Search

Suppose that f : SX → SY is a surjective map between the unit spheres of two real ∞ (Γ)-type spaces X and Y satisfying the following equation We show that such a mapping f is phase equivalent to an...

To realize real-time detection of the operating environment of bridge cranes, this paper presents a three-dimensional mapping method using a binocular camera and laser ranging sensor. First, the left and right images are obtained by using the binocular camera, and the block matching is used for stereo correspondence to obtain the disparity image. Then, according to the reprojection matrix and the disparity image, the depth value of each pixel is obtained, and the depth image can be transformed into a three-dimensional point cloud of the current frame. Relying on the camera position data obtained by the laser ranging sensor, the three-dimensional point cloud generated from different positions is registered to obtain the three-dimensional point cloud of the craneʼs global operating environment. Finally, an octree map is used to represent the operating environment. To simulate the construction process of the operating environment of the bridge crane, an experimental platform was built, and experiments were carried out using the method proposed in this paper. The experimental results verified the feasibility of the method proposed in this paper.

With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

The corrosion of grounding materials seriously threatens the safe operation of the power system. The corrosion resistance of four typical grounding materials as carbon steel, galvanized steel, Zn–Al-coated steel, copper was studied in acid red soil. The results show that carbon steel, galvanized steel, Zn–Al-coated steel, copper exhibit different corrosion resistance behaviors, respectively. The corrosion rate of these grounding materials usually increases first and then slowly decreases. Pitting corrosion is the main corrosion feature of carbon steel. The corrosion rate of carbon steel is the largest compared to the other three grounding materials. The corrosion rate of galvanized steel is higher than that of copper. Copper has a low corrosion rate and exhibits good corrosion resistance, but the cost of copper is high and it causes heavy metal pollution. The corrosion rate of Zn–Al-coated steel is the lowest compared to the other three grounding materials, and it has the best corrosion resistance.

Bridge cranes must be able to sense their working environment to achieve autonomous operation. An active visual mapping system is presented in this research to adapt the measurement range based on the crane's operational state. The rotation angles of the two servos are computed based on the crane's speed so that the binocular camera is deflected and a greater field of view is gained in front, improving the crane's safety. An experimental platform is developed to simulate the operation process of the active vision 3D mapping system, and experiments are carried out using the approach proposed in this paper. The experimental results indicate that the technology can successfully enhance the mapping scope of the bridge cranes' digital operating environment and improve crane operation safety.

An improved soft kill option (SKO) method is proposed to achieve the optimization design of tower crane boom. For a better optimization performance, a parabolic weight coefficient is suggested and the displacement constraint is taken into consideration. In order to eliminate the numerical instability phenomena like checkerboard and mesh dependence, element temperature filter function is added into SKO method. Through the optimization data comparison of rectangular cantilever plate, it is verified that the improved SKO method can achieve a better result with more uniform stress and higher efficiency. Based on the dimension and load parameters of QTZ63 tower crane boom, an optimization model is established, and a periodic SKO method is put forward to optimize this model. The optimization result of the crane boom can provide a new thought for tower crane boom design.

A new method combined continuum topology with discrete truss is proposed for truss optimization. The optimized material distribution is obtained by means of continuum topology optimization and then transformed into initial truss. Based on the element principal stress and 8-neighborhood elements of continuum, force flow path extraction method is presented to obtain the initial truss layout. For section size optimization, criterion is deduced from a mathematical model by Lagrange multiplier method. Leveraging the free-form nature of continuum, this method can avoid the restriction of traditional ground structure. And it can achieve a better solution with less mass, smaller deformation and more uniform stress.

Public research institutions are encouraged to engage in industry sustainable collaboration in China. We develop an analytical framework based on the factor-process-outputs model and use a mechanism model by incorporating four elements (innovation climate, strategic partnership, collaborative mechanism, and the degree of participation) associated with the research institutions and industry collaboration. Using data collected from a face-to-face interview survey of 533 experts located at research institutions in seven Chinese provinces and one municipality who have collaborated with the seed industry, we use a structural equation model to identify important factors that affect innovation behavior. Results show that the innovation climate does not directly affect the participation of research institutions in research industry collaboration, however, it has a direct effect on strategic partnership and the collaborative mechanism. We find that an innovation climate could indirectly influence the participation of research institutions via collaborative mechanism and strategic partnership. Furthermore, strategic partnership and collaborative mechanism are found to moderate the participation behavior of research institutions. Moreover, we find that policy support, knowledge innovation strategies, and resource sharing mechanisms are essential factors for sustainable and effective collaboration.

Deep learning methods have been widely used in the field of intelligent fault diagnosis due to their powerful feature learning and classification capabilities. However, it is easy to overfit depth models because of the large number of parameters brought by the multilayer-structure. As a result, the methods with excellent performance under experimental conditions may severely degrade under noisy environment conditions, which are ubiquitous in practical industrial applications. In this paper, a novel method combining a one-dimensional (1-D) denoising convolutional autoencoder (DCAE) and a 1-D convolutional neural network (CNN) is proposed to address this problem, whereby the former is used for noise reduction of raw vibration signals and the latter for fault diagnosis using the de-noised signals. The DCAE model is trained with noisy input for denoising learning. In the CNN model, a global average pooling layer, instead of fully-connected layers, is applied as a classifier to reduce the number of parameters and the risk of overfitting. In addition, randomly corrupted signals are adopted as training samples to improve the anti-noise diagnosis ability. The proposed method is validated by bearing and gearbox datasets mixed with Gaussian noise. The experimental result shows that the proposed DCAE model is effective in denoising and almost causes no loss of input information, while the using of global average pooling and input-corrupt training improves the anti-noise ability of the CNN model. As a result, the method combined the DCAE model and the CNN model can realize high-accuracy diagnosis even under noisy environment.

Objective: As a carrier, bridge cranes are widely used in port cargo handling. Due to the structure of the crane itself, the load inevitably produces displacement deviation and lifting weight swing. Therefore, the optimization investigation of the bridge crane control system is carried out to guarantee the fast and secure operation of the crane. Method: According to the characteristics of bridge cranes, combined with the experience of on-site operating staff, the fuzzy rules that meet the working conditions of the site are designed by using the advantages of fuzzy PID (Proportion-Integration-Differentiation) control algorithm without relying on an accurate mathematical model, to set the parameters of the fuzzy PID controller. The speed control technique of frequency converter is adopted to design the system to improve the safety of the overall system. Results: The results show that the adjustment time of the swing angle of crane weight of the traditional PID control requires 6.79s, and the maximum swing angle of crane weight is 0.039rad, and the adjustment time under the fuzzy control is 4.89s, and the swing angle of crane weight is 0.013rad. The fuzzy PID controller surpasses the traditional PID controller in the positioning accuracy. It is not sensitive to changes in the internal parameters of the system. Also, it has strong adaptability to changes in operating conditions. The swing angle of crane weight is smaller, which further improves the robustness. The vector frequency conversion speed control has a more precise control effect on the speed and running track of the operating mechanism of the bridge crane. This method can be applied to the automatic operation mechanism of bridge cranes and achieve good control performance. Conclusion: The conducted optimization investigation of the bridge crane control system makes the control system flexible, simple and robust, providing important theoretical support for related explorations.

Accurate degradation state recognition of rolling bearing is critical to effective condition based on maintenance for improving reliability and safety. In this work, a new architecture is proposed to recognize the degradation state of the rolling bearing. Firstly, the time-domain features including RMS, kurtosis, skewness and RMSEE, and Mel-frequency cepstral coefficients features are extracted from bearing vibration signals, which are then used as the input of k-means algorithm. These unlabeled features are clustered by k-means in order to define the different categories of the bearing degradation state. In this way, the original vibration signals can be labeled. Then, the convolutional neural network recognition model is built, which takes the bearing vibration signals as input, and outputs the degradation state category. So, interference brought by human factors can be eliminated, and further, the bearing degradation can be grasped so as to make maintenance plan in time. The proposed method was tested by bearing run-to-failure dataset provided by the Center for Intelligent Maintenance System, and the result proved the feasibility and reliability of the methodology.

In the present study, electrical properties of a composite electrolyte composed of a BaZr 0.8 Y 0.2 O 3 -δ (BZY) and a perspective of defect chemistry. A DFT first-principles calculation further confirmed that proton transfer in molten carbonates was a low-energy process.

In order to achieve the layout and size optimization of the web members of tower crane boom, a truss topology and cross section size optimization method based on continuum is proposed considering three typical working conditions. Firstly, the optimization model is established by replacing web members with web plates. And the web plates are divided into several sub-domains so that periodic soft kill option (SKO) method can be carried out for topology optimization of the slender boom. After getting the optimized topology of web plates, the optimized layout of web members is formed through extracting the principal stress distribution. Finally, using the web member radius as design variable, the boom compliance as objective and the material volume of the boom as constraint, the cross section size optimization mathematical model is established. The size optimization criterion is deduced from the mathematical model by Lagrange multiplier method and Kuhn-Tucker condition. By comparing the original boom with the optimal boom, it is identified that this optimization method can effectively lighten the boom and improve its performance., {"references":["Y. Yang, D. Qing, T. Yang, \"A study on design optimization for dual lifting-point boom of tower crane,\" Construction Machinery and Equipment, vol. 34, pp. 16-19, June 2003.","J. Jia. Y. Wan, \"Light-weight design of tower crane boom structure based on multi-objective optimization,\" International Conference on Mechanical Science and Engineering, Qingdao: Atlantis Press, pp. 1-6, 2016.","H. Zhang, C. Xu, \"Optimized design for the structure of truss crane jib based on MATLAB and parameterized model,\" Journal of Wuhan University of Technology, vol. 35, pp. 201-204, Jan. 2011.","H. Jin, \"Structure analysis and optimization of the tower cranes,\" Hebei University of Technology, 2014.","R. Aelmić, P. Cvetković, R. Mijailović, \"Optimum dimensions of triangular cross-section in lattice structures,\" Meccanica, vol. 41, pp. 391-406, Apr. 2006.","R. Mijailović, G. Kastratović, \"Cross-section optimization of tower crane lattice boom,\" Meccanica, vol. 44, pp. 599-611, May 2009.","A. Baumgartner, L. Harzheim, C. Mattheck, \"SKO (soft kill option): the biological way to find an optimum structure topology,\" International Journal of Fatigue, vol. 14, pp. 387–393, June 1992.","J. Hou, X. Ding, \"SKO structural topology optimization method based on a continuous step-up reference stress criterion,\" China Mechanical Engineering, vol. 23, pp. 28-33 Jan. 2012.","H. Jiao, Q. Zhou, Q. Wu, W. Li, Y. Li, \"Periodic topology optimization of the box-type girder of bridge crane,\" Journal of Mechanical Engineering, vol. 23, pp. 134-139, Dec. 2014.\n[10]\tC. Mattheck, Design in nature: learning from trees. Berlin: Springer, 1998.\n[11]\tQ. Wu, Q. Zhou, X. Xiong, R. Zhang, \"Layout and sizing optimization of discrete truss based on continuum,\" International Journal of Steel Structures, vol. 17, pp. 43-51, Jan. 2017.\n[12]\tQ. Zhou, Q. Wu, X. Xiong, L. Wang, \"Optimal design of topology and section size of truss structures,\" Journal of Xi'an Jiaotong University, vol. 50, pp. 1-10, Sep. 2016."]}

Hydraulic pushing equipment is widely used to transport the extreme heavy structure and equipment in road and bridge, construction, railway, electric power, metallurgy, petrochemical, etc. In this article, the hydraulic pushing equipment can move with the pushed object along the track, which is mainly composed of hydraulic cylinder and clamping device. The clamping device installed in the back of the hydraulic cylinder mainly consists of a rod and bugles beside the rail. The device can provide reaction force when the piston rod stretches out through the compaction of the rod and bugle. The clamping device follows the movement of the hydraulic cylinder when the piston rod retracted. This paper takes the hydraulic pushing equipment of 2,500-ton ring crane as an example to introduce the specific design, and optimizes the key components and overall structure using ANSYS.

Aiming at solving the problem of excess or lack of maintenance which exists in traditional maintenance of stack crane in automatic storage and retrieval system, the stack-crane monitor and diagnostic system (SCMDS) based on the component module has been proposed, using the SCMDS as a research object, and utilizing the open-system architecture for condition-based maintenance (OSA-CBM) model and component technology theory for reference. First, this paper details the internal structure, functional modules, and interactive interface of the generic component module with the reconfigurable and scalable features in SCMDS. Second, it puts forward the six layers whole project of SCMDS which constituted by single and nested components. Finally, using the fault tree analysis model which established on the physical characteristics of the stack crane as an example, it describes the specific implementation of a single component and also provides the theoretical basis for application.

A kind of special spreaders of super-tonnage crane are studied and designed, which are used for lifting large-scale tower equipments. As a very key component or bearing of the crane, the design of the special spreader is in the pursuit of the rationalization and the lightweight of the structure on the premise of ensuring high security. Studying and analyzing the mechanical characteristics and the actual working conditions of the tower equipment, using Solid Works to build the parametric model and importing the image into the ANSYS Workbench for the finite element analysis which is based on the traditional mechanical design, a comprehensive scheme combining the traditional design and the parametric modeling and finite element design is proposed. Finally, take the spreader of the 2,500-t ring crane as an example, which proves the feasibility of the design concept and the design process. Also, it provides a theoretical basis and design method for the design of similar projects.

This paper is based on the design of 2500t ring crane. Because of the high-reliability requirement of this crane, a design scheme of distributed control system based on CAN bus in huge crane is proposed. The author mainly introduces the composition and realization of the system, the design of data communications, and the design of monitoring and controlling function of host computer. This system can achieve coordinated distributed control in the actions of hosting, luffing, slewing, machine leveling, and tower head leveling of the crane. It can also collect and monitor the status information of the crane in real time.

In view of the problem of the operational risk on distribution center, a technical framework of logistics equipments that adapted to the risk-based maintenance decision making is proposed. The frame includes three modules: risk analysis, risk evaluation, and risk control. The reliability of equipment and consequence of malfunction are considered. The risk is quantitatively analyzed, by which maintenance strategy is built for decision objective, so that we can build the management system of logistics equipment. An instance is taken to explain how to use the risk-based maintenance decision technique to logistics equipment.

Aiming at increasing the precision of tunnel settlement prediction, a modified support vector machine (SVM) based on the dynamic on-line sliding window (Dolsw) technique is proposed. In the prediction model, the historically observational settlement data act as the learning samples. The nonlinear relationship between settlement data and influencing variables is established on the basis of on-line learning SVM. In addition, the number of the samples is controlled withdynamic sliding window technique for improving its effectiveness. Finally, the new method can be used to predict the testing samples. Experimental resultsshow that this method can effectively provide reliable predictions with higher precision and greater generalization. Also, it can prevent the over fitting phenomenon. Keywords—tunnel settlement; support vector machine; sliding window; prediction

Some adverse conditions exist in the high-speed railway tunnel lining, such as lining insufficient thickness, lining cavity, unreasonable steel reinforcement layout, etc. In this paper, simulation of the typical adverse lining condition was implemented by using the simulation software GPRMax2D. The analysis of the typical radar images based on detection examples of a high-speed railway tunnel was described, and the summary of the features and rules of the adverse lining conditions was introduced in order to improve ground-penetrating radar data feature library, which provides the effective basis for the highspeed railway tunnel non-destructive testing.

The course Automatic Control Theory is a fundamental subject for machinery design, manufacturing and automation students of bachelor degree programs in College of Mechanical Engineering, Tongji University. The course construction under the framework of Tongji’s “Excellent Talent Program” has been proposed revolving around teaching content adjustment, teaching methods improving, bilingual teaching developing, and staff construction. This paper discusses the course content adjustment focused on typical theories and widely used engineering techniques. Teaching methods improving faces to the problem of quite diversified student population in university today and present some active methods such as problem-based teaching to improve the students’ ability of independent analysis and solving problems. About 5 years bilingual teaching experience of this course shows that suitable textbook, student-based teaching method and small scale class will benefit the teaching effect. The course Automatic Control Theory is developing to satisfy the demands of advanced engineering education.

The micro-electro-mechanical systems (MEMS) technology has broadened the horizon for sensors design, and MEMS devices, such as sensors and actuators, with low manufacturing cost, compact size, low weight and power consumption, are widely used in many industrial fields. A new type of MEMS accelerometer designed for the application in civil engineering is introduced in this paper. The some characteristics parameters of the sensor, such as reliable response frequency range and cross-axis sensitivity ratio, are tested through the calibration experiments designed in the paper, with the consideration based on application fields of the accelerometer.

1. Introduction High temperature (HT) operation at 800 – 1000 °C causes many problems such as the thermal mismatch between membrane electrode assembly (MEA) components, expensive bipolar plates, micro structural changes, inter-diffusions, slow start-up time, decreasing system power density due to heat insulators. In order to overcome this main commercialization obstacle of solid oxide fuel cells (SOFCs), a lot of intermediate temperature (IT) electrolyte materials (Doped ceria, LSGM, ScSZ and so on) which can substitute for conventional YSZ have been proposed. And various thin film deposition techniques (Screen printing, Dip-coating, Magnetron sputtering, Pulsed Laser Deposition, Chemical Vapor Deposition and Atomic Layer Deposition) were applied to this research field. The goal of both types of approaches is minimizing the ionic resistance at decreased temperature. Recently, the sodium doped strontium silicate (Sr1-xNaxSiO3-0.5x) is gathering attentions as a fast ion conductor.[1] And Wei et al. confirmed a good SOFC performance using this electrolyte material at 500 and 600 °C. [2] In this study, we investigated on this promising material to get the optimal fabrication conditions with composition and to minimize several problems on this material. 2. Experimental The starting raw powders of SrCO3 (Sigma-Aldrich 99.9%), Na2CO3 (Alfa Aesar, 99.9%) and SiO2(Alfa Aesar 99.9%) were mixed and ball milled. The Na doping percentages on strontium site were 0 to 100 %. We varied calcination temperature from 600 °C to 1000 °C. After ball milling step, we also varied sintering temperature (800 – 1150 °C) and time (10, 20 and 100 h). Conductivity tests were conducted in the air environment and the furnace was controlled from 400 to 750 °C. Sample pellet was prepared to get the thickness of 1.5 mm using low speed saw. Then, we pasted silver electrodes with current collecting meshes on both sides of pellets and connected wires to electrochemical impedance spectrometer (Solartron 1287 and 1260, UK). The micro structural images were captured using a field emission scanning electron microscope (FESEM, Zeiss Ultra) equipped with an energy dispersive X-ray spectroscopy (EDS) analyzer, respectively. The phase check was done using an X-ray diffractometer (D/max-A, Rigaku, Japan) with CuKα radiation (λ=1.5418 Å). The scan range was 2θ = 10 – 70 °at a rate of 5 ° min-1. From this study, we found out the optimal fabrication conditions (sintering at 900 °C for 10 h) for 45 % sodium doped strontium silicate electrolyte which was known as the best ionic conductor. Moreover, we could guess the origin of this high conductivity was from the amorphous sodium silicate. Reference [1] P. Singh and J. B. Goodenough, J. Am. Chem. Soc., 2013, 135, 10149–10154 [2] T. Wei, P.Singh, Y. Gong, J.B. Goodenough, Y. Huang and K. Huang, Energy Environ. Sci., 2014, 7, 1680-1684 Figure 1