Abstract
Spent fuel shearing machines in nuclear power plants are important equipment for the head end of spent fuel reprocessing in power reactors. Condition monitoring and fault diagnosis play ...important roles in ensuring the safe operation of spent fuel shearing machines, avoiding serious accidents, and reducing their maintenance time and cost. Existing research on fault diagnosis of spent fuel shearing machines has some shortcomings: (a) the current research on fault diagnosis of shearing machines is small and diagnostic accuracy is not high. The research methodology of shearing machines needs to be updated; (b) the high difficulty in obtaining fault data and the often limited and highly informative fault data for shearing machines lead to low diagnostic performance. To solve these problems, this study constructs a residual network (ResNet) model based on Bayesian optimization (BO) and convolutional block attention module (CBAM). First, dual-channel difference method is introduced into the preprocessing of noise signals, and two data enhancements were applied to the Mel spectrograms used as inputs to the model. Second, the attention mechanism CBAM is introduced to improve the ResNet to enhance the deep feature extraction ability of the network, and the BO algorithm is used to train the hyperparameters, such as the optimizer, and retrain the network model after obtaining the optimal hyperparameters. Finally, the feasibility and effectiveness of the proposed model are verified through experiments on the noise signals of spent fuel shearing machines. The experimental results show that the diagnostic accuracy of the constructed model is 93.67%, which is a significant improvement over the other methods.
It has been unclear how fiber coarseness affect formation and the utilization of furnish strength in the machine-made paper (strength efficiency). In this work, the effect of softwood kraft fiber ...coarseness on formation and strength efficiency in twin-wire roll forming was examined in a pilot machine investigation. A reduction in softwood kraft fiber coarseness from 0.21 to 0.17 mg/m, associated with a reduction in fiber grammage from 6.2 to 5.2 g/m
, was found to have no significant effect on formation at the point of minimum shear during dewatering. The insignificant effect of reduced coarseness can be interpreted as the net result of two effects, namely, an increase in the number of fiber layers at a given grammage (favorable) and an increase in the flocculation tendency (unfavorable). While the effect of coarseness was negligible at the point of minimum shear, coarser fibers enabled larger improvement in formation through the jet-to-wire speed difference. In correspondence to the insignificant effect on formation, fiber coarseness had a negligible effect on tensile strength efficiency and Z-strength at the point of minimum shear. The larger improvement in formation through the jet-to-wire speed difference for the coarser fibers was reflected in a favorable effect on Z-strength efficiency.
To obtain a high degree of flexibility and excellent surface finish in a manufacturing process, a lot of work is done on sheet metal by cutting it into a variety of shapes and sizes. The pneumatic ...Sheet Metal Clamping and Shearing Machine is one of the modern machines used to efficiently cut Sheet Metal to specification. This project on the Development of Sheet Metal Clamping and Shearing Machine discusses the maximum force that the cylinder actuator can exert on the workpiece, the shearing force required to cut sheet metals of 1.0mm, 1.2mm and 1.5mm for a length of 25mm. Also, a comparison of the time taken to cut sheet metals of 0.45mm, 0.6mm, and 0.8mm for a length of 50mm with a Manual Shearing Machine and Pneumatic Sheet Metal Clamping and Shearing Machine. The time by the Pneumatic Shearing Machine is less than that of the Manual Shearing Machine as shown in the presented table. Moreover, the cutting accuracy of the developed pneumatic Sheet Metal Clamping and Shearing Machine was compared with the Manual Metal Shearing Machine, and observations made, showed that the Pneumatic Clamping and Shearing Machine has greater accuracy than the Manual Shearing Machine as a result of the clamping device on the machine which gives it greater clamping rigidity on the workpiece for the cutting operation to be carried out. The project had been able to address the following: Production time reduction, increase in cutting accuracy, and elimination of manually applied effort.
In this study, a support vector regression (SVR) model is developed for reliability estimation. An imperialist competitive algorithm is applied for selecting the SVR parameters such as ∁,
. The ...proposed model is validated by applying it to a benchmark data set. Satisfactory performance of the proposed model with respect to the data set is demonstrated through a comparative study. A shearing machine operating at an electric tableau manufacturing company is considered a case study. A set of data representing the time-to-failure (TTF) of the shearing machine is used to calculate the cumulative TTF for reliability modelling. The experimental results indicate that the proposed model achieves high estimation accuracy.
In the modern industrial manufacturing field, PLC plays a very important role. In this paper, through analyzing the working process and control requirements of plate shearing machine and using PLC ...control technology, the automation design of the plate shearing machine control system is realized.
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