｜LTspiceで始める実用電子回路入門
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In this lesson, we can learn about 4 filters that remove noises by using LTspice. • -Table of Contents • 0:00 Opening • 0:18 Demonstration • 0:38 Question • 1:10 What's bio-sensor • 2:25 4 filters • 3:54 Notch filter that is used for removing specific frequency • 4:59 How to confirm filter characteristic by AC analysis • 5:50 Conclusion • -Introduction • Hardware engineer • 9 years experience as a Maker • -SNS • Web : https://start-electronics.com/ • Twitter : / buonoatsushi • #Electronics • -Content • This is a servo motor that uses a myoelectric sensor, one of the biometric sensors, to move in accordance with the force applied to the hand. The sensor is called MyoWARE, which was purchased from Switch Science. It can change its angle depending on how much force is applied, and can also be applied to remote-control gadgets by sending signals via the Internet. • Suddenly, here is a problem. • This circuit is commonly used in such biometric sensors. Think about it for 10 seconds. The clue is that the voltage level of the biometric signal is so weak that it is subject to various noises. One of them is electromagnetic noise due to commercial frequencies such as 50 Hz and 60 Hz. Which frequency response should be used to eliminate this noise? • Then the correct answer is (d). The correct answer is the frequency response (d). I will explain in a few steps. • First of all, let's talk about what a biometric sensor is. • When we want to know the internal state of our body, we cannot directly implant a sensor in the body, so we need to infer the internal state using information accessible from the outside of the body. • Biometric sensors are used for this purpose, and common examples include thermometers and blood pressure monitors. While these sensors are relatively easy to acquire information from, for example, muscle potentials, the electrical signals generated when muscles contract, are difficult to detect because the signals are weak. • Here is a measurement of an arm muscle using MyoWare's myopotential sensor. As you can see, the voltage increases as the force is applied. By reading this voltage value and operating according to the value, we can create a kind of remote control gadget. • However, although muscle information seems to be easily obtained, in fact, the voltage level originally generated is only a few 100uV to a few mV, and such a sensor module has a built-in circuit that amplifies it by about 1000 times using an operational amplifier. • At this time, since the original voltage level is low, various noises come on board, as shown here, which is a major problem when dealing with biometric sensors. If these are not removed first, the noise will be amplified together. This is where noise filters come in. • Here we introduce four types of noise filters. • There are four main types of noise filters, as shown here, and they are used according to the frequency you want to remove. • When the input is Vin and the output is Vout, the frequency response of the Vout/Vin relationship plotted by frequency is as shown in the figure here, which was explained in the previous problem. What the frequency response means is that frequency components with smaller values on the vertical axis become smaller, while frequency components with larger values pass through as they are. • For example, a low-pass filter passes only low frequencies and cuts off high frequencies. In fact, if you take a pulse waveform as input and look at the output side, you will see a waveform with a slow rise, as shown here. This is because the rising edge changes quickly in time, i.e., it has a high frequency component, and that part of the component is cut off. • On the other hand, a high-pass filter has the exact opposite characteristics of a low-pass filter: the rising part of the pulse is followed as it is, and the voltage drops when the pulse becomes stable. • In addition, since the bandpass filter is a circuit that is a cross between a low-pass filter and a high-pass filter, the output characteristic is a waveform that is between the low-pass and high-pass filters. • The frequency at which the frequency characteristic drops by 3 dB is called the cutoff frequency. This frequency can be calculated using the following formula, where R is the resistance value and C is the capacitance of the capacitor. If the frequency to be cut has been determined, design the circuit by determining each constant with reference to this formula. • And finally, I will introduce a slightly special notch filter. • Among band-elimination filters, a filter with a particularly narrow frequency to be removed is called a notch filter. One type of noise that rides on biological sensors is the 50Hz or 60Hz commercial frequency noise called hum noise. This is the kind of noise that our body itself becomes an antenna and gets mixed in with the biometric sensor. Notch filters are used when we want to remove only specific frequencies like this.
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