Guojin Chen

In this study, a small core diameter single mode fiber laser was applied to weld an 8 mm thick plate of 6061-T6 aluminum alloy. The microstructural evolution and mechanical properties of the laser welded aluminum alloy specimens were investigated in detail. The results indicated that fully penetrated welded specimens, free of welding defects like porosity, melt sagging, and hot cracking could be achieved by optimizing the processing parameters through response surface methodology. The upper part of the fusion zone consisted mainly of fine equiaxed dendrites, with secondary dendrite arm spacing (SDAS) of approximately 3–5 μm. While the lower region of the fusion zone exhibited pronounced microstructural coarsening, made up mostly of coarse columnar grains, along with some localized equiaxed grains, and an SDAS ranging from 8 to 12 μm. Both the fusion zone and heat affected zone (HAZ) were characterized by a “softened” hardness profile. The fusion zone featured a narrow region with the lowest microhardness across the welded joint with the microhardness value reducing to ~72% of the base metal (BM). Meanwhile, the microhardness of the HAZ was ~87.4% of the BM. The ultimate tensile strength of laser welded specimens was ~243.6 MPa, amounting to approximately 78.3% of the base metal. This study provides a fresh approach for welding medium-thick aluminum alloy plate using a high-quality laser beam, even at the kilowatt level with a fiber laser, and it shows a strong promise for applications in light-alloy manufacturing sectors such as automotive, rail transportation, aerospace, and beyond.

Capacitive equipment refers to its insulation design using the principle of capacitance of electrical equipment, mainly by a variety of different capacitive components in series. Most of the equipment in the substation is capacitive equipment. Once an insulation failure occurs, it will lead to extremely serious consequences. Monitoring grid overvoltage and insulation degradation of capacitive equipment is an effective means to ensure the stable operation of the power system. Therefore, in order to enhance the health management of capacitive equipment, including transformers, bushings, and current transformers, and to mitigate the risk of severe failures, it is imperative to conduct broad-spectrum frequency-domain online monitoring of overvoltages, dielectric losses, and partial discharge. However, the current monitoring work requires the utilization of multiple detection apparatuses. Aiming at the disadvantage that the existing inspection is not well integrated and requires a combination of multiple devices. This paper proposes a smart grid overvoltage identification system that utilizes partial discharge (PD) signals in correlation with dielectric loss detection. The system achieves synchronous detection of dielectric loss and high-frequency partial discharge by synchronously and in real-time acquiring four current signals from the power grid, enhancing the integration level of the hardware system.

In this work, we design a micro-vibration platform, which combined with the traditional metal-assisted chemical etching (MaCE) to etch silicon nanowires (SiNWs). The etching mechanism of SiNWs, including in the mass-transport (MT) and charge-transport (CT) processes, was explored through the characterization of SiNW’s length as a function of MaCE combined with micro-vibration conditions, such as vibration amplitude and frequency. The scanning electron microscope (SEM) experimental results indicated that the etching rate would be continuously improved with an increase in amplitude and reached its maximum at 4 μm. Further increasing amplitude reduced the etching rate and affected the morphology of the SiNWs. Adjusting the vibration frequency would result in a maximum etching rate at a frequency of 20 Hz, and increasing the frequency will not help to improve the etching effects.

The online detection of partial discharge (PD) in gas-insulated switchgear (GIS) is a crucial and powerful tool for maintaining their reliability. However, extracting weak discharge signals from strong disturbances is a significant challenge. The presence of noise can hamper the identification and localization of PD types, making the extraction of pure PD signals the focus of current research. This paper proposes a PRPD-based PD filtering algorithm that analyzes interference using the output information from PRPD and sets threshold parameters for noise reduction processing. This method is mainly used for secondary noise reduction at a later stage, without analyzing the noise source, to achieve effective signal acquisition while retaining the characteristics of the PD signals, thereby improving the system’s sensitivity and the signal’s purity.

In the fiberglass industry, Pt–Rh bushings made of platinum and rhodium have very good characteristics, such as high temperature resistance, corrosion resistance, oxidation resistance, and creep resistance. In this paper, a semi-infinite lath structure model is constructed, and the expression of the surface temperature distribution of a Pt–Rh alloy plate with a circular through hole is obtained based on the non-Fourier heat conduction equation, complex function method and conformal mapping method. At the same time, the influence of the position of the circular through hole in the Pt–Rh bushing and the parameters of the incident light source (Non-diffusion incident wave number and relative thermal diffusion length) on the surface temperature distribution of the Pt–Rh bushing is studied by using this formula. It is found that: 1. heat concentration and fracture are occur easily at the through hole; 2. when the through hole is in the asymmetric center, the greater the asymmetry, the smaller the maximum temperature amplitude; 3. when the buried depth of the through hole increases, the maximum temperature amplitude decreases; 4. when the incident wave number and the relative thermal diffusion length of the incident light source are larger, the maximum temperature amplitude is smaller. The numerical results are almost consistent with those of ANSYS thermal simulation. The expression of the surface temperature distribution of the semi-infinite lath structure proposed in this paper can effectively reduce the loss of precious metal materials and the time of thermal simulation in the experimental process, as well as provide important significance for structural design, quality inspection, process optimization, and service life improvement of Pt–Rh bushings.

Intelligent manufacturing has a strong role in promoting the transformation and upgrading of traditional industries such as the chair industry. This study aimed to accurately evaluate the production status and technical level of chair industry enterprises, and then better guide chair industry enterprises to gradually implement intelligent manufacturing. Based on the analytic network process (ANP), we propose four capability domains, nine capability sub-domains, and 21 evaluation elements, thereby constructing an evaluation model for the capability maturity of chair industry enterprises’ intelligent manufacturing. First, the weight relationship of each index of the model was determined by means of an expert questionnaire. Then, super decision software was used to complete the modeling of the evaluation index of the network analytic hierarchy process. Finally, the evaluation model of the intelligent manufacturing maturity of chair industry enterprises was applied to 50 chair industry enterprises for evaluation and verification, and the evaluation results of the model proposed in this paper were compared with the evaluation results of the intelligent manufacturing maturity model released by China’s national standards. The results show that the evaluation model constructed in this study can better reflect the development status and overall technical level of intelligent manufacturing in the chair industry. Furthermore, the evaluation results can provide decision-making suggestions for chair industry enterprises to identify important areas for improvement and implementation of intelligent manufacturing upgrade plans.

Piezoelectric positioning stage is the core component of precision positioning system and advanced instrument. Its hysteresis characteristics, especially rate-dependent characteristics, are the main factors affecting the positioning or control accuracy. The multi-slope Prandtl–Ishlinskii (MPI) based hysteresis modeling and compensation experiments of two-dimensional piezoelectric positioning stage are discussed. The impact of the driving voltage amplitude and frequency on the hysteresis characteristics of uniaxial piezoelectric actuator in the piezoelectric positioning stage are studied, especially the influence of variable-frequency voltages on the output displacement of a piezoelectric actuator. The MPI compensation control of two-dimensional piezoelectric positioning stage is carried out, and the fitting coefficient R² is proposed to evaluate the hysteresis compensation accuracy of MPI model. Under the full range driving voltage of 20~120 V, the fitting coefficient reaches more than 99.6%. The experiments of feedforward compensation and feedback compensation are implemented. Having applied the composite triangular-wave signal, the average absolute displacement error of the piezoelectric actuator is 0.1192 μm, as well as the mean square error 0.2949 μm. It demonstrates that the MPI model is effective against hysteresis for two-dimensional piezoelectric positioning stage.

(1) Background: Personalized product customization is an important direction in the development of the chair industry. This paper studies an intelligent design method for the rapid realization of personalized office chair customization; (2) Methods: based on the case-based reasoning (CBR) method, the characteristic attributes of office chair patterns are analyzed, and an attribute model is established. According to office chair data and customer demand, an intelligent design model using multi-layer weighted k-nearest neighbor (K-NN) for chair patterns is developed using the entropy weight method and an analytic hierarchy process. In addition, an example is employed for verification of the K-NN and multi-layer weighted K-NN retrieval models; (3) Results: both models are able to effectively retrieve chair type cases that meet the target requirements from the office chair pattern base; the case matching similarity of the multi-layer weighted K-NN retrieval model was higher, with an average increase of about 3.9%, and the chair pattern case results obtained by setting different customer needs are different, indicating that the case can be selected according to different customer preferences, which is more conducive to personalized product customization design; (4) Conclusions: The multi-layer weighted K-NN model for intelligent chair pattern design proposed in this paper is more conducive to personalized product customization design.