Cong Ding

The purpose of this paper is to investigate the relationship between surface morphology and friction coefficient during the wear process. Different wear stage tests of AISI 52100 ring sliding against AISI 5120 disc were designed and performed. The fractal and chaos theories were employed to study the spatial and temporal features of surface structure and friction signal, respectively. It is found that the disc worn surface has a 3D fractal nature, and the friction coefficient signal has a chaotic nature. Additionally, the correlation coefficients between the fractal dimension D and standard deviation of distance matrix STD, and multifractal spectrum width [ ] and STD, were −0.7727 and 0.7130, respectively. The absolute values of both correlation coefficients greater than 0.5 indicate a strong similarity between spatial fractal and temporal chaos in the friction system. This characteristic is beneficial to online recognition of worn surface by using the friction coefficient signal in real time.

To enhance the corrosion resistance of aluminum alloy exposed to marine environment, a novel Peano fractal micro-nano texture was introduced. The Peano micro-nano textures with three depths were prepared by laser etching technology, and the textured surfaces were modified by using an ethanol solution of 1H, 1H, 2H, 2H-perfluorodecyltriethoxysilane (PFDS). The hydrophobic properties of aluminum alloy surfaces with Peano textures were measured. The wetting mechanism was analyzed via XPS characterization. And the electrochemical experiments were performed to explore the corrosion resistance of a superhydrophobic surface. The results showed that LS-d30 (laser processed specimen with depth of 30 µm) exhibited the optimal superhydrophobicity, with a water contact angle of 169.3° and a sliding angle of 3.9°. The Peano micro-nano texture facilitated the adsorption of PFDS, resulting in the creation of CF₂-CF₂ and CF₃-CF₃ functional groups on the surface. These functional groups contributed to the enhancement of hydrophobic properties. The LS-d30 surface exhibited a superior corrosion inhibition rate of 84.16%. Additionally, EIS revealed a significant increase in the corrosion resistance of the Peano fractal micro-nano texture surface.

Aiming to explore the influence of ultrasonic burnishing technology on the wear behaviors of Al7075 alloy friction pairs, the recurrence analysis method is employed to study the evolutions of recurrence plot (RP) and recurrence quantification analysis (RQA) parameters of friction coefficient signals. The results show that the RPs of burnishing Al7075 alloy specimens evolve from an abrupt structure to a homogeneous structure in the wear process. The average value of determinism [ ] and the average value of entropy [ ] of burnishing specimens as a whole are larger than those of nonburnishing specimens. For the burnishing specimens, the [ ] and [ ] are the highest under the load of 25[ ]N, with the values of 34.2008 and 4.3129, respectively. It demonstrates that the friction system of burnishing Al7075 alloy under the load of 25[ ]N has superior determinism and stability.

Closed-loop neural interfaces with on-chip machine learning can detect and suppress disease symptoms in neurological disorders or restore lost functions in paralyzed patients. While high-density neural recording can provide rich neural activity information for accurate disease-state detection, existing systems have low channel counts and poor scalability, which could limit their therapeutic efficacy. This work presents a highly scalable and versatile closed-loop neural interface SoC that can overcome these limitations. A 256-channel time-division multiplexed (TDM) front-end with a two-step fast-settling mixed-signal DC servo loop (DSL) is proposed to record high-spatial-resolution neural activity and perform channel-selective brain-state inference. A tree-structured neural network (NeuralTree) classification processor extracts a rich set of neural biomarkers in a patient- and disease-specific manner. Trained with an energy-aware learning algorithm, the NeuralTree classifier detects the symptoms of underlying disorders (e.g., epilepsy and movement disorders) at an optimal energy-accuracy tradeoff. A 16-channel high-voltage (HV) compliant neurostimulator closes the therapeutic loop by delivering charge-balanced biphasic current pulses to the brain. The proposed SoC was fabricated in 65-nm CMOS and achieved a 0.227-$\mu$J/class energy efficiency in a compact area of 0.014mm$^2$/channel. The SoC was extensively verified on human electroencephalography (EEG) and intracranial EEG (iEEG) epilepsy datasets, obtaining 95.6%/94% sensitivity and 96.8%/96.9% specificity, respectively. In vivo neural recordings using soft $\mu$ECoG arrays and multi-domain biomarker extraction were further performed on a rat model of epilepsy. In addition, for the first time in literature, on-chip classification of rest-state tremor in Parkinson's disease (PD) from human local field potentials (LFPs) was demonstrated.

With the urgent demand of high-end equipment for high quality surfaces, the technique of ultrasonic vibration-assisted burnishing is introduced to strengthen the surface properties. To explore the influence of the ultrasonic vibration on the dynamic response of a burnishing system, the burnishing friction force generated from a multi-ball surface burnishing system was characterized by chaos theory. The system had four assisted forms: no ultrasonic vibration, one-dimensional (1D) ultrasonic in x-axis, 1D ultrasonic in z-axis, and 2D ultrasonic in xz-axis. The results showed that any burnishing system had chaotic nature. Under the 2D ultrasonic vibration-assisted burnishing, the burnishing friction force was reconstructed to be a chaotic attractor with high convergence degree. Moreover, the burnishing system has notable complexity and stability. The burnished Al7075 alloy sample has an excellent surface with a higher smoothness and hardness. The burnishing with 2D ultrasonic vibration in xz-axis is a technique to enhance surface properties.

The purpose of this paper is to establish the relationship between surface morphology and friction coefficient in the wear process. Different wear stage tests of AISI 52100 ring sliding against AISI 5120 disc were designed and conducted on a rotating setup. The fractal and chaos theories were employed to study the nonlinear features of surface structure and friction signal from spatial and temporal scales. The results showed that 3D surface morphology has fractal nature. The fractal dimension D_s first increased and then stabilized at a maximum and finally decreases dramatically. The multifractal spectrum width Δα presented an contrary evolution trend. The friction coefficient signal has chaotic nature. The standard deviation of distance matrix STD obeyed the evolution rule of a bathtub curve. The correlation value between D_s and STD was − 0.7727, and the correlation value between Δα and STD was 0.7130. The strong correlation between spatial and temporal scales is beneficial to on-line recognition and prediction of wear states in real time.

The leveling and measurement of the aircraft is performed after the final assembly is completed. Measurements are used to check the accuracy of the geometric relationships within and between the various components of the aircraft and checks whether the aircraft assembly meets the overall design requirements. It is performed on the datum marks of the level measurement. During the leveling and measurement of a certain type of aircraft, the horizontal tail cathedral angles, and the engine installation angles of many aircraft have been found to have different degrees of deviation. These deviations have impact on aerodynamic characteristics, stability performance, and on-site production schedule of the aircraft. This paper has carried out special research on this deviation of the horizontal tail cathedral angles and the engine installation angles, by using empirical formulas and other methods to evaluate the deviation of the leveling and measurement, to provide a basis for the deviation evaluation of the leveling and measurement, improve the evaluation efficiency, and ensure the aircraft mass production. In addition, this paper also summarizes the root causes of the deviation, and provides an improvement direction for the aircraft’s configuration control, fuel consumption reduction and carbon dioxide emission reduction.