## 2 Materials and Methods
### Improvement of SNR  
The flow object composition in the dredging pipe is complex, and due to interference from other electromagnetic components, many electromagnetic signals are carried in the measurement field, which leads to a large amount of high-frequency and low-frequency noise in the measurement circuit. Therefore, it is necessary to conduct spectral analysis in the measurement circuit to observe the frequency distribution of the noise and add corresponding filters to eliminate related noise. At the same time, selecting appropriate electrode materials and transmission signal lines can also reduce external interference to a certain extent. Our study will propose two methods to improve the SNR of EIT. (1) _Optimization of the measurement circuit_  
After the excitation signal is added to the sensor, the obtained current signal is transmitted to the FPGA for demodulation through the measurement circuit. The measurement signal carries relevant information about the field conductivity distribution. Due to the complexity of signals in the field of dredging pipes, measurement signals may carry various noise frequencies. Therefore, a series of signal processing circuits must be added to the measurement circuit to obtain high-precision measurement signals. AD8129 is selected as the cross-resistance amplifier. The signal amplified by AD8129 in the measurement circuit can be observed through an oscilloscope. It is seen that this signal contains higher-order harmonics much higher than 80 kHz. After discrete Fourier transform (DFT) verification, it was observed that this higher-order harmonic signal is approximately in the frequency band of 4 MHz. The structure of the measurement circuit and the DFT results are shown in Figure 2. Where \(I_{X}\) is the current to be measured, \(R_{O}\) is the resistance value of the sensing resistor, and \(U_{O}\) is the partial voltage of the sensing resistor. Therefore, we chose a second-order Salley-Kelly low-pass filter and set its cutoff frequency to 3 MHz. The structure and filtering effect are shown in Figure 3, and it can be seen that most of the noise signals in the measurement signal have been filtered out at this time. \begin{table}
\begin{tabular}{l} \hline Step 1: Generate a digital sine wave from FPGA. \\ Step 2: Drive an external DA conversion chip to generate an AC signal. \\ Step 3: Load filtered smooth signal to the sensor electrode. \\ Step 4: Measure the current signal and convert it into a digital signal through an AD conversion chip. \\ Step 5: Transfer the digital signal to FPGA for demodulation to obtain its amplitude. \\ Step 6: Process the data collected by the EIT system through the upper computer. \\ \hline \end{tabular}
\end{table} 
Table 1: Workflow of the EIT acquisition process. _Electrode and transmission line_  
The sensor electrodes are composed of metal materials arranged at equal intervals inside the pipe or container. They are used to release and obtain electrical signals and are key media for establishing sensitive fields in the measured field domain. These electrode arrays directly affect the potential and equipotential lines of the detection field and have a significant impact on the reconstruction of the conductivity distribution in the measured field [15]. Therefore, sensors used in dredging engineering have high requirements for the materials and manufacturing processes of electrodes and pipes. The internal schematic diagram is shown in Figure 4.  
Figure 4: EIT sensor structure. Figure 3: Filter structure and filtering effect. (**a**) Filter structure; (**b**) Filtering effect. Figure 2: Measurement circuit and DFT result. (**a**) Measurement circuit; (**b**) DFT result. The electrode material must have good conductivity and stable chemical properties. Under the excitation of sinusoidal electrical signals, if the excitation frequency is too low, the polarization reaction on the electrode surface is severe; if the excitation frequency is too high, electromagnetic induction and \"connection impedance\" will create strong noise [16; 17; 18; 19].