The internal stress difference between soft-ductile aluminum alloy substrate and hard-brittle Ni–W alloy coating will cause stress concentration, thus leading to the problem of poor bonding force. Herein, this work prepared the Ni–W graded coating on aluminum alloy matrix by the pulse electrodeposition method in order to solve the mechanical mismatch problem between substrate and coatings. More importantly, a backward propagation (BP) neural network was applied to efficiently optimize the pulse electrodeposition process of Ni–W graded coating. The SEM, EDS, XRD, Vickers hardness tester and Weighing scales are used to analyze the micromorphology, chemical element, phase composition, and micro hardness as well as oxidation weight increase, respectively. The results show that the optimal process conditions with BP neural network are as follows: the bath temperature is 30 °C, current density is 15 mA/cm2 and duty cycle is 0.3. The predicted value of the model agrees well with the experimental value curve, the relative error is minor. The maximum error is less than 3%, and the correlation coefficient is 0.9996. The Ni–W graded coating prepared by BP neural network shows good bonding with the substrate which has flat and smooth interface. The thickness of the coating is about 136 μm, which slows down the oxidation of the substrate and plays an effective role in protecting the substrate.

Aluminum alloy has limited its application due to low hardness and poor wear resistance. Therefore, surface modification by electroplating is beneficial to improving hardness and wear resistance properties. Hence, Ni/W–ZrO2 coating was organized on aluminum alloy by electro-deposition method in this paper. The optimum organization parameters were obtained. The impact of different ZrO2 additions on the hardness and friction wear properties of Ni/W–ZrO2 coatings were further investigated. The SEM, Vickers examiner and wear examination are used to analyze the micromorphology, micro-hardness as well as friction and wear resistance properties, respectively. The results show that when the addition of ZrO2 was 40g/L in the deposition bath, the Ni/W–ZrO2 coating possesses the optimum micro-hardness of 384HV. This is mainly attribute to the dispersion-enhancing effect of ceramic particles. This work offers a new approach to surface strengthening technology for aluminum alloys.

The high cutting temperature and poor thermal diffusion efficiency of nickel-based alloys during deep hole machining have become technical challenges in the hole machining field. In this paper, a finite element simulation model of Inconel-718 BTA ordinary drilling and vibration drilling processes was established by using Deform-3D finite element simulation software. The variations in the temperatures of the tool teeth and the workpiece at different positions of the nickel-based alloy under ordinary drilling and vibration drilling were investigated. Additionally, the wear pattern of each tool tooth under the two drilling methods was further analyzed by building an experimental platform for workpiece temperature detection, which reveals the wear and cooling mechanism of nickel-based alloy BTA deep hole drilling. The results show that the average temperatures of the external, intermediate, and central teeth were reduced by 18.1%, 21.1%, and 17.8%, respectively, during vibration drilling. In addition, the workpiece hole wall and hole bottom temperatures were reduced by 5.7% and 4.6%, respectively. To conclude, the experimental tests were consistent with the simulated temperature trends. BTA vibration drilling optimizes the heat exchange conditions between the cutter teeth and the workpiece during the drilling of nickel-based alloys, which effectively reduces the cutting temperature and, thus, improves the wear resistance of the cutter teeth.

Aiming at the problems of the low detection accuracy and difficult identification of the early weak fault signals of rolling bearings, this paper proposes a method for detecting the early weak fault signals of rolling bearings based on a double-coupled Duffing system and VMD. The influence rule of system initial value on the response characteristics of a double-coupled Duffing system is studied, and the basis for its determination is given. The frequency of the built-in power of the system is normalized, and a variance evaluation standard for the output value of the double-coupled Duffing system for weak fault signals detection is established. In order to solve the interference problem of fault monitoring signals, VMD is proposed to pre-process the fault monitoring signals. The weak fault signal detection method proposed in this paper is tested and verified by simulation signals and rolling bearing fault signals. The results show that the method proposed in this paper can detect the weak fault signal with the lowest signal-to-noise ratio reduced by 2.96 dB compared with the traditional Duffing detection system, and it can accurately detect the early weak fault signal of rolling bearings.