To address the issue of not having enough labeled fault data for planetary gearboxes in actual production, this research develops a simulation data-driven deep transfer learning fault diagnosis method that applies fault diagnosis knowledge from a dynamic simulation model to an actual planetary gearbox. Massive amounts of different fault simulation data are collected by creating a dynamic simulation model of a planetary gearbox. A fresh deep transfer learning network model is built by fusing one-dimensional convolutional neural networks, attention mechanisms, and domain adaptation methods. The network model is used to learn domain invariant features from simulated data, thereby enabling fault diagnosis on real data. The fault diagnosis experiment is verified by using the Drivetrain Diagnostics Simulator test bench. The validity of the proposed means is evaluated by comparing the diagnostic accuracy of various means on various diagnostic tasks.
In order to study the mechanical response of cement concrete pavements under impact loading, four types of typical cement concrete pavement structures are investigated experimentally and numerically under an impact load. Full-scale three-dimensional pavement slots are tested under an impact load and are monitored for the mechanical characteristics including the deflection of the pavement surface layer, the strain distribution at the bottom of the slab, and the plastic damage and cracking under the dynamic impact load. Numerical analysis is performed by developing a three-dimensional finite element model and by utilizing a cement concrete damage model. The results show that the calculation results based on the cement concrete damage model are in reasonable agreement with the experimental results based on the three-dimensional test slot experiment. The peak values of stress and strain as monitored by the sensors are analyzed and compared with the numerical results, indicating that the errors of numerical results from the proposed model are mostly within 10%. The rationality of the finite element model is verified, and the model is expected to be a suitable reference for the analysis and design of cement concrete pavements.
The Full-Scale Loading Slot Experiment2.1. Impact Load Characteristics. In order to explore the dynamic response law of the concrete pavement structure under an impact load and over load, an impact load was designed as shown in Figure 1 and the load was applied to the pavement structure by a dynamic loading device. The acting Hindawi
An electrical capacitance tomography (ECT) sensor is an array capacitive sensor that is sensitive to the medium of the measured object and can be widely used in oil, natural gas, machinery and other industrial fields to solve the problem of multiphase fluid object parameter detection in industrial processes. However, ECT sensor uniformity defects need to be addressed. Aiming at the problem that the non-uniform electrode spacing angle affects the characteristics of the measured value of the actual ECT sensor, a method for compensating the measured value of the ECT sensor based on the assumption that the geometric factor is invariant is proposed. The simulated measurement value in the case of the tube and the measurement value of the actual sensor in the case of an empty tube and a full tube are to compensate the measurement value of the actual ECT. Experiments show that, without compensation, non-ideal sensor monitoring has large error, and, after compensation, it has a good effect and can be expected to perform satisfactorily in practical use.
In order to improve the information and product originality level of intelligent manufacturing industry based on sensor technology, this paper summarizes the current situation of CAx integration based on sensor technology and its design application and analyzes the shortcomings of existing CAx integration, aiming at accurate, complete, timely, and barrier-free transfer of sensor product data and information between CAx system and MRPII/ERP management information system. The concept and information model of feature extension of sensor components oriented to the whole process of sensor intelligent manufacturing is presented. Taking feature extension of sensor components as the integration link, CAx integration framework structure and its design application mode based on feature extension are established, while key technologies and implementation ideas to realize the integration and the design application are put forward, which provides an effective path to realize the sensor integration of CAx and management information systems such as MRPII/ERP.
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