## 1 Introduction  
With economic development around the world, the numbers of transformers are increasing as well. At the same time, the noise generated by the transformer has a great impact on residential areas, business centers, factories, subway stations, airports, schools, hospitals and other places. As the urban population and electricity consumption increases, distribution transformers are getting closer and closer to residential areas, and a large number of them even have to be set up in buildings or basements in order to save space. The main source of the transformer's body noise is from the core and winding vibration [1; 2; 3; 4; 5; 6]. The total vibration level on the transformer could be adequately described by the first few harmonics of 100 Hz [7]. Whereas the airborne sound output of transformers is not tremendously high, the vibration and subsequent structure-borne noise can be extreme. The reflection of solid-borne sound in walls and floors of buildings increases the energy density greatly [8]. For the most part, the transmission loss of the concrete floors is more than sufficient in attenuating airborne sound but structure-borne sound can be carried throughout the floors below for large distances from the transformer location [8], and then through beams, bricks, and walls to the rooms, thus resulting in more and more complaints from residents. The structure-borne sound and airborne sound transmission paths are shown in Figure 1. In view of this problem, it is difficult to adopt traditional sound insulation, muffler or sound control measures to achieve the desired results. Building engineers and consultants address airborne noise problems more effectively and confidently than structure-borne noise problems [9]. In order to predict and measure the structure-borne sound in buildings, a series of methods and techniques have been established. Statistical energy analysis (SEA) is a technique ideally suited for the study of sound and vibration transmission through complex structures [10]. [PERSON] and [PERSON] et al. [11; 12] examined the structural coupling and used SEA models to learn the vibration and sound propagating paths. However, statistical energy analysis is unreliable at low frequencies due to the statistical uncertainties that occur when there are few resonant modes in each of the elements or subsystems [10]. Finite element models do not suffer from these limitations at low frequencies and can be used to model such systems \"exactly\". [PERSON] and [PERSON] [10] used a finite element model to carry out \"numerical experiments\" to show the relationship between the properties of subsystems and the coupling between them. [PERSON] and [PERSON] [13] used the finite-difference time-domain method which is investigated as a new prediction method for architectural structure-borne sound. In addition, [PERSON] et al. [14] used techniques of Fourier transform and finite difference approximation to formulate vibration power flow model. [PERSON] [15] predicted the sound power radiated by a floating floor system using a model that used fluid-structure interaction and the Jinc function approach. [PERSON] and [PERSON] [16] analytically developed the three-dimensional Component Mode Synthesis method and used it on studying sound transmission between coupled volumes. [PERSON] et al. [17] developed an impedance model to study ground-borne vibrations caused by passing traffic in the test building. [PERSON] et al. [18] developed a method for characterizing building-mounted wind turbines (BMWTs) as sources of structure-borne sound and derived a methodology for prediction of structure-borne sound and vibration inside attached dwellings. Although there has been a development of methods of prediction and measurement of structure-borne sound, there still remains a shortfall in methods of predicting noise from vibrating machines in contact with building elements, which transmit vibrations and radiate sound [3], especially the specific study on the distribution transformer's vibration and noise in the building.