Transient Thermal Analysis Model of Damaged Bearing Considering Thermo-Solid Coupling Effect.

As one of the important parameters of bearing operation, temperature is a key metric to diagnose the state of service of a bearing. However, there are still some shortcomings in the study of the temperature variation law for damaged bearings. In this paper, according to the structural characteristics of bearings, the influence law of thermal-solid coupling effect on bearing structure is considered, and a novel transient temperature analysis model of damaged bearings is established. First, a quasi-static analysis of the bearing is performed to obtain the variation laws of the key parameters of the bearing under thermal expansion. Then, the load variation law of the bearing under the condition of damage is discussed, and the heat generation and heat transfer of the damaged bearing during operation are studied. Based on the thermal grid method, a transient temperature analysis model of the damaged bearing is developed. Finally, the model is tested experimentally and the influence of the rotate speed and load on the bearing temperature variation is analyzed. The results show that the established model can effectively predict the temperature variation and thermal equilibrium temperature of damaged bearings.

Thermal Error Prediction and Compensation of Digital Twin Laser Cutting Based on T-XGBoost.

Laser cutting belongs to non-contact processing, which is different from traditional turning and milling. In order to improve the machining accuracy of laser cutting, a thermal error prediction and dynamic compensation strategy for laser cutting is proposed. Based on the time-varying characteristics of the digital twin technology, a hybrid model combining the thermal elastic-plastic finite element (TEP-FEM) and T-XGBoost algorithms is established. The temperature field and thermal deformation under 12 common working conditions are simulated and analyzed with TEP-FEM. Real-time machining data obtained from TEP-FEM simulation is used in intelligent algorithms. Based on the XGBoost algorithm and the simulation data set as the training data set, a time-series-based segmentation algorithm (T-XGBoost) is proposed. This algorithm can reduce the maximum deformation at the slit by more than 45%. At the same time, by reducing the average volume strain under most working conditions, the lifting rate can reach 63% at the highest, and the machining result is obviously better than XGBoost. The strategy resolves the uncontrollable thermal deformation during cutting and provides theoretical solutions to the implementation of the intelligent operation strategies such as predictive machining and quality monitoring.

Design and Development of a Three-Component Force Sensor for Milling Process Monitoring.

A strain-type three-component table dynamometer is presented in this paper, which reduces output errors produced by cutting forces imposed on the different milling positions of a workpiece. A sensor structure with eight parallel elastic beams is proposed, and sensitive regions and Wheastone measuring circuits are also designed in consideration of eliminating the influences of the eccentric forces. To evaluate the sensor decoupling performance, both of the static calibration and dynamic milling test were implemented in different positions of the workpiece. Static experiment results indicate that the maximal deviation between the measured forces and the standard inputs is 4.58%. Milling tests demonstrate that with same machining parameters, the differences of the measured forces between different milling positions derived by the developed sensor are no larger than 6.29%. In addition, the natural frequencies of the dynamometer are kept higher than 2585.5 Hz. All the measuring results show that as a strain-type dynamometer, the developed force sensor has an improved eccentric decoupling accuracy with natural frequencies not much decreased, which owns application potential in milling process monitoring.

Development of a Tri-Axial Cutting Force Sensor for the Milling Process.

This paper presents a three-component fixed dynamometer based on a strain gauge, which reduces output errors produced by the cutting force imposed on different milling positions of the workpiece. A reformative structure of tri-layer cross beams is proposed, sensitive areas were selected, and corresponding measuring circuits were arranged to decrease the inaccuracy brought about by positional variation. To simulate the situation with a milling cutter moving on the workpiece and validate the function of reducing the output errors when the milling position changes, both static calibration and dynamic milling tests were implemented on different parts of the workpiece. Static experiment results indicate that with standard loads imposed, the maximal deviation between the measured forces and the standard inputs is 4.87%. The results of the dynamic milling test illustrate that with identical machining parameters, the differences in output variation between the developed sensor and standard dynamometer are no larger than 6.61%. Both static and dynamic experimental results demonstrate that the developed dynamometer is suitable for measuring milling force imposed on different positions of the workpiece, which shows potential applicability in machining a monitoring system.

Defect reconstruction from magnetic flux leakage measurements employing modified cuckoo search algorithm.

Accurate and efficient estimation for defect profile of magnetic flux leakage (MFL) signals is important for nondestructive evaluation in industry. To improve the accuracy of defect profile reconstruction, an improved reconstruction method based on modified cuckoo search (CS), called MCS, is proposed in this paper. Firstly, a novel single-dimension updating evolution strategy is proposed to avoid the interference between multiple dimensions, which can make full use of the appropriate nest position in the historical search. Secondly, an adaptive multi-strategy difference evolution is introduced into the evolution process to improve the diversity and efficiency of CS algorithm. The proportion factor of each strategy in multi-strategy difference evolution is adjusted dynamically according to the value of the objective fitness. Finally, various MFL signals are selected to verify the effectiveness of the proposed MCS algorithm. The experiment results illustrate that the proposed method has high performance on the quality of the solution and robustness for noise.