Contents

Force sensor is a kind of sensor that can convert mechanical quantities into electrical signals, which is widely used in industrial, medical, scientific research and other fields. According to the working principle, force sensors are mainly divided into resistive strain, capacitive, inductive and piezoelectric types. Among them, resistance strain sensors are widely used in engineering practice because of their high precision, good stability, wide linear range and other advantages.

The back-end signal processing of the load cell refers to the sensor output signal acquisition, amplification, filtering, conversion and other processing, in order to obtain accurate and reliable measurement results. The following will introduce the main methods of back-end signal processing.

1. Signal acquisition

Signal acquisition refers to the acquisition of the electrical signal output from the force transducer for subsequent processing. The acquired signals are generally analogue and need to be converted to digital using an analogue-to-digital converter (ADC) for computer processing. The acquired signal should retain as much of the original sensor information as possible to avoid noise and distortion.

2. Signal amplification

Since the electrical signals output from the force transducer are often weak, amplification is required to obtain better measurement accuracy. Amplifier is the key device in the signal amplification process, which needs to be selected and adjusted according to the output characteristics of the sensor and measurement requirements. Amplifier should have high precision, low noise, low distortion and other characteristics to ensure that the amplified signal can truly reflect the output of the sensor.

3. Signal filtering

Force transducer output signal often contains a variety of noise and interference, the need for filtering to reduce errors and improve stability. Filter is a key device in the signal filtering process, according to different sources of noise and interference, you can choose different filter types and parameters. Common filter types include low-pass filters, high-pass filters, band-pass filters and trap filters. The filter should have high selectivity, low distortion and low noise characteristics to ensure that the filtered signal can truly reflect the output of the sensor.

4. Signal conversion

Signal conversion refers to the acquisition, amplification and filtering of the signal is converted to digital signals that can be processed by the computer. Converter is a key device in the signal conversion process, according to different conversion needs, you can choose different types of converters and parameters. Common converter types include analogue-to-digital converter (ADC) and digital-to-analogue converter (DAC). The converter should have high resolution, high accuracy, low noise and low distortion to ensure that the converted signal can truly reflect the output of the sensor.

5. Data processing and compensation

Data processing and compensation refers to the converted digital signal for further processing and compensation to obtain more accurate and reliable measurement results. Data processing and compensation methods include digital filtering, nonlinear compensation, temperature compensation and so on. These methods should be selected and adjusted according to the specific measurement needs and sensor characteristics to ensure the accuracy and reliability of the measurement results.

The back-end signal processing methods of force transducers play a crucial role in obtaining accurate and reliable measurement results. Through the careful design and adjustment of the acquisition, amplification, filtering, conversion and data processing, the measurement accuracy and stability of the force sensor can be effectively improved to provide more reliable technical support for applications in related fields. With the continuous development of technology in the future, the back-end signal processing methods of force sensors will have richer and more diversified application prospects.