# Research on Leakage Location of Pipeline Based on Module Maximum Denoising
## 3 Results  
### Verification by Experiment  
The pipeline leakage experiment system as shown in Figure 2 is built. The leakage simulation system is shown in Figure 3, and the acquisition equipment is shown in Figure 4. The pipe is supplied by connection to an external water supply pipe. The pipe material is Q235B steel, the inner diameter is 80 mm, and the pipe wall thickness is 3 mm. To simulate a leak, the faucet can be opened quickly. The pressure signal is collected by a high-frequency dynamic pressure sensor with a range of 0-0.6 MPa. The battery is charged via a solar panel to power the sensor. The data acquisition card is used to collect the signal of the sensor and transmit it to the computer. The signal sampling frequency is 2 kHz, and the pressure in the pipeline fluctuates between 0.16\(\sim\)0.24 MPa. When the pipeline pressure drops by more than 0.1 MPa in a short time, a leak is considered to have occurred. The 3 valves used to simulate leakage in the pipeline are fully opened, half-opened, and then closed in turn, with signal data received from the two pressure sensors. Figure 2: Experimental system layout diagram. Considering the influence of the decomposition level on the algorithm, this paper first analyzes the influence of this key parameter on the signal-to-noise ratio, based on the experimental data, and the results are shown in Figure 5.  
From Figure 5, it can be seen that for the experimental system in this paper, the best denoising effect can be achieved when the number of the decomposition layer is 5. According to the pipeline parameters shown in Table 1, the negative pressure wave velocity is calibrated as 462.5 m/s. Figure 4: Laboratory acquisition equipment. Figure 5: Relationship between decomposition layer and SNR. Figure 3: Experimental equipment. \begin{table}
\begin{tabular}{l r} \hline \hline Pipe inner diameter (m) & 0.08 \\ \hline The density of water (kg/m\({}^{3}\)) & 998.203 \\ \hline Pipe wall thickness (m) & 0.003 \\ \hline The volumetric elastic modulus of water (Pa) & \(2.1\times 10^{8}\) \\ \hline The elastic modulus of the pipe (Pa) & \(2.1\times 10^{11}\) \\ \hline Sampling frequency (kHz) & 2 \\ \hline The pressure of the pipe (MPa) & 0.16\(-\)0.24 \\ \hline \end{tabular}
\end{table} 
Table 1: The pipeline parameters. Figure 6 shows the change of pressure signal when simulated leak point 2 is fully opened. As can be seen from Figure 6, the original signal contains a large amount of noise. In order to verify the effectiveness of the proposed method, we use wavelet denoising method, modular maximum method, VMD denoising method and the proposed method to denoise the signal respectively. The result is shown in Figure 7.  
Figure 7a shows wavelet denoising, Figure 7b shows module maximum denoising, Figure 7c shows VMD denoising, and Figure 7d shows improved module maximum denoising. It can be seen from the denoising results of each method in Figure 7 that the improved module maximum denoising proposed in this paper achieves the best denoising effect while preserving the original signal characteristics as much as possible. It causes a spike at the stop point of the signal due to local extreme points, because there is no subsequent signal for scale iteration, and scale preservation cannot be performed. According to the denoising effect shown in Figure 7, it can be seen that the improved module maximum denoising can best retain the original signal, suppress the noise signal. It can more truly reflect the detailed changes of the original signal, especially for the detection of pressure abrupt points caused by NPW. Our method can retain the characteristics of the peak signal at the inflection point in the one-dimensional sequence with almost a straight drop of press, which provides a basis for the accuracy of extracting the singularity (inflection point), by wavelet decomposition. The SNR of the four methods is as follows: VMD is 40.87, wavelet threshold is 43.90, module maximum is 44.01, and improved module maximum is 50.97.