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Surface morphology impacts material performance and durability significantly. To gain a deeper understanding of the impact of laser shock peening (LSP) treatment on the surface morphology of materials and to explore more optimized LSP treatment strategies, this study presents an investigation into the surface morphology of 20CrMnTi steel following LSP treatment. Through the application of statistical analysis, the study examines the induced surface morphology variations resulting from both single-point repetitive LSP and multiple LSP treatments. Experimental results demonstrate significant alterations in surface roughness and peak height distribution after LSP treatments, accompanied by the presence of high amplitude compressive residual stress (CRS). Moreover, the depth of laser-induced indentations is found to be closely related to the number of impacts, and the incidence angle of the laser exhibits a discernible influence on the directional texture and periodicity of the impacted surfaces. This investigation also proposes a method for estimating surface morphology variations after LSP treatment by means of analysis of impact patterns, thereby offering the potential for enhancing the friction and wear performance of the impacted surfaces through the adjustment of the impact region position during multi-layer LSP treatment. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to improve the wear resistance of titanium alloy using a high-hardness boride layer, which was fabricated on Ti6Al4V by a high-temperature boronizing process. Design/methodology/approach: The boride layers on Ti6Al4V were obtained at 1000°C for 5–15 h. Scanning electron microscopy, energy dispersive analysis and X-ray diffractometer were used to characterize the properties of the boride layer. The tribological performance of the boride layer at room and elevated temperatures was investigated. Findings: The X-ray diffraction analysis showed that the boride layers were a dual-phase structure of TiB and TiB2. When the boronizing time increased from 5 h to 15 h, the microhardness increased from 1192 HV0.5 to 1619.8 HV0.5. At 25°C and elevated temperatures, the friction coefficients of the boride layers were higher than that of Ti6Al4V. The wear track areas of T-5 at 200°C and 400°C were 2.5 × 10–3 and 1.1 × 10–3 mm2, respectively, which were 6.1% and 2.6% of that of Ti6Al4V, indicating boride layer exhibited a significant wear resistance. The wear mechanisms of the boride layer transformed from slight peeling to oxidative wear and abrasive wear as the temperature was raised. Originality/value: The findings provide an effective strategy for improving the wear resistance of Ti6Al4V and have important implications for the application of titanium alloy in a high-temperature field. [ABSTRACT FROM AUTHOR]

Soft robots offer a great application potential in the field of military, medical, and industry. In this study, a rolling gait was adopted to the design of the soft robot so as to improve the locomotion velocity of the soft robot actuated by the magnetic field. The soft robot was fabricated as a square frame structure (6 × 6 × 0.6 mm) to achieve grasping function. The experimental results indicated that the designed soft robot could roll on a slope with a maximum inclination around 30° under the given conditions. The velocity of the soft robot during the rolling process would decrease with the increase of the inclination. Meanwhile, the soft robot could carry objects 3.75 times its own weight when it rolled on a level pavement. Further analysis and experiments suggested that the rolling locomotion of the soft robot relied on the magnetic torque and the friction force. The locomotion velocity of the soft robot was related to the perimeter of the contour composed of the soft robot and the object being grasped. Moreover, a modular assembly strategy was proposed to improve the locomotion and grasping performance of the soft robot. The findings of this work will help to promote the application of untethered soft robots. [ABSTRACT FROM AUTHOR]

The hydrolytic cleavage of pUC19 DNA as promoted by the trivalent cerium complex (CeL) of diaza-crown ether ligand L (1,4,10,13-tetraoxa-7,16-diazacyclooctadecane) was examined in detail. The interaction of CeL with calf thymus DNA was investigated by UV-Vis spectroscopy. Furthermore, studies on the effects of pH, reaction time, and the concentration of CeL on cleavage of pUC19 DNA were carried out by gel electrophoresis. The results indicate that CeL can bind to DNA electrostatically with a binding constant of 2.18×104 M-1; CeL can promote the cleavage of plasmid pUC19 DNA from supercoiled to the nicked form under the appropriate conditions, and the optimal pH value is 7.54. The lack of effect of radical scavengers indicates that the cleavage involves hydrolytic cleavage. [ABSTRACT FROM AUTHOR]

Changing or replenishing the oil in an engine influences the accuracy of oil monitoring. An online visual ferrograph (OLVF) was used to monitor engine wear in this study. The variation in the debris concentration in an engine lubrication system was studied, and its equilibrium concentration of debris was determined to correct the data acquired using an OLVF after fresh oil was added to the system. This correction made the monitoring data of OLVF continuous, thereby enabling the raw data collected before and after oil replenishment to be compared. Changing the oil caused an interruption in the raw data. By combining different prediction modes, a comprehensive trend prediction framework was constructed to correct the data acquired after the engine’s oil was changed. Thus, the data acquired before and after the oil change could be analysed and compared. In addition, the engine’s whole wear trends could be observed. This correction strategy could also be used to assess the engine’s health and to predict its degradation trend. [ABSTRACT FROM AUTHOR]

Wear-debris characterization using ferrography, which is of importance in machine condition monitoring and fault diagnosis, remains a challenge. The newly developed on-line visual ferrograph can provide digital wear-debris images and perform on-line analysis during wear monitoring. In this article, image projection transformation was utilized for extracting the overall characteristics of the wear-debris chains according to the fundamental feature of wear-debris arraying along the horizontal direction. Moreover, Full Binary Tree Based Image Division was also proposed to analyse the regional features on different scales in on-line visual ferrographic images. Several descriptive parameters including thinning ratio, chain length and chain width were proposed. In the experiments, four types of images with different wear-debris groups were compared and a group of time-sequence on-line visual ferrographic images of an inline four-cylinder gasoline engine was studied. It is found that more comprehensive wear information can be acquired through the proposed multi-parameter description method. Meanwhile, the image projection transformation method extracts macrocharacteristics of images rapidly and efficiently and the thinning ratio measures wear-debris width in an intuitive way. [ABSTRACT FROM PUBLISHER]

This study applies stepped loading and stepped velocity approaches to simulate the actual working conditions of gasoline engines. Accelerated wear tests were conducted for piston rings and cylinder liners under different lubricating conditions by using a self-made pin-on-disc wear machine equipped with an on-line visual ferrograph (OLVF) for wear monitoring. The wear coefficients for oil monitoring were extracted to distinguish between constant conditions and stepped changing conditions. A similarity model for oil monitoring was constructed and the monitoring data sets of similar working conditions were grouped together. Results show that the OLVF monitoring system can be used to obtain the real-time variation in debris concentration. The index of particle coverage area (IPCA) of OLVF increases abruptly after the load or speed changes. The similarity model can evaluate the similarity of the variation trend of IPCA under different operating conditions. The relationship between IPCA and working conditions was examined in this study and provides an essential support to wear monitoring and life prediction of engines. [ABSTRACT FROM AUTHOR]

Condition based maintenance(CBM) issues a new challenge of real-time monitoring for machine health maintenance. Wear state monitoring becomes the bottle-neck of CBM due to the lack of on-line information acquiring means. The wear mechanism judgment with characteristic wear debris has been widely adopted in off-line wear analysis; however, on-line wear mechanism characterization remains a big problem. In this paper, the wear mechanism identification via on-line ferrograph images is studied. To obtain isolated wear debris in an on-line ferrograph image, the deposition mechanism of wear debris in on-line ferrograph sensor is studied. The study result shows wear debris chain is the main morphology due to local magnetic field around the deposited wear debris. Accordingly, an improved sampling route for on-line wear debris deposition is designed with focus on the self-adjustment deposition time. As a result, isolated wear debris can be obtained in an on-line image, which facilitates the feature extraction of characteristic wear debris. By referring to the knowledge of analytical ferrograph, four dimensionless morphological features, including equivalent dimension, length-width ratio, shape factor, and contour fractal dimension of characteristic wear debris are extracted for distinguishing four typical wear mechanisms including normal, cutting, fatigue, and severe sliding wear. Furthermore, a feed-forward neural network is adopted to construct an automatic wear mechanism identification model. By training with the samples from analytical ferrograph, the model might identify some typical characteristic wear debris in an on-line ferrograph image. This paper performs a meaningful exploratory for on-line wear mechanism analysis, and the obtained results will provide a feasible way for on-line wear state monitoring. [ABSTRACT FROM AUTHOR]

Wear over time affects engine’s reliability and efficiency. On-line wear monitoring could provide timely information about engine health condition. In the current study, on-line monitoring of engine wear via an on-line visual ferrograph was performed in reliability tests of gasoline engines, and a wavelet-analysis-based differential method of data analysis for wear condition estimation was proposed. The tests were designed for 220 h, which consist of a running-in stage of 20 h and a thermal shock cycle test stage of 200 h. One of the tests was terminated because of failures in the main bearings and crankshaft journal at 146th hour of thermal shock cycle test, while the other two completed successfully without failures. Index of particle coverage area, which represents wear-debris concentration in lube oil, was studied, and piecewise trend-extraction of index of particle coverage area was achieved by wavelet decomposition and reconstruction. The first-order differential of the index of particle coverage area trend was used to represent the wear rate or the generation rate of debris for health condition assessment of engines. Off-line oil analyses were performed in laboratory via an analytical ferrograph, and engine disassembly results of the engines were given to determine the causes of engine failures if it happened. It is found that favorable trend extraction from index of particle coverage area could be achieved by the segmented wavelet de-noising. Moreover, on-line visual ferrograph monitoring estimated the engine wear at macro-levels effectively, and it provided an advance warning for the failures after the continued deterioration of the engine wear. The study and application of this method can make early failure prediction of engine and avoid serious fault. [ABSTRACT FROM PUBLISHER]