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简体中文Digital filtering technology for hydraulic position sensors
For digital filtering technology for hydraulic position sensors, commonly used filter types include finite impulse response filters and infinite impulse response filters.
FIR filter: FIR filter has linear phase characteristics, that is, the phase delay of all frequency components is the same, which helps to maintain the waveform characteristics of the signal. FIR filter is simple in design, stable and easy to implement, so it is widely used in many applications. For hydraulic position sensors, FIR filters can effectively filter out high-frequency noise while keeping the phase information of the signal unchanged.
IIR filter: IIR filter has higher design freedom than FIR filter, which can achieve steeper transition band and lower passband ripple. The phase characteristics of IIR filter are usually nonlinear, which may cause distortion of signal waveform. When selecting IIR filter, it is necessary to weigh the relationship between its filtering effect and phase distortion. For some applications with low phase requirements, IIR filter may be a better choice.
Design principles of digital filter
When designing digital filters for hydraulic position sensors, the following principles need to be followed:
Clear filtering target: It is necessary to clarify the filtering target, that is, which frequency noise and interference need to be filtered out. This usually needs to be determined based on the characteristics of the hydraulic system and the performance indicators of the sensor.
Select the appropriate filter type: Select the appropriate filter type based on the filtering target and system requirements. For applications that need to maintain the phase characteristics of the signal, FIR filters should be given priority; for applications that do not require high phase, IIR filters can be selected to obtain better filtering effects.
Optimize filter parameters: After determining the filter type, it is necessary to further optimize the filter parameters, such as filter order, cutoff frequency, etc. The optimization of these parameters can be completed through simulation experiments and actual application tests.
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