Predicting the fatigue life of remanufactured centrifugal compressor impellers is a critical problem. In this paper, the S-N curve data were obtained by combining experimentation and theory deduction. The load spectrum was compiled by the rain-flow counting method based on the comprehensive consideration of the centrifugal force, residual stress, and aerodynamic loads in the repair region. A fatigue life simulation model was built, and fatigue life was analyzed based on the fatigue cumulative damage rule. Although incapable of providing a high-precision prediction, the simulation results were useful for the analysis of fatigue life impact factors and fatigue fracture areas. Results showed that the load amplitude greatly affected fatigue life, the impeller was protected from running at over-speed, and the predicted fatigue life was satisfied within the next service cycle safely at the rated speed.

The accumulated damage process of rolling contact fatigue (RCF) of plasma-sprayed coatings was investigated. The influences of surface roughness, loading condition, and stress cycle frequency on the accumulated damage status of the coatings were discussed. A ball-on-disc machine was employed to conduct RCF experiments. Acoustic emission (AE) technique was introduced to monitor the RCF process of the coatings. AE signal characteristics were investigated to reveal the accumulated damage process. Result showed that the polished coating would resist the asperity contact and remit accumulated damage. The RCF lifetime would then extend. Heavy load would aggravate the accumulated damage status and induce surface fracture. Wear became the main failure mode that reduced the RCF lifetime. Frequent stress cycle would aggravate the accumulated damage status and induce interface fracture. Fatigue then became the main failure mode that also reduced the RCF lifetime.

Crankshaft is regarded as an important component of engines, and it is an important application of remanufacturing because of its high added value. However, the fatigue failure research of remanufactured crankshaft is still in its primary stage. Thus, monitoring and investigating the fatigue failure of the remanufacturing crankshaft is crucial. In this paper, acoustic emission (AE) technology and machine vision are used to monitor the four-point bending fatigue of 42CrMo, which is the material of crankshaft. The specimens are divided into two categories, namely, pre-existing crack and non-pre-existing crack, which simulate the crankshaft and crankshaft blank, respectively. The analysis methods of parameter-based AE techniques, wavelet transform (WT) and SEM analysis are combined to identify the stage of fatigue failure. The stage of fatigue failure is the basis of using AE technology in the field of remanufacturing crankshafts. The experiment results show that the fatigue crack propagation style is a transgranular fracture and the fracture is a brittle fracture. The difference mainly depends on the form of crack initiation. Various AE signals are detected by parameter analysis method. Wavelet threshold denoising and WT are combined to extract the spectral features of AE signals at different fatigue failure stages.

Laser hot wire cladding, with the prominent features of low heat input, high energy efficiency, and high precision, is widely used for remanufacturing metal parts. The cladding process, however, needs to be improved by using a quantitative method. In this work, volumetric defect ratio was proposed as the criterion to describe the integrity of forming quality for cladding layers. Laser deposition experiments with FV520B, one of martensitic stainless steels, were designed by using the Taguchi method. Four process variables, namely, laser power (P), scanning speed (V_s), wire feed rate (V_f), and wire current (I), were optimized based on the analysis of signal-to-noise (S/N) ratio. Metallurgic observation of cladding layer was conducted to compare the forming quality and to validate the analysis method. A stable and continuous process with the optimum parameter combination produced uniform microstructure with minimal defects and cracks, which resulted in a good metallurgical bonding interface.

This work discusses the interactive effects between every two of argon flow rate, voltage, and spray distance on in-flight particles by plasma spray and constructs models that can be used in predicting and analyzing average velocity and temperature. Results of the response surface methodology show that the interactive effects between voltage and spray distance on particle in-flight properties are significant. For a given argon flow rate, particle velocity and temperature response surface are obviously bending, and a saddle point exists. With an increase in spray distance, the interactive effects between voltage and argon flow rate on particle in-flight properties appear gradually and then weaken. With an increase in voltage, the interactive effects between spray distance and argon flow rate on particle in-flight properties change from appearing to strengthening and then to weakening.

Natural gas, whose primary constituent is methane, has been considered a convincing alternative for the growth of the energy supply worldwide. Adsorbed natural gas (ANG), the most promising methane storage method, has been an active field of study in the past two decades. ANG constitutes a safe and low-cost way to store methane for natural gas vehicles at an acceptable energy density while working at substantially low pressures (3.5–4.0 MPa), allowing for conformable store tank. This work serves to review the state-of-the-art development reported in the scientific literature on adsorbents, adsorption theories, ANG conformable tanks, and related technologies on ANG vehicles. Patent literature has also been searched and discussed. The review aims at illustrating both achievements and problems of the ANG technologies-based vehicles, as well as forecasting the development trends and critical issues to be resolved of these technologies.

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

Friction stir welding (FSW) process has gained attention in recent years because of its advantages over the conventional fusion welding process. These advantages include the absence of heat formation in the affected zone and the absence of large distortion, porosity, oxidation, and cracking. Experimental investigations are necessary to understand the physical behavior that causes the high tensile strength of welded joints of different metals and alloys. Existing literature indicates that tensile properties exhibit strong dependence on the rotational speed, traverse speed, and axial force of the tool that was used. Therefore, this study introduces the experimental procedure for measuring tensile properties, namely, ultimate tensile strength (UTS) and tensile elongation of the welded AA 7020 Al alloy. Experimental findings suggest that a welded part with high UTS can be achieved at a lower heat input compared with the high heat input condition. A numerical approach based on genetic programming is employed to produce the functional relationships between tensile properties and the three inputs (rotational speed, traverse speed, and axial force) of the FSW process. The formulated models were validated based on the experimental data, using the statistical metrics. The effect of the three inputs on the tensile properties was investigated using 2D and 3D analyses. A high UTS was achieved, including a rotational speed of 1050 r/min and traverse speed of 95 mm/min. The results also indicate that 8 kN axial force should be set prior to the FSW process.

The study proposes an innovative and completely new but low-cost configuration of a platform that can easily climb stairs. This platform serves the purpose of a chassis. Different versions, such as staircase-climbing wheelchair or staircase-climbing trolley for material transferring, can be derived depending on the structure built on the platform. The driving wheels have a shape that completely matches with the profile of the steps. Complex components are eliminated. Thus, this platform is conveniently applicable in the configurations useful for climbing staircases.

The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm (k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S_r was classified by the k-NN algorithm with training set T_z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler’s numbers. Last, while the classification confidence coefficient equaled k, made S_r as one sample of pre-training set T_z′. The training set T_z increased to T_z+1 by T_z′ if T_z′ was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65% identification accuracy, also selected five groups of samples to enlarge the training set from T₀ to T₅ by itself.

Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into three-dimensional (3D) grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.