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Mechanical properties are important indicators for evaluating the quality of strips. This paper proposes a mechanical performance prediction model based on the Gray Wolf Optimization (GWO) algorithm and the Extreme Learning Machine (ELM) algorithm. In the modeling process, GWO is used to determine the optimal weights and deviations of ELM and experiments are used to determine the model's key parameters. The model effectively avoids manual intervention and significantly improves aluminum alloy strips' mechanical property prediction accuracy. This paper uses processed data from the aluminum alloy production plant of Shandong Nanshan Aluminum Co., Ltd. as experimental data. When the prediction deviation is controlled within ±10%, the GWO-ELM model can achieve a correct rate of 100% for tensile strength, 97.5% for yield strength, and 77.5% for elongation on the test set. The RMSE of the tensile strength, yield strength, and elongation of the GWO-ELM model was 5.365, 11.881, and 1.268, respectively. The experimental results show that the GWO-ELM model has higher accuracy and stability in predicting aluminum alloy strips' tensile strength, yield strength, and elongation. The GWO-ELM model effectively avoids the defects of the traditional model. It has a special guiding significance for producing aluminum alloy strips. [ABSTRACT FROM AUTHOR]

In the context of today's supply-side structural reform, the research on the relationship between foreign trade and economic growth has received extensive attention from researchers. Since China's economic reform and opening up in the late 1970s, China's economy has experienced a relatively long period of rapid growth. From 1978 to the end of 2008, China's economy grew at an average annual rate of about 10%, and its GDP grew from US$9.75 billion in 1978 to US$1,430.69 billion in 2008. The progress is amazing, the total import and export of goods increased from 20.64 billion US dollars in 1978 to 25.6326 billion US dollars in 2008, and the world ranking rose from 32nd in 1978 to 3rd in 2008, second only to the United States and Germany. The analysis of the test results presented in this paper shows that, from 1995 to 2014, China's average annual exports accounted for 23.72% of GDP. Since China joined the World Trade Organization in 2001, China's share of export trade has increased significantly. In 2004, the total value of exports reached 4910.33 billion yuan, equivalent to more than 29% of China's GDP, and continued to rise in the following years. China's total exports as a share of GDP declined between 2009 and 2014 but remained above 20% in both cases. [ABSTRACT FROM AUTHOR]

The magnetorheological elastomer (MRE) is a kind of smart material, which is often processed as vibration isolation and mitigation devices to realize the vibration control of the controlled system. The key to the effective isolation of vibration and shock absorption is how to accurately and in real time determine the magnitude of the applied magnetic field according to the motion state of the controlled system. In this paper, an optimal fuzzy fractional-order PID (OFFO-PID) algorithm is proposed to realize the vibration isolation and mitigation control of the precision platform with MRE devices. In the algorithm, the particle swarm optimization algorithm is used to optimize initial values of the fractional-order PID controller, and the fuzzy algorithm is used to update parameters of the fractional-order PID controller in real time, and the fractional-order PID controller is used to produce the control currents of the MRE devices. Numerical analysis for a platform with the MRE device is carried out to validate the effectiveness of the algorithm. Results show that the OFFO-PID algorithm can effectively reduce the dynamic responses of the precision platform system. Also, compared with the fuzzy fractional-order PID algorithm and the traditional PID algorithm, the OFFO-PID algorithm is better. [ABSTRACT FROM AUTHOR]

In this paper, we compare the performances of the least mean square (LMS) and constant modulus (CM) algorithms for beamforming. Our interest in these algorithms finds its origins in their reliability as a source-receiver pair. In addition, their use brings a great frequency of diversity even to respond quickly to the increasing spectral demand. The results suggest that the greater the number of elements in the antenna, the better the directivity for both LMS and CM. We also note that a judicious choice of the control parameter mu leads to a better speed of convergence for the two algorithms. Let us note, however, that LMS is more efficient. Our simulations show that in an environment affected by white Gaussian noise, LMS is more robust than CM. This confirms the theoretical result due to the fact that LMS uses a sequence for learning. Performance analyses of the two techniques are simulated in the MATLAB environment. [ABSTRACT FROM AUTHOR]

In the process of 3D printing, the setting of the initial layer is the most important step to achieve perfect printing results, and its main function is to prevent warping in 3D printing. There are three main types of the first layer: Raft, Brim, and Skirt. The Brim is a special skirt and is usually the preferred starting layer for the printing process. In order to increase the adhesion, multiple Brim contour edges will be printed, which increases the difficulty of removal. Otherwise, poor adhesion effect will occur. By analyzing the distinction between inner and outer contours of polygons, the offset process of contour points in different cases is calculated in this paper, and a simplified processing method of contour offset line is designed by using the idea of Douglas–Peucker simplifying curve feature points. According to the functional characteristics of the Brim edge structure, a novel platform attached support structure is generated based on ray-casting algorithm and contour offset algorithm. The proposed algorithm is encapsulated into the slicing engine and compared with three common initial layer structures for conducting part printing comparison experiments. The experimental results show that the edge structure realized by the proposed generation optimization algorithm of a novel platform attached support can effectively reduce the slicing execution time, and the auxiliary structure has little impact on the forming quality. It can be easier to remove on the premise and the warpage of the printing model is small. [ABSTRACT FROM AUTHOR]

To select reasonable PID controller parameters and improve control performances of hydraulic systems, a variable weight beetle antenna search algorithm is proposed for PID tuning in the hydraulic system. The beetle antennae search algorithm is inspired by the beetle preying habit depending on symmetry antennae on the head. The proposed algorithm added the exponential equation mechanism strategy in the basic algorithm to further improve the searching performance, the convergence speed, and the optimization accuracy and obtain new iteration and an updating method in the global searching and local searching stages. In the PID tuning process, advantages of less parameters and fast iteration are realized in the PID tuning process. In this paper, different dimension functions were tested, and results calculated by the proposed algorithm were compared with other famous algorithms, and the numerical analysis was carried out, including the iteration, the box-plot, and the searching path, which comprehensively showed the searching balance in the proposed algorithm. Finally, the reasonable PID controller parameters are found by using the proposed method, and the tuned PID controller is introduced into the hydraulic system for control, and the time-domain response characteristics and frequency response characteristics are given. The results show that the proposed PID tuning method has good PID parameter tuning ability, and the tuned PID has a good control ability, which makes the hydraulic system achieve the desired effect. [ABSTRACT FROM AUTHOR]

In order to avoid subjective estimation of the direction of groove by using a tester in the four-ball friction test, an automatic wear angle detection method based on gray difference of inclination angle is proposed in this paper. First, the gray difference between the pixel and its W × 2W neighborhood pixels is acquired, in which each neighborhood pixel corresponds to an inclination angle. Second, a row's grayscale difference of inclination angle is calculated, which is the sum of grayscale difference of all pixels in the same row with the same inclination angle. Third, the inclination angle corresponding to the minimum row's grayscale difference is defined as the approach angles. Finally, the first t approaching angles with the highest frequency determine the wear angles. Compared with true angles determined manually, the simulation results of 200 samples show that the average absolute error is 2.1238° and the average running time is 1.3 s per frame. The influence of the algorithm parameters on detection precision is also analyzed. [ABSTRACT FROM AUTHOR]

The protection of earthen sites plays an important role in the context of preservation of cultural heritage, especially in the inheritance and promotion of history and culture. The aim of the paper is to present the essential results of an ongoing research on a reinforced rammed earthen wall in Suoyang City (Guazhou, China). The wall vibrations caused by ambient actions were analyzed using the stochastic subspace algorithm to estimate the modal parameters of the wall. The frequencies of the first three orders are 3.566 Hz, 5.003 Hz, and 6.250 Hz, and the corresponding modes are first-order transverse bending, second-order left and right torsion, and third-order vertical bending, respectively. Then, according to the data of elastic modulus obtained in the lab, the finite element calculation is carried out, and referring to the results of field measurement, the revised elastic modulus value is 205.90 MPa. It is worth mentioning that the revised value is significantly improved from the original laboratory value, and it is also indicated that the seismic performance of the reinforced wall has been significantly improved. The present work is expected to provide a theoretical basis for reinforcement, protection, and seismic control of earthen ruins. [ABSTRACT FROM AUTHOR]

For long-term monitoring of the midspan deflection of Songjiazhuang cloverleaf junction on 309 national roads in Zibo city, this paper proposes Zhang’s calibration-based DIC deflection monitoring method. CCD cameras are used to track the change of targets’ position, Zhang’s calibration algorithm is introduced to acquire the intrinsic and extrinsic parameters of CCD cameras, and the DIC method is combined with Zhang’s calibration algorithm to measure bridge deflection. The comparative test between Zhang’s calibration and scale calibration is conducted in lab, and experimental results indicate that the proposed method has higher precision. According to the deflection monitoring scheme, the deflection monitoring software for Songjiazhuang cloverleaf junction is developed by MATLAB, and a 4-channel CCD deflection monitoring system for Songjiazhuang cloverleaf junction is integrated in this paper. This deflection monitoring system includes functions such as image preview, simultaneous collection, camera calibration, deflection display, and data storage. In situ deflection curves show a consistent trend; this suggests that the proposed method is reliable and is suitable for the long-term monitoring of bridge deflection. [ABSTRACT FROM AUTHOR]

Advanced vision solutions enable manufacturers in the technology sector to reconcile both competitive and regulatory concerns and address the need for immaculate fault detection and quality assurance. The modern manufacturing has completely shifted from the manual inspections to the machine assisted vision inspection methodology. Furthermore, the research outcomes in industrial automation have revolutionized the whole product development strategy. The purpose of this research paper is to introduce a new scheme of automation in the sand casting process by means of machine vision based technology for mold positioning. Automation has been achieved by developing a novel system in which casting molds of different sizes, having different pouring cup location and radius, position themselves in front of the induction furnace such that the center of pouring cup comes directly beneath the pouring point of furnace. The coordinates of the center of pouring cup are found by using computer vision algorithms. The output is then transferred to a microcontroller which controls the alignment mechanism on which the mold is placed at the optimum location. [ABSTRACT FROM AUTHOR]

The aim of the current study lies in the development of a reformative technique of image segmentation for Computed Tomography (CT) concrete images with the strength grades of C30 and C40. The results, through the comparison of the traditional threshold algorithms, indicate that three threshold algorithms and five edge detectors fail to meet the demand of segmentation for Computed Tomography concrete images. The paper proposes a new segmentation method, by combining multiscale noise suppression morphology edge detector with Otsu method, which is more appropriate for the segmentation of Computed Tomography concrete images with low contrast. This method cannot only locate the boundaries between objects and background with high accuracy, but also obtain a complete edge and eliminate noise. [ABSTRACT FROM AUTHOR]

This paper established the fault diagnosis system of aluminum electrolysis, according to the characteristics of the faults in aluminum electrolysis. This system includes two subsystems; one is process fault subsystem and the other is fault subsystem. Process fault subsystem includes the subneural network layer and decision fusion layer. Decision fusion neural network verifies the diagnosis result of the subneural network by the information transferring over the network and gives the decision of fault synthetically. EMD algorithm is used for data preprocessing of current signal in stator of the fault subsystem. Wavelet decomposition is used to extract feature on current signal in the stator; then, the system inputs the feature to the rough neural network for fault diagnosis and fault classification. The rough neural network gives the results of fault diagnosis. The simulation results verify the feasibility of the method. [ABSTRACT FROM AUTHOR]

Diffusion coefficient from chloride migration test is currently used; however this cannot provide a conventional solution like total chloride contents since it depicts only ion migration velocity in electrical field. This paper proposes a simple analysis technique for chloride behavior using apparent diffusion coefficient from neural network algorithm with time-dependent diffusion phenomena. For this work, thirty mix proportions of high performance concrete are prepared and their diffusion coefficients are obtained after long term-NaCl submerged test. Considering time-dependent diffusion coefficient based on Fick's 2nd Law and NNA (neural network algorithm), analysis technique for chloride penetration is proposed. The applicability of the proposed technique is verified through the results from accelerated test, long term submerged test, and field investigation results. [ABSTRACT FROM AUTHOR]

Damage identification based on the change of dynamic properties is an issue worthy of attention in structure safety assessment, nevertheless, only a small number of discontinuous members in existing structure are damaged under service condition, and the most remaining members are in good condition. According to this feather, we developed an effective damage location and situation assessment algorithm based on residual mode vector with the first mode information of targeted structure, which utilized the quantitative relationship between first natural modes of global structure with the change of the element stiffness. Firstly, the element damage location is determined with exploitation of the sparseness of element stiffness matrices based on the discontinuity of damaged members. Then, according to the distribution characteristics of the corresponding residual mode vector, the nodal equilibrium equation about the damage parameter is established based on the residual mode vector, and the damage coefficients of structural elements are evaluated with the proposed equations. Two numerical examples are given to verify the proposed algorithm. The results showed that the proposed damage identification method is consistent with the preset damage. It can even accurately identify large-degree damages. The proposed algorithm only required the first-order modal information of the target structures and held few requirements of analysis resource; hence when compared with existing methods, it has obvious advantages for structural damage identification. [ABSTRACT FROM AUTHOR]

Underwater structures are crucial for national economic and social development. However, because of their complex environment, they are susceptible to damage during service. This damage should be prevented to minimize casualties and economic loss. Therefore, this study investigates the problems of disease identification and area statistics of underwater structures. To this end, the Dark-Retinex (DR) algorithm that can enhance the image of underwater structure defects is proposed. The algorithm consists of a combination of a dark channel algorithm and the Retinex algorithm. This study analyzes the current research status of underwater image processing technology, designs the overall framework of the DR algorithm, and uses the underwater structure disease image to verify the algorithm. Comparing the effect of the image with only the dark channel defogging and DR algorithm processing, the DR algorithm is observed to achieve "defogging" processing of underwater structural disease images to achieve better enhancement effects. Moreover, for accurate disease area statistics, the binary morphology and optimal threshold segmentation theories are combined to perform disease edge screening and remove interference information. Finally, accurate statistics of the proportion of diseased pixels are achieved, as well as the quantitative detection of surface diseases of underwater structures. After actual operational verification, the improved image dehazing and parallel boundary screening algorithms can achieve better application results to detect underwater structure defects and disease statistics. The objective evaluation shows that the DR algorithm facilitates image processing, can obtain relatively high-quality target images, and can solve the problems of time-consuming and labor-intensive detection of underwater structures, with significant risks and limitations. This helps pave the way for (1) the actual engineering of surface structure detection of underwater structures, (2) future storage in the database and assessment of hazard levels, and (3) a guide for engineering technicians to take corresponding maintenance measures. [ABSTRACT FROM AUTHOR]