High-speed cam mechanism is widely used in vehicles, textile machinery, printing machinery etc. The research of dynamic analysis is the basis and key point to improve the mechanical properties. Discretization of the flexible elements of cam mechanism is carried out by means of finite-element method. Furthermore, the dynamic model of the rigid-flexible coupled cam mechanism is proposed based on modal synthesis technique and Kane’s equations. The dynamic equation obtained is more general for flexible beam type, and very convenient for solving by computer because it is a modal-coordinates dynamic equation. The system dynamic performance is studied by analyzing the system modal and solving the dynamic equation. The simulation of dynamics model which has different orders is carried on, which can not only ensure accuracy of calculation but also save computational resources. Research results have important guiding significance for determining whether the dynamic analysis of high-speed cam systems in practical application is required, and furthermore, research results can provide strong guide for dynamic modeling and modal characteristics research of similar mechanism.

Acoustical guided waves modal analysis in rail is the basis of long distance guided wave inspection and rail vibration and noises control. In particular the various propagating guided waves in the rail are identified in terms of their propagation wavenumber coefficients and their corresponding deformed shapes. The semi-analytical finite element method is used to formulate the governing equation for guided waves propagating in elastic waveguides of arbitrary cross-section on the basis of the virtual work principle, wavenumber dispersion curves and deformed shapes are extracted by solving governing equation, which provide the basis for selecting mode and frequency during application. The propagating guided waves wavenumber dispersion curves and deformed shaped under 0-8 kHz frequency range for CHN60 type free rail are obtained using semi-analytical finite element method, and the characteristics of the eight based guided waves mode in rail are discussed. Instrumented hammer experimental study and modal analysis using sever vibration accelerometers mounted on rail are carried out to verify the vertically vibrating mode and horizontally vibrating mode guided waves wavenumber dispersion coefficient. Modeling and experimental investigations of lateral and vertical excitation in railhead shows that good agreement between numerical calculation and experiment.

Robotics in medical have made giant strides in past several decades with its widely use in various aspects. According to it’s function and usage, medical robots are classified into 7 types: neurosurgery robot, orthopedics robot, laparoscopic robot, vascular interventional robot, prosthetics and exoskeleton robot, assistive and rehabilitation robot and capsule robot. The functions, specifications, advantages and disadvantages of present typical commercially available medical robotics are surveyed. The current research foci, key technology and future trends of medical robotics are also discussed.

Drill pipe is a critical and vulnerable component in oil & gas industry. A novel feed-through alternating current field measurement (ACFM) is proposed to achieve in-service detection for axial cracks on the surface of drill pipe. The finite element model is built by ANSYS software for analyzing the induced electromagnetic field distribution and disturbance caused by the axial crack on the external surface of drill pipe. Signal features of the crack are extracted through quantitatively analyzing the relationship between the size of crack and disturbance field. On the basis of theory and FEM simulation, the feed-through ACFM system is set up and proved by the axial crack of drill pipe detection experiments. The results show that, the signal features of Bx and Bz from the feed-through ACFM system show the depth and length information of the axial crack respectively on pipe string, and the lift-off effect can meet the demands of in-service detection for drill pipe. Furthermore, the feed-through ACFM system with sensors array can detect all the axial cracks in-service with a single pass scanning.

Since the concept of compliant mechanisms (CMs) is firstly proposed in late 1980s, it develops rapidly and has become an important branch of modern mechanism community. In the past less than 30 years, dozens of design methodologies and theories for CMs have emerged, which lays a solid foundation on their successful use. With the increasing insight for flexures and CMs, more and more applications of CMs can be found in various fields. After summarizing and comparing the current design methods for flexure-based compliant mechanisms five years ago, the state-of-arts of CMs have been overviewed from the point of application in this paper. Most existing CMs are resorted to three categories, i.e. precision engineering, bionic robotics, and smart structures if considering the difference of their functions and application background. The successful uses, study focuses and even application prospects in each category of CMs are introduced case by case. Afterward, four new types of CMs with great potential applications, i.e. cellular CMs, contact aid CMs, lamina emergent mechanisms, and static balance CMs are illustrated in brief. We hope more scholars all over the world start to study these amazing CMs and industrial personnel pay more attention on the usage of CMs as well after getting the overview of CMs.

The platen superheater tube of a domestic flame boiler burst and leaked after one month operation. The burst causes of superheater tube were analyzed by means of macroscopic examination, chemical composition analysis, hardness test, metallographic examination, scanning electron microscope and energy spectrum analysis. The results show that long-time over temperature operation caused tube burst. Weld beadings inside the girth weld of superheater tube joint blocked the steam flow, and oxide skin impacted heat transfer, which caused partial wall overheating for a long time. Serious aging of microstructure and obvious creep damage of burst mouth reduced the strength of tube material, and the pressure bearing capacity of tube wall and finally led to burst and leakage of superheater tube.

In order to extract machinery fault characteristics that are submerged in strong background noise, a general singular value decomposition (SVD) based subspace noise reduction algorithm is applied to signal processing, i.e., μ-SVD based denoising method. It can be proved that the traditional SVD based denoising method is a special case of the μ-SVD based one where μ=0. μ-SVD based denoising method contains a filter factor that plays a role in restraining information contributions of the noise-domain singular values to the denoised signal. μ-SVD based denoising method involves five parameters, including delay time, embedding dimension, noise reduction order, noise power and Lagrange multiplier. The selection methods for these parameters are discussed. In particular, the effects of noise reduction order and Lagrange multiplier on denoising performance are also studied. The experimental results of simulation signal with local fault and vibration signal with early crack fault in gear demonstrate that the μ-SVD based denoising method is superior to the traditional one in denoising performance, and can more effectively extract the gear fault characteristics at the presence of strong background noise.

The major parameter estimation error source for discrete Fourier transform are spectrum leakage and picket fence effect. A weighted two points vector interpolation algorithm based on Rife-Vincent window for improving the estimation accuracy of parameters for the multi-frequency damped signals is presented, where the signals are weighted by M-order cosine window family before the discrete Fourier transform and the equations with nuknown of frequency deviation and decay factor is established by the ration of two adjacent spectral lines near the real frequency position. The frequencies, amplitudes and phases are calculated by the frequency deviation solved from the above equation. The cosine window family with the characteristic of maximum sidelobe decay can essentially remove the spectral leakage and two point vector interpolation will cope with the problem of the picket fence. To combine the merits of the above two method can effectively increase the accuracy. The simulation and test results show that the proposed algorithm has a higher estimate accuracy and steady estimates. The higher computational efficiency and lower memory demand are suggested especially for poor computing resource situations. It also can be used as an optional method for the features extraction of the multi-frequency damped signals.

Based on thermodynamics theory and finite element method, a finite element model of equipment and its airbag cushion system is established and verified experimentally. The simulation results are obtained under the same conditions of the airdrop test and the simulation results agree very well with the experimental results, which indicate the established model is valid for further research. Because nonlinear model of airbags cushion system is very complicated, the calculation takes tens of hours of CPU time. As a result, the large-scale calculation is impossible. In order to overcome this problem, surrogate models are employed instead of the complex finite element model based on extended latin hypercube method and radial basis function. Initial velocity, initial heeling angle, initial pitch angle, lateral velocity and gradient are variables, while maximum acceleration, maximum heeling angle, maximum pitch angle and maximum airbag pressure are responses. Considering the influence of landing condition, Monte Carlo method and surrogate model are used to calculate landing success probability of airdropping equipment under multi-condition. The landing success probability calculated is 95.84%. Acceleration is the primary contributor to cushion performance, while pressure inside airbag is secondary contributor.

Isogeometric analysis (IGA) is a novel numerical method for solving equations of physical fields, which is motivated by improving the integration between numerical simulations of physical phenomena and the computer-aided design tools, and provides a new way to associate product design with analysis and optimization via a common mathematical platform. The method of geometric modeling and its mathematical description are introduced in detail based on the computational framework of IGA. Taking NURBS as an example, the parametric representation in an analysis model and the mesh refinement method are analyzed, and the discretization methods, boundary conditions and quadrature in the parametric domain of IGA are discussed as well by comparing them with those in the standard finite element analysis. Applications of IGA in thermal analysis, fluid-structure interaction, contact problems and structural optimization are summarized and a simple example of 2D problem is provided.

A method for structural optimization design of wafer handling robot is presented. The static deformation of the end effector is employed as the constraint of the method. The nature frequencies of the rigid links flexible joints system are selected as the optimization objectives, and the thicknesses of the arms are determined as the optimization parameters. The dynamic model of the rigid links and flexible joints is established, and the modal analysis is carried out to determine the orders of the modal which will influence the trajectory precision. The masses of the second arm and the third arm are selected as the optimization parameters by the sensitive analysis of the nature frequencies. The deflection model of the arm is established with the variables of the thicknesses of the arm. The relationships between the thicknesses and the deformation of the end effector are analysed, and the structures of the arms are optimized based on the analysis. The comparison between the performance before optimization and the performance after optimization are carried out, and the result shows that the nature frequencies and the frequency of the vertical vibration are significantly enhanced and the deflection of the end effector is obviously reduced.

Recently, micro-nano coordinating measuring machine(CMM) has become a research focus in the field of three-dimensional(3D) micro-nano measurement. Due to the difficulty of the development of a 3D nano probe, a novel 3D resonant trigger probe has been proposed. This probe can reach nanometer/sub-nanometer resolution in three-dimensions, and its operation principle is different from the present contact probes and optical non-contact probes. The 3D nano resonant trigger probe is constructed by a piece of piezo-electrical PVDF film, two piezo-actuators, an integrated fiber micro-stem and micro-ball tip. The PVDF film vibrates at its resonant frequency and acts as a sensor. Using the piezoelectric property of PVDF film and the high sensitivity of its resonant parameters to the micro-force, the probe can give 3D trigger signal. The probe contacts the sample in traditional tapping-mode in z direction and friction-mode in both x and y directions. Experimental results show that the trigger resolution of 3D resonant trigger positioning system constructed by the above probe, 3D nano positioning unit, the feedback control module and the signal processing circuit could reach sub-nanometer resolution, which is 0.12 nm in x direction and 0.10 nm in y direction, while 0.12 nm in z direction. The 3D repeatability error is 26 nm, 36 nm and 10 nm respectively. The results demonstrate the validity of the new type of 3D nano resonant trigger probe and positioning system.

New energy vehicle(NEV) has been widely used around the world in response to the fossil energy crisis and environmental pollution problems. NEV will generate massive real-world data during its daily operating which is contributed by high electrification and intelligent networking. Applying these multi-source heterogeneous data for a security warning and technical analysis will play a key role in promoting the development of NEV industry in China. The current situation of data-driven analysis technology in the NEV field is reviewed. Firstly, the basic theory of big data analysis techniques are introduced and the development of big data technology is depicted. The structure and function of the National Monitoring and Management Platform for New Energy Vehicles are introduced, and the particular process of big data analysis on NEV is emphasized. The previous data-driven research and methods in power battery, NEV daily operation and charging behavior are proposed for discussion respectively. Some representative research results and applications are displayed at the same time. Finally, the issues and prospects of the data-driven method on NEV application field are summarized and forecasted.

How to transform from a big nation in manufacturing  to  a  powerful one is a great subject of China's  economic development in the new era.This paper discussed  the guiding ideology,strategic deployment,basic policy and strategic measure of “made in China 2025” based on detailed analyses of current manufacturing situations  of China,and indicated  that “Internet+advanced manufacturing+modern service industry” will become a new engine of China's economic development.It  is pointed  out that digitization,networking and  intellectualization of manufacturing industries  are the core technologies of  a new round industrial revolution, and should be used as commanding point,breakthrough and main direction of  “made in China 2025”.An overall thorough interpretation of above points was put forward.

Ultra-precision machining is essential method for obtaining the highest quality in terms of form accuracy, surface finish Ultra-precision machining is essential method for obtaining the highest quality in terms of form accuracy, surface finish and surface integrity. As the higher requirements of quality and diversifications for products are put forward, it is essential to improve the precision and efficiency of ultra-precision machining. Ultra-precision machining has become a complicated systems engineering, which involves more and more last research fruits. The conception, application fields, present research status, development tendency, and the key issues of future researches on scientific and technological f of ultra-precision machining are introduced in this paper. Some advanced and typical ultra-precision machine tools, ultra-precision cutting, grinding, and polishing are reviewed and compared in terms of machining accuracy, quality and efficiency. The main problems and miss distance from the advanced technologies of China in ultra-precision machining field are analyzed. In the same time, the probable further trend of ultra-precision machining is forecasted, and the developing countermeasure and strategy of fundamental research, technologies and industry in China are given.

With the development of science and technology as well as the advancement of production technology, contemporary equipment is increasingly developing towards large-scale, complex, automated and intelligent direction. In order to ensure the safety and reliability of equipment, the remaining useful life (RUL) prediction technology has received widespread attention and been widely used. Traditional statistical data-driven methods are obviously influenced by the choice of models. Machine learning has powerful data processing ability, and does not need exact physical models and prior knowledge of experts. Therefore, machine learning has a broad application prospect in the field of RUL prediction. In view of this, the RUL prediction methods based on machine learning are analyzed and expounded in detail. According to the depth of machine learning model structure, it is divided into shallow machine learning methods and deep learning methods. At the same time, the development branches and research status of each method are sorted out, and the corresponding advantages and disadvantages are summarized. Finally, the future research directions of RUL prediction methods based on machine learning are discussed.

Prognostics and health management (PHM) is crucial for ensuring the safe operation of machinery, improving the productivity and increasing economic benefits. High-quality life-cycle data, as the basic resource in the field of PHM, are able to carry the key information which reflects the complete degradation processes of machinery. However, due to the high costs in data acquisition and insufficient development in storage and transmission technology, typical life-cycle data is extremely scarce, which limits the theoretical research and engineering application of PHM for machinery. In order to solve this dilemma, accelerated life tests of rolling element bearings are carried out by Prof. Yaguo Lei's research group from School of Mechanical Engineering, Xi'an Jiaotong University (XJTU) and the Changxing Sumyoung Technology Co., Ltd. (SY), Zhejiang. These tests lasted for two years and the acquired datasets, i.e., XJTU-SY bearing datasets, have been publicly released for all PHM researchers. The XJTU-SY bearing datasets contain run-to-failure vibration signals of 15 rolling element bearings under three different operating conditions. These datasets have high sampling frequency, large amount of data, abundant failure types and detailed recording information. Accordingly, these datasets not only provide fresh "data blood" for PHM and promote the research of fault diagnosis and remaining useful life prediction, but also are able to help to improve intelligent maintenance decision making in industry.

The intelligent spindle possesses three major characteristics of processing state perception, decision-making and execution. It can realize self-feedback and self-control of machining status, which is the core component of intelligent manufacturing. It is the basic supporting technology for "Industrie 4.0" and "Made in China 2025" and the development direction for next-generation spindle technology. Condition monitoring, diagnosis and vibration control, as the typical embodiment of the three major functional features, are the core technologies for ensuring the efficient operation of intelligent spindles. Therefore, aiming at alleviating the problem of monitoring, diagnosis and vibration control of intelligent spindle, and with the monitoring, diagnosis and control of high-failure parts and failure modes as the clues, the current research status both at home and abroad is systematically summarized, the existing problems are concluded and the potential development trends are proposed.

As an important approach to realize MC and AM, modular product design can produce more variety of products with limited resources by combination of different modules. Such method is viewed as a goal of good design practice in current engineering. However, it is not received sufficient attention in the literature, and most solutions are proposed at an abstract level. The literature on modular product design focusing on definitions, methodologies, key technologies and its application is reviewed. Finally, some focused research issues on modular product design are formulated.

Since the beginning of this century,Chinese scientific and technical workers in the field of pres-sure vessels have solved many technical problems brought by production scale upsizing,harsh medium en-vironment and long-term safe operation of process industries,and established the technological methods of design,manufacturing and maintenance based on life-cycle risk control. Based on these achievements,the important pressure vessels in China are no longer depend on importation,and the failure rate per ten thou-sand sets of equipment is decreasing year by year. However,the problem of heavy-duty trend of pressure vessels due to scale upsizing of the process industry plants becomes increasingly prominent,which not only causes large material,energy and labor consumption,and makes processing and manufacturing difficult, but also there may exist certain safety risks. The lightweighting,green design and manufacturing of pres-sure vessels under the premise of ensuring their inherent safety,and the reduction of environmental pollu-tion caused by the failure of pressure vessels subjected to disasters,are two outstanding problems that need to be solved focally during China's "12^th Five-Year Plan" period. At the same time,in recent years,the rapid development of modern information technology,such as Internet of Things,big data etc. and artificial intelligence technology has brought unprecedented opportunities and challenges to the traditional technolo-gy of pressure vessels in China. Another important problem that Chinese pressure vessel technical workers began to explore and solve in the "12^th Five-Year Plan" period,is to deeply integrate with modern infor-mation and artificial intelligence technology so as to promote the development of Chinese pressure vessel technology toward the direction of digitalization,networking and intelligentization. This paper briefly re-views the progress of the green design,manufacturing and maintenance,network-based remote operation and maintenance technology of Chinese pressure vessels since the "12^th Five-Year Plan". In combination with the strategic requirements of " Made in China 2025",this paper also proposes some research sugges-tions during the "13^th Five-Year Plan" period and in the future,including the genome program of pressure vessel materials and additive manufacturing, network-based collaborative manufacturing and intelligent factory,intelligent operation and maintenance,etc.

With the development of robotics technology,industrial robots are widely used in automation production,which greatly improves the production efficiency and automation degree. Trajectory planning is the key link to complete the task,and trajectory optimization further improves the quality of mission completion and meets the needs of industrial development. The research progress of trajectory planning and optimization for joint space of industrial robots is reviewed. Firstly,the algorithm of joint space trajectory planning is briefly described. It is pointed out that polynomial interpolation is the main mode,and B-spline curve is an inevitable trend of future development due to its excellent characteristics. Then,the trajectory optimization under different objectives is comprehensively summarized,and the existing problems such as the determination of the optimization objectives and the improvement of the algorithm are pointed out. Finally,the future development direction is prospected. The multi-objective optimization solution and dynamic adjustment of constraints will be the focus of future research.