When using a probe to measure soil moisture, it is affected by the soil environment, and the measurement error in saline alkali land is large. In order to minimize the occurrence of this error, digital filtering technology is added to the soil moisture measuring instrument to reduce the interference of environmental factors on the soil moisture measurement results. Commonly used digital filtering algorithms include finite amplitude filtering, median filtering, arithmetic mean filtering, weighted average filtering, sliding average filtering, low-pass filtering, and composite filtering. Among many methods, there is always one that is applied to soil moisture measurement:
1) The amplitude limiting filtering method compares the difference between adjacent sets of data with the maximum allowable error value to obtain the data. Mainly used for processing data with relatively slow changes.
2) The arithmetic mean filtering method, also known as the arithmetic mean filtering method, involves taking N consecutive samples for arithmetic averaging. It is suitable for filtering signals with random interference and is influenced by the data set.
3) The weighted average filtering method is cumbersome for comparison and conversion. It involves multiplying N sets of data by a weighting coefficient and then calculating the cumulative sum.
4) The sliding average filtering method only samples once, compares this value with past sampled values, and calculates the average value. When the sampling speed is slow, the real-time performance of the system can be improved.
5) Low pass filtering method, which represents the differential equation of a simulated low-pass filter using a difference equation, allows software algorithms to simulate the functionality of hardware filtering, and has a certain effect on those with slow changes.
6) Composite filtering method is a combination of two digital filters with different filtering functions to form a composite filter, which has a good buffering effect on both fast and slow signals.
By using the above method and comparing it multiple times with the results obtained from soil moisture temperature measuring instruments or soil moisture monitoring systems, it was found that using arithmetic mean filtering and sliding average filtering as the filtering algorithms for the measuring instruments can directly reduce the interference of various parameters in the environment, and the accuracy of the values measured by the soil moisture measuring instrument is good.