## 1 Introduction  
Metallic materials are widely used in aerospace, transportation, construction, and other fields. However, the metal materials may generate defects due to fatigue loading. Studies have shown that the degradation of metal material performance has obvious stage characteristics [1; 2]. Due to cyclic loading, a large number of dislocation groups are generated inside the material, and the damage accumulates, which in turn causes the resident slip zone and microcracks to be generated. For well-designed engineering components, early damage to the materials accounts for the majority of their life, and the early performance degradation accounts for approximately 85% of the total fatigue life [3; 4; 5]. Eventually, the microcracks expand into macroracks until the material is completely destroyed. In practical engineering applications, due to the harsh working environment of the material, micro-cracks that are not discovered in time will greatly affect the overall response of the structure, making the material brittleness increase, and partial or global rebound is unstable. The probability of occurrence of the fracture accident increases, which may result in irretrievable loss [6]. In order to ensure the safety of engineering structures, microcrack detection technology has received more and more attention. Non-destructive testing (NDT) technology is widely used because it has a larger detection range, faster detection speed, and causes no damage to the structure. Destructive testing is only for manufacturing raw materials and is clearly inappropriate for structures that are being processed or in service. However, NDT can achieve full participation and, because there is no harm to the structure, a 100% full inspection can be achieved if necessary [7; 8; 9]. Among the NDT methods, the permeation detection (PT) cannot quantitatively evaluate defects, the radiographic testing (RT) is slow and harmful to the human body, and the magnetic particle testing (MT) cannot detect non-ferromagnetic material; in ultrasonic testing (UT), the traditional linear ultrasonic is severely attenuated at high frequencies, and the wavelength becomes longer at low frequencies. It is not suitable for detecting sheet materials and is not sensitive to small damage. Laser ultrasonic is a non-contact, high-precision, and non-invasive ultrasonic detection technology. However, due to its complicated operation, low convenience, and the immature detection technology of hard and brittle materials, its application is limited [10; 11]. The nonlinear ultrasonic testing technology is based on nonlinear characteristics such as harmonics and subharmonics for damage identification. It not only easily detects, but is also sensitive to early damage such as microcrack. Therefore, this paper uses nonlinear ultrasonic testing technology to detect microcracks in sheet materials. Since the higher harmonic signal is weaker and easily submerged in the noise, proper filtering means facilitates the signal analysis. Empirical mode decomposition (EMD) is an adaptive signal decomposition algorithm for nonlinear, non-stationary signals. By decomposing the signal into intrinsic mode functions (IMF) of different frequencies, it can screen out the obvious high-frequency noise and finally get a signal with a higher signal to noise ratio. Lamb wave is an elastic wave, and is attenuated less than the traditional longitudinal wave during propagation. Lamb waves can travel longer distances and are more efficient. Therefore they are suitable for large area inspection and have been proven to be suitable for the detection of plate-shaped or tubular structures [12; 13; 14; 15; 16]. In this paper, lamb wave is chosen as the fundamental wave for nonlinear ultrasonic testing to detect early damage in the sheet. It is affected by microcrack and other defects during the propagation process [17]. When a large value and high energy lamb wave reaches the crack, the elastic wave opens and closes the crack by stretching and compression.