The acoustic emission (AE) signal collected by a sensor in the welding process has an overlapping frequency band and weak characteristics under a complex noise background. It is difficult for the wavelet noise reduction method, with single basis function, to effectively match the different characteristic information of the welding crack AE signal. Taking into account the adaptive decomposition characteristics of Empirical Mode Decomposition (EMD), a novel wavelet packet noise reduction method for welding AE signal was proposed. The welding AE signal was adaptively decomposed into several Intrinsic Mode Functions (IMFs) by the EMD. The effective IMFs were selected by the frequency distribution characteristics of the welding crack AE signal. A wavelet packet, with a specific basis function, was subsequently performed on the effective IMFs, which were reconstructed to be the welding crack AE signal. The simulated and experimental results indicated that the proposed method can effectively achieve noise reduction of the welding crack AE signal, which provided a mean for structure crack detection in the welding process.

The effect of 60Si2Mn substrate preheating on the forming quality and mechanical properties of cobalt-based tungsten carbide composite coating was investigated. Substrate preheating was divided into four classes (room temperature, 150 °C, 250 °C, and 350 °C). The morphology, microstructure, and distribution of elements of the coating were analyzed using a two-color laser handheld 3D scanner, a scanning electron microscope (SEM), and an energy dispersive X-ray spectrometer (EDX), respectively. The hardness and wear properties of the cladding layer were characterized through a microhardness tester and a friction wear experiment. The research results show that the substrate preheating temperature is directly proportional to the height of the composite coating. The solidification characteristics of the Stellite 6/WC cladding layer structure are not obviously changed at substrate preheating temperatures of room temperature, 150 °C, and 250 °C. The solidified structure is even more complex at a substrate preheating temperature of 350 °C. At this moment, the microstructure of the cladding layer is mainly various blocky, petaloid, and flower-like precipitates. The hardness and wear properties of the cladding layer are optimal at a substrate preheating temperature of 350 °C in terms of mechanical properties.

The dynamic response of the vibrating screen has a great impact on the screening efficiency and fatigue life of the structures. For the conventional dynamic design, the consideration of the influence of load weight on dynamic response is lacking. So, in this paper, taking a very common vibrating screen used in tunnel construction as an example, the relationship between the screen dynamic response and the load weight is studied through numerical simulations. Firstly, to make sure the accuracy of simulation, the three‐dimensional finite element model of a vibration screen is strictly built to maximize consistency with the real screen, and then the simulated results are validated by experiments. Furthermore, the variation regularity of dynamic response with the load weight and excitation frequency is analyzed based on simulations. Results show the load weight has obvious influence on the modal shapes as well as the natural frequencies. There are three regions that will lead to the sudden increase of vibration acceleration: (1) the load weight variates within 0–50 kg and excitation frequency variates within 40–60 Hz; (2) the load weight variates within 10–100 kg and excitation frequency variates within 50–90 Hz; (3) the load weight variates within 80–200 kg and excitation frequency variates within 70–100 Hz. These results will provide new theoretical reference for the maintenance and further improvement in the dynamic design of the vibrating screen.

The acoustic emission (AE) signal is weak due to the coupling and intersecting coexistence of other disturbance components in aluminum alloy metal inert-gas welding (MIG) process. It is necessary to analyze and process the AE signal for the accurate identification of the welding state. A time frequency feature extraction method based on synchronous compression wavelet (SST) and principal component analysis (PCA) is proposed in this paper. The SST transform is performed to the collected AE signal of the MIG welding process to obtain the time frequency distribution. The PCA is subsequently performed to the time frequency distribution of the AE signals to determine the principal components. The approximate entropies of the principal components are calculated to quantitatively express the state characteristics of the welding process. The proposed method is applied to the AE signal of the friction, arc shock and the crack in the aluminum alloy MIG welding process. The three kinds AE signals are identified by inputting the calculated approximate entropies into the support vector machine (SVM). The results indicate that the calculated approximate entropies highlight the characteristic ability of the different modal AE signals, which can be used for monitoring the aluminum alloy MIG welding process quantitatively.

In order to improve the wear resistance of 45 steel, in this study, WC/Ni60 composite coatings with different CeO₂ additions (0, 1, 2, and 3 wt%) were prepared on 45 steel by the laser cladding technique; the experimental analysis was carried out by means of scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), a Vickers hardness tester, and a friction and wear tester. The results show that CeO₂ had little effect on the phase composition of the coatings; however, with the increase in CeO₂ content, the CeO₂ played a key role in refining the grains of the coating, thus reducing the generation of cracks. In addition, CeO₂ could effectively strengthen the internal structure of the coating and improve its microhardness and wear resistance. Particularly noteworthy is the observed reduction in both the friction coefficient and mass loss of the coating when the CeO₂ addition reached 2%. This suggests an enhancement in the tribological performance of the coating at this concentration.