## 1 Introduction  
With the benefits associated with enhancing safety and reducing maintenance costs, structural health monitoring (SHM) has become an increasingly important topic, especially in the aerospace industry. Unlike conventional nondestructive testing techniques, structural health monitoring refers to the process of continuously monitoring the current state of a structure and measuring damage-sensitive data from the sensors that are typically permanently installed on the structure. Nowadays, many researchers are dedicated to piezoelectric transducer (PZT)-based SHM methods [1; 2; 3; 4; 5; 6] because of their performance in damage diagnosis and their stability against noise from the environment. The PZT-based SHM methods can be divided into two categories: the passive method, where sensors are designed to collect data only, and the active method, where the PZT sensors generate vibration or emit stress waves [7]. One of the typical active SHM methods is based on guided waves (GW). These are specific types of elastic waves that are generated and measured by PZTs. This method has been widely used for damage detection in metallic and composite structures because GW can travel a relatively long distance and are sensitive to damage [8; 9; 10; 11]. However, components of these kinds of systems consist of a waveformgenerator, power amplifier, charge amplifiers, data acquisition-boards, and computer systems, which make their application to online applications difficult. Another active sensing technique is based on electromechanical impedance (EMI) [2; 8], which can be applied on a composite material [12]. The theoretical model for the EMI method was first established by [PERSON] et al. [13]. In this model, the electrical impedance, which is the inverse of the electrical admittance, of a PZT sensor is shown to be coupled with the mechanical impedance of the host structure. Thus, the measured impedance from PZT can represent the severity of damage in the host structure. However, there are some practical issues related to the application such as debonding issues, temperature effects, and so on [14]. Usually, equipment employed for measuring electric impedance includes an inductance-capacitance-resistance (LCR) meter or impedance analyzer [15]. This hardware, including Agilent 4194A and Wayne Kerr 6500B [16], and so on, is often employed in experiments. Researches using this hardware tend to focus on some practical issues and theoretical problems and pursue a high level of precision; thus, reducing energy consumption and weight of hardware is not considered in these studies. Moreover, some of SHM systems utilizing EMI methods require a set of PZTs to form a sensor network, and this causes the hardware system to become heavy and complex. Therefore, it is necessary to design a lightweight and low-power consumption hardware system for real applications. One way to shrink the size of the hardware system is to employ a chip named AD5933. The AD5933 impedance converter is a high-precision impedance converter system with an on-board frequency generator, a 12-bit 1 MSPS, ADC, and an on-board digital signal processing (DSP) engine processing a discrete Fourier transform (DFT) with a weight of less than 5 g. Nowadays, it is employed by many researchers for designing low-cost, on-board, and wireless SHM systems [4]. The next generation of EMI-based system is supposed to be an onboard and sensor system comprising a mini impedance measuring chip such as AD5933 [15]. Conversely, impact detection, which also requires several sensors to form a sensor network, is a typical passive SHM method. Impact detection is usually divided into two missions: impact source location detection and impact energy level detection, and this information can help to conduct maintenance and repair work. Time-of-arrival based on PZT sensor arrays is a common method used for source location [17], whereas wavelet transform can be used to improve the signal-to-noise ratio [18].