In order to improve the performance of the plasma-sprayed Ni60A/Ni-WC composite coatings on the surface of high AlZn sinking roller, the as-sprayed Ni60A/Ni-WC coatings were treated using laser remelting technology, and the influential effects of laser remelting on the microstructure and performance of the Ni60A/Ni-WC coating was studied. The surface morphologies, microstructure, and microhardness of the Ni60A/Ni-WC coatings were analyzed using scanning electron microscopy (SEM) and microhardness tester. The high-temperature friction and wear characteristics of the Ni60A/Ni-WC coatings were also investigated. The results show that laser remelting treatment eliminates the defects such as lamellar structure and pores of the as-sprayed Ni60A/Ni-WC coatings, and the coatings density is improved. In addition, under the action of the high energy density laser, WC particles partially melt and precipitate dendritic structures around WC particles. The microhardness of Ni60A/Ni-WC coatings after laser remelting treatment are significantly improved, and their wear resistance are also significantly higher than that of the as-sprayed coatings.
In order to improve the service life of high Al-Zn sinking rollers, four layer WC particles reinforced Ni-based alloy gradient coatings of Ni60A, Ni60A+10% Ni-WC, Ni60A+20% Ni-WC, Ni60A+30% Ni-WC were prepared on the surface of the sinking roller using coaxial powder feeding laser cladding technology. The microstructure and phase composition of the Ni60A/Ni-WC gradient coatings were studied using optical microscopy (OM), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The results show that the microstructure of each gradient layer is composed of γ-Ni dendrite, multicomponent eutectic structure and reinforced phase of dispersed distribution. The number of reinforced phases gradually increases and the number of dendrites gradually decreases in the gradient coating from bottom to top. The main generated phases in Ni60A/Ni-WC gradient coatings are γ-Ni dendrite; eutectic composition of γ-Ni with Ni3B, Ni3Si, etc; reinforced phases of M6C, M7C3, M23C6, CrB, etc. Due to the gradient distribution of the original WC content and the dissolution of WC particles, the types of reinforced phases in the gradient coating also show a hierarchical distribution.
This study optimized laser cladding process parameters by combining BP neural network (BPNN) and genetic algorithm (GA) based on the multi-layer cladding nano Al2O3-13 wt.%TiO2 coating. The model structure was trained according to the orthogonal test results. The BPNN model of closed loop control temperature of the molten pool, ultrasonic vibration frequency and preheating temperature of the incubator with bonding strength and microhardness of the coating was constructed. Moreover, single-objective and multi-objective parameter optimizations were carried out to bonding strength and microhardness of the coating based on GA. Results demonstrated that the predicted values of models are very close to test values, indicating that the constructed model was accurate and reliable. The maximum bonding strength and the maximum microhardness of the coating after GA optimization are 70.7 MPa and 2025.5 HV, respectively. When weights of bonding strength and microhardness of the coating are the same, the coating achieved the optimal comprehensive performances under the 2472.0 oC of closed-loop control temperature of the molten pool, 31.9 kHZ of ultrasonic vibration frequency and 400 oC of preheating temperature of incubator. The corresponding bonding strength and microhardness are 69.1 MPa and 1835.5 HV, respectively.
To get a deep understanding on the relationship between process parameters of multi-layer laser cladding and performances of the coating, a Al2O3-13 wt.%TiO2 nanostructured ceramic coating was prepared by quash presetting multi-layer laser cladding. Effects of three major parameters (closed loop control temperature of molten pool, ultrasonic vibration frequency and preheating temperature of incubator) on bonding strength of coating were analyzed in the laser cladding experiment through 3-factor and 3-level orthogonal experiments. Moreover, process parameters of laser cladding were optimized. Results demonstrated that closed loop control temperature of molten pool was the dominant influencing factor of bonding strength of coating, followed by preheating temperature of incubator and ultrasonic vibration frequency successively. The optimal process parameters for preparing the Al2O3-13 wt.%TiO2 nanostructured coating through multi-layer laser cladding include closed loop control temperature of molten pool=2500 oC, ultrasonic vibration frequency=50 kHZ and preheating temperature of incubator=400 oC. The bonding strength of coating after process parameters optimization reached 66.3 MPa.
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