Jaw Functional Orthopedics and Cranoficial Growth
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Field evaluation of the geotechnical behavior of lime-ground cushions in the Republic of Tajikistan
No full textThe article presents the methodology for conducting field tests of lime-soil cushions to examine the technology of their construction, gain strength, their operation under rigid stamps, and the characteristics of stress-strain state development. The results of field studies showed that the lime-soil mixture can be used as a structural material in the preparation of bases on loess- loess soils in the conditions of the Republic of Tajikistan. Field tests showed that the lime-soil mixture achieved a dry density of 1.53-1.56 t/m3, while the deformation modulus increased by 5-10 times compared to natural loess soils
Multi source heterogeneous data diagnosis method of rotating machinery based on parameter collaborative optimization of multi-scale convolutional autoencoder
No full textIn order to fully utilize the features of multi-source heterogeneous data and effectively improve the accuracy and efficiency of fault diagnosis of rotating machinery, a multi-source heterogeneous data diagnosis method based on parameter collaborative optimization multi-scale convolutional autoencoder (MSCAE) is proposed. Firstly, multi-scale information learning is integrated into the convolutional autoencoder (CAE) to consider the temporal and spatial feature information of the diagnostic object simultaneously. To improve the training and diagnostic efficiency of MSCAE, a quantum particle swarm optimization (QPSO) module is used to perform hyperparameter optimization on it using chaos initialization and dynamic weight strategy (DWS). Besides, the sparse attention mechanism is introduced into the MSCAE model to improve the recognition rate of key fault features hidden in the original heterogeneous signals. Finally, the confusion matrix and visualization techniques are used to achieve fault classification. The experimental results demonstrate that after 100 experiments, the proposed method has an average diagnostic accuracy of 98.5 % and strong robustness to noise, providing a new method for rotating machinery fault diagnosis based on multi-source heterogeneous data
Improving the quality of cast blanks by applying force to the solidifying metal
No full textIn the course of the research, the authors studied the formation of structures of cast blanks on various alloys, depending on the conditions of metal crystallization, including under the influence of vibration. An analysis of the structures of the control samples (blanks) confirmed that solidification under normal conditions occurs mainly according to the sequential crystallization scheme, as evidenced by the width of the structural zones in them. The external vibration effect on solidifying alloys leads to a significant change in the conditions of their crystallization, in particular, to a significant grinding of the macrostructure of the workpieces and a change in the size of the structural zones, which indicates a volume-sequential scheme of their crystallization. It is established that vibration increases the physico-mechanical properties of cast metal and significantly reduces their anisotropy over the section of the workpieces
Acoustic detection of fan blade faults based on dynamic Cauchy swarm algorithm to optimize support vector machine
Get PDFFan blades operate in outdoor environments, where the detection of sound signals is susceptible to interference from background noise such as random loads, wind speed, rainwater, and other ambient noise. Therefore, this article proposes an acoustic detection method for wind turbine blade faults based on a dynamic Cauchy bee colony algorithm-optimized support vector machine. First, the signal is preprocessed using a Butterworth bandpass filter, and the full frequency band is divided into sub-bands using the octave band feature extraction method. Based on frequency domain analysis, the natural frequency offset of the blade is determined. Next, the dynamic Cauchy bee colony algorithm is applied to optimize support vector machine parameters, while moving average and bandpass filtering are used to smooth the noise power curve and extract impeller speed information. The experimental results show that the proposed method converges in fitness value after 22 iterations, with a detection time of only 6.8 seconds and small fluctuations in impeller speed amplitude. In terms of classification performance, the accuracy of detecting normal samples is 0.95, the recall rate is 0.96, and the F1 score is 0.95. The method demonstrates high prediction accuracy and stability for various types of fault samples and can be reliably applied to the acoustic detection of wind turbine blade faults
Study on the compaction and dynamic properties of loess enhanced by waste tyre rubber particles
Get PDFThis study investigates the compaction and dynamic properties of rubber particle-loess from Inner Mongolia through laboratory tests, including compaction tests and dynamic triaxial tests. Four rubber particle sizes (10 mesh, 20 mesh, 40 mesh, and 100 mesh) and four contents (5 %, 10 %, 15 %, and 20 % by volume) were tested under varying conditions: confining pressures of 50 kPa, 100 kPa, and 200 kPa, and freeze-thaw cycles of 0, 1, 3, 6, and 9. The tests aimed to simulate environmental conditions relevant to infrastructure in Inner Mongolia's loess regions. Results revel that adding 5 % 40-mesh rubber particles maximized dynamic shear modulus, damping ratio, and compactness. The dynamic shear modulus exhibited strain-softening behavior, which decreased with increasing dynamic strain, rubber content, and freeze-thaw cycles, but increased with confining pressure. The damping ratio showed a non-linear relationship with moisture content, showing a minimum at optimum moisture and increasing with freeze-thaw cycles while decreasing with confining pressure. Notably, the damping ratio of rubber particle-loess consistently exceeded that of plain soil. These results highlight the potential of waste tire rubber particles as an eco-friendly material to enhance loess engineering properties, particularly in cold regions with significant freeze-thaw effects. The study provides a theoretical basis for improving loess stability and seismic performance in geotechnical applications
Research on fault diagnosis of rolling bearings based on multi-method fusion
No full textTo address the limitation that Variational Mode Decomposition (VMD) relies on empirical settings for the mode decomposition number K and penalty factor α, this paper proposed the RIME-VMD-KNN method for bearing fault diagnosis. Specifically, the RIME algorithm was used to intelligently optimize K and α of VMD, breaking the reliance on experience; Pearson Correlation Coefficient (PCC) was adopted to screen Intrinsic Mode Functions (IMFs) with high fault correlation for signal reconstruction, preserving key features; and the sample entropy of the reconstructed signal was input into KNN for fault identification. Experiments show that the optimization performance of RIME is superior to that of GA, GWO and AOA; the generalization ability is verified by supplementary tests on the XJTU-SY dataset; KNN is simpler and more efficient than SVM, proving the rationality of its selection; the confusion matrix and multiple random cross-validation confirm stability; and computing time and resource data are provided to verify the feasibility of embedded deployment. This method improves the reliability and real-time performance of diagnosis and has engineering value
Analysis of dynamic response characteristics of vehicle-mounted tank based on the finite element method
No full textThe vehicle-mounted tanks face prominent challenges in balancing dynamic safety, including vibration resistance and fatigue durability under complex transportation conditions. A rigid-flexible coupled finite element model, consisting of the base, tank body, and frame, was established. Vibration response analysis was conducted in accordance with ride comfort standards and road excitation requirements. Rigid-flexible coupled simulations were implemented with consideration of vertical acceleration inputs and road unevenness. For random vibration, power spectral density analysis demonstrated that the tank structure was prone to resonance in specific frequency bands. For structural optimization, key dimensions were selected as design variables, including vertical thickness, longitudinal thickness, middle width, and lateral width. An optimization mathematical model was established, and the Sequential Quadratic Programming (SQP) algorithm was adopted to solve the constrained nonlinear multi-objective optimization model. Through optimization calculations, the structure achieved 4.93 % reduction in mass, 37.3 % decrease in stress, and 37.1 % increase in the first-order natural frequency, thereby effectively balancing the requirements of lightweight design, structural strength safety, and anti-resonance performance. This study provided a comprehensive methodology for the dynamic analysis and optimization of vehicle-mounted tank containers, offered key technical support for advancing innovative studies in transportation and vibration engineering
Lightweight design of double-head machine tool beam based on the adaptive multi-objective method
No full textDouble-head machine tool has the advantages of high efficiency and high degree of automation. In order to reduce the weight of double-head machine tool and improve the stiffness of the entire machine. An optimization design method combining topology optimization, sensitivity analysis and adaptive multi-objective method is used. Firstly, simplify the model in SolidWorks and import it into ANSYS Workbench software to carry out finite element analysis on the entire double-head machine tool to find out the weak component as the beam. Afterwards, carry out topological optimization on the beam and redesign the beam structure, and complete the first optimization. Then, through sensitivity analysis of the input parameters, key parameters that significantly impact the objective function are identified. Subsequently, a multi-objective optimization function is constructed for these key parameters and the objective function. Finally, an adaptive multi-objective method is used to solve the problem and obtain a Pareto optimal solution set, completing the second optimization. The results show that the weight of the beam is reduced by 8.88 %, the deformation of the beam is reduced by 11.29 %, and the equivalent stress of the entire machine is reduced by 28.33 %. This design not only yields significant economic benefits but also serves as a valuable reference for the lightweight design of large machine tool crossbeams
Energy analysis of living stumps slope based on Hilbert-Huang Transform and marginal spectrum
Get PDFA large-scale shaking table model test on a slope with living stumps was designed and conducted. Under various types of seismic waves and excitation intensities, acceleration data from monitoring points on both sides of the living stumps were collected. Hilbert-Huang Transform (HHT) was innovatively applied to study the dynamic response of slopes with living stumps under seismic loading, overcoming the limitations of traditional Fourier Transform and Wavelet Transform. The variation patterns of Hilbert energy and marginal spectral characteristics under different seismic excitations were analyzed, providing new insights from both time-frequency domain and energy perspectives. The research conclusion showed that: (1) Under different seismic waves, the horizontal peak acceleration inside the living stumps slope shows the elevation amplification effect, and increases with the intensity of excitation. Additionally, the existence of living stumps causes a difference in horizontal acceleration on both sides, and the absolute value of the difference is positively correlated with elevation and excitation intensity. (2) Under different seismic waves, Peak of Hilbert energy spectrum (PSHEA) is positively correlated with excitation intensity and elevation. With the increase of elevation, the increase of PSHEA increases gradually when the excitation intensity increases. PMSA is positively correlated with excitation intensity, but at low frequencies (1-3 Hz), Peak of marginal spectrum (PMSA) is negatively correlated with elevation; while at high frequencies (7-11 Hz), PMSA is positively correlated with elevation. (3) With increasing elevation and excitation intensity, the total seismic Hilbert energy continues to accumulate and reaches the maximum at the top of the slope. During the propagation of seismic waves, the living stumps and the rock-soil composite play the characteristics of filtering the low-frequency components and amplifying the high-frequency components, causing the total seismic Hilbert energy in the low-frequency (1-3 Hz) component to gradually decrease and transfer to the high-frequency (7-11 Hz) component, resulting in a significant increase in seismic Hilbert energy in the high-frequency component. (4) The superposition of incident wave and reflected wave near the living stumps, and the absorption of seismic Hilbert energy by the living stumps make the PSHEA, PMSA, and total seismic Hilbert energy on the outside of the living stumps always smaller than the inside, resulting in different dynamic responses on either side of the living stumps. The living stumps show attenuation effect on seismic Hilbert energy, and the attenuation degree increases with the increase of excitation intensity and elevation. The study provides a theoretical basis for the seismic design of living stumps slopes
Effect of Si addition on phase structure and wear resistance of CoCrFeMoNi alloy coatings
Get PDFCoCrFeMoNi high entropy alloy coating was prepared on Q235 substrate by plasma cladding method. The phase structure, morphology characteristics, element distribution, microhardness, and wear resistance for this alloy without and with Si doping were investigated by XRD, OM, SEM, EDS, microhardness tester, and friction-wear tester, respectively. The results show that CoCrFeMoNi alloy is composed of a single FCC phase, while Si-containing alloy is composed of FCC main phase and HCP phase. Both alloys have a typical dendritic structure. There is a layer of isotropic fine-grained region near the fusion line, and a columnar crystal region away from the fusion line. After adding Si element, the enrichment of Mo element in the interdendrite region and Co element in the dendrite region significantly decreased, which is related to the Si-containing alloy can provide a liquid environment with longer duration, lower viscosity, and greater fluidity. The change of Cr element enrichment from interdendrite region to dendrite region is the result of comprehensive competition of mixing enthalpy, atomic radius difference, electronegativity, density, and melt flowability between alloying elements. The friction coefficients of the two alloys show a rapid increase first and then gradually stabilize with the increase of time. After adding Si element, the hardness and wear resistance of the alloy are greatly improved, which is mainly related to the increase of the lattice distortion of FCC phase, the formation of high-strength HCP phase and the reduction of internal defects