# Underwater Radiated Noise Prediction Method of Cabin Structures under Hybrid Excitation
## 3 Underwater Radiation Noise Prediction Method for Cabin Structures  
Acoustic/Vibration-Acoustic\" Transmission Network inside and outside the Cabin Structure Modeling Method Based on OTPA  
OTPA can obtain the \"acoustic/vibration-acoustic\" transmission network inside and outside the cabin through the working condition test, and based on this transmission network and its monitoring data, the near-field radiation noise of the conformal hologram surface outside the cabin can be calculated in real time. For the application scenario where the positions of the input point and the output point are determined, the OTPA method can set the intermediate node of the transmission path between the excitation source and the target point under the actual operating conditions, collect the information of the intermediate node and the target point, and use the transfer function between the intermediate node and the target point to characterize each transmission path. This method can calculate the response of the target output point quickly and accurately, making it very suitable for the application scenario of this paper. OTPA was originally an analysis method based on experimental testing. In recent years, with the development of computer technology, CAE-based OTPA numerical calculation methods have replaced real experimental testing in some application scenarios, reducing the test costs and the complexity of the test systems to a certain extent. The transfer network constructed in this paper can be tested by experimental or numerical calculation, and the two can also be combined. Since the structure of the simulation and test object is known and relatively simple, in order to facilitate the discussion of the problem, this paper adopts the CAE-based numerical method to model the \"sound/vibration-sound\" transmission network of the cabin structure. The input signal of the sound source excitation is as follows:  
\[p(\omega,t)=A_{p}*\exp(j\omega t+\varphi_{p}) \tag{8}\]  
Figure 6: Average error of the full frequency band of the information collected by each physical field under different numbers of monitoring points: (**a**) Inner surface mean square sound pressure. (**b**) Internal surface mean square velocity. (**c**) Outer surface mean square sound pressure. where \(A_{p}\) is the amplitude of the acoustic excitation signal and \(\phi_{p}\) is the phase of the acoustic excitation signal. The input signal of the force source excitation is as follows:  
\[v(\omega,t)=A_{v}*\exp(j\omega t+\varphi_{v}) \tag{9}\]  
where \(A_{v}\) is the amplitude of the force excitation signal and \(\phi_{v}\) is the phase of the force excitation signal. When the numerical working condition test is carried out, the working condition test model is established using the numerical calculation software COMSOL 6.0. Secondly, the excitation input amplitude \(A_{p}\) and phase \(\phi_{p}\) of the sound source and the excitation input amplitude \(A_{v}\) and phase \(\phi_{v}\) of the force source are calculated in the studied frequency band to obtain the acoustic monitoring data of the acoustic monitoring points inside the cabin, the vibration monitoring data of the vibration monitoring points, and the acoustic response data of the near-field radiation noise response points on the conformal holographic plane outside the cabin, which is a working condition test. Finally, multiple working condition tests are carried out by changing the relative size of \(A_{p}\) and \(A_{v}\) and the relative phase of \(\phi_{p}\) and \(\phi_{v}\). According to the conclusions in Section 2.1, in the vibration-acoustic synchronous monitoring information, the PSIR has a relatively high reliability and is more than 20 dB in most of the frequency bands. The vibration and acoustic information has a large energy difference, so the acoustic information can be approximated as independent excitation of the sound source, while the vibration information has strong coupling.