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Industrial robots are widely used in various industrial fields, such as handling and welding, due to their good repeat positioning accuracy. The motion error determines the absolute accuracy. For robot design, dimensional parameter errors and drive parameter errors, a mathematical model of a kinematic exponential product with error screws was proposed. The influence of different rod lengths and transmission errors on the accuracy of the end motion was analysed. A composite analysis method based on screw theory and vector method is proposed for the spatial deflection error of robot rotating joints with clearance. By using screw theory, a mathematical error model of the axial movement and spatial deflection of the joint gap was established. A mathematical model of joint space radial movement was established by using the three-dimensional vector method. Through numerical simulation, the position distribution law of the random error of the robot terminal in the workspace and the distribution of the plane projection density were obtained. By solving the attitude matrix, the distribution of each Euler angle error was obtained. A simulation test was carried out to verify the model's correctness. The calculation showed that the method is simple and correct, and the obtained error distribution characteristics are of great significance to improving robotic kinematic calibration accuracy and optimising the spatial position error distribution.

High-speed trains have a large amount of ancillary equipment, which is suspended from the underside of the train by means of a suspension structure. Due to the large mass of the ancillary equipment, the suspension structure is subjected to various loads during train operation and there is a risk of fatigue failure. In this paper, the stress distribution at the suspension point and the lo-cation of the maximum stress point under load are investigated in detail based on actual test loads at the suspension point and finite element simulation analysis. In order to further investigate the fracture failure of the suspension points, experimental studies were carried out. Firstly, static strength tests were carried out to obtain the load–displacement curves of the structural members and to determine the fracture strength of the structure based on the displacement sensors, and secondly, fatigue tests at different stress levels were carried out to obtain the load–life curves of the structural members and to investigate the probabilistic load–life curves at different reliability levels. The test results show that the structural component has a high fracture strength of 65kN, while the conditional fatigue strength is relatively low, corresponding to a load level of 12.5kN at a median life of 106 cycles. The above research work provides the necessary basis for the design, optimization and reliability assessment of the suspension structures of high-speed trains.

The compressor blade-disk system of an aero-engine is a complicated system with numerous components, and the failures of components are related. To evaluate its reliability accurately and efficiently, a fatigue reliability assessment method to handle the issues with failure dependency between components was proposed. Firstly, the finite element analysis was carried out considering the dispersion of load and material; secondly, the probabilistic distributions of stress, strain, and fatigue life of components were fitted by the response surface method; finally, the multi-component failure-dependent reliability model (MCFDM) of the compressor blade-disk system was established based on the dependent failure system reliability theory. Based on this model, the fatigue life of the blade-disk system at varying reliability levels and the reliability and failure probability at varying specified life levels were calculated. The results of MCFDM are compared with those of the independent failure reliability assessment model(IFM) and the traditional Monte Carlo method(MCM). It is demonstrated that the system reliability calculated by IFM is too optimistic, while MCM requires a large number of samples based on the finite element model directly. In comparison, MCFDM can offer results with sufficient accuracy and higher efficiency.

In order to realize the high-quality work requirements of welding robots, based on the actual working conditions, the seven-degree-of-freedom series welding robot is taken as the research object, we design and determine the relevant technical parameters of it, and establish the kinematics model in D-H coordinate system. The micro-displacement synthesis method is introduced, and the static pose error model and reliability calculation model of the robot are established. The influencing factors of the accuracy of the welding robot's pose accuracy are analyzed and the sensitivity of the influencing factors was obtained. Finally, based on Monte-Carlo simulation method, the link parameters of the welding robot are taken as an example to verify the reliability of the position and accuracy of the welding robot, and the relevant results are obtained. The work in this paper is of some guiding significance in reliability design and assessment of a welding robot.

Escalators are now more and more widely used around the world. As escalator accidents occur from time to time, it is very important to analyze the structure and reliability of escalators. This paper studies the structure and reliability analysis methods of typical escalators. By applying parametric analysis methods, the efficiency and accuracy of escalator structure analysis are greatly improved. Because the failure of each structural member of the escalator truss system is dependent, this paper applies the dependent failure reliability modeling method and analyzes the reliability of the escalator truss system. The results show that the reliability analysis method of the truss system after considering the dependent failure is more reasonable. The above research work has certain reference significance for the design and analysis of escalators.

High-speed trains are now the most important medium- and long-distance mode of transport in many countries, and green economy is one of the important directions of high-speed train design. Aluminum alloy material is widely used in various structural parts of high-speed trains due to its advantages of high strength and low density, etc. As the speed of high-speed trains is getting faster and faster, the load on the car body structure is getting bigger and bigger, the safety, reliability and longevity of aluminum alloy structure has received wide attention. In this paper, the stress distribution, maximum stress value and maximum stress point position of aluminum alloy structural members of high-speed trains are analyzed in detail based on the real load situation, and the influence of stress level on train operation is analysed. The above work has certain reference significance for the design of high-speed train.

Based on the failure trajectory concept and backwards statistical inference technique, experimental programs are designed to fit P–S–N curve with a small number of test data. Underlying the program is a method to convert fatigue lives tested at different cyclic stress levels into the equivalent lives at an arbitrary stress level, by which a relatively large size sample is established. The basic justification is that the probability distribution of the equivalent lives is identical to that of the real life distribution at the same stress level, only if the conversion is based on the correct life distribution – stress relationship. Consequently, parameters characterizing P–S–N equation can be acquired through a process to search reasonable life distribution – stress level relationship, by means of statistically testing the difference between equivalent life distribution and the real life distribution, that is either obtained by a large size sample of fatigue life test data or reasonably provided.

A new method based on Dynamic Bayesian Network (DBN) is proposed to assess the car engine reliability because of the limitation that the existing reliability analysis methods can only be used in static system reliability assessment. Firstly, define the failure mode and effect analysis table (FMEA) and the failure rates of the main components of the car engine and construct Bayesian network (BN) model. Secondly, combine the original BN model with time information and assess the reliability of the systems by using the advantages of BN in terms of the multi-state variables and uncertainly relations. The method is able not only to compute the reliability indices of car engine but also to carry out the fault detection easily to recognize the weakness of the system. This research is meaningful for reliability design and prediction of car engine.

Fatigue life corresponding to specific failure probability is much more significant than mean life, since fatigue fracture is a highly uncertain phenomenon. For a complex structural component with several damage sites, the contributions of the every damage site are stochastic in nature. Moreover, the damages or fatigue lives of the individual vulnerable sites are neither completely correlated nor perfectly independent of each other. The present paper develops a probabilistic fatigue life evaluation approach to predict the probabilistic fatigue life of complex mechanical or structural components containing multiple damage sites. By correctly dealing with the failure dependence of the every damage sites and characterizing the fatigue life random variable of a multi-site-damage (MSD) structure or component using the extreme statistic of the fatigue lives of the individual damage sites, probabilistic fatigue life of MSD structural component is reasonably predicted.

Aluminum alloy structural hangers are widely used in subway vehicle. The advantage of aluminum alloy is light weight and corrosion resistance. For different application fields, the structures of aluminum alloy components are very different. They are typically lighter for the same strength and provide better heat conduction. As we know that do FEA (finite element analysis) is necessary before and after the alloy structures have been made. In this paper, a detail analysis was done with FEM (finite element method), and the stress distribution of alloy structural hanger was obtained. Also the FEA results show that the maximum stress is less than the yield stress and the stress concentration of the slot is relatively high.

Hexagon socket head bolts are widely used in many engineering fields as fasteners and are common and important parts for engineering, but for some hexagon socket head bolts it is still tedious to build the 3D models and assess their reliability. It is important for a hexagon socket head bolt to do reliability assessment, especially for some hexagon socket head bolt that under complex load conditions. In order to improve the reliability and stabilization, a hexagon socket head bolt reliability assessment method is introduced and an example is given, and the example shows that do reliability assessment is useful and effective.

Bolt joints are widely used in all kinds of machines. The advantage of them is cheap and convenience. For different application fields, the structures of bolts are very different. They are typically lighter for the same strength and provide better heat conduction. As we know that do FEA (finite element analysis) is necessary before and after the bolts have been made. In this paper, a detail analysis was done with FEM (finite element method), and the stress distribution of bolt joint was obtained. Also the FEA results show that the maximum stress is less than the yield stress and the stress concentration of the thread is relatively high.

A gear transmission system such as a gear train is a series system in sense of reliability evaluation, while it is different from a traditional series system such as a chain. Therefore, the conventional series system reliability model is not appropriate for gear transmission system. Based on the time-dependent configuration and the time-dependent loading path of a gear train, system specific reliability modeling technique is presented, by which a gear train is taken as a time-dependent series system, consisting of different components (gear teeth) in different time intervals. To illustrate the application of the reliability analysis method, several time-dependent series system reliability models are developed for different types of gear trains, the reliability estimation results are compared with those obtained by traditional series system reliability model.

The propulsion system, comprising four hydraulic cylinders, is an important power supply assembly in tunnel boring machine, and fatigue is the major failure modes to concern for the hydraulic cylinders. To evaluate the reliability of the propulsion system, i.e. the hydraulic cylinder assembly, a reliability model capable of completely reflecting the effects of stochastic load environment and material property degradation is required. For such a purpose, this paper presents a method to describe the uncertainty of random load history at two levels, i.e. the macro-level characterizing the variation in the whole load history intensity over individual load historys, and the micro-level describing the fluctuation of load peaks inside one load history. Starting from random load history expression, a multi-layer, multi-variate dynamic (time-dependent) reliability model is developed through system-level load-strength interference analysis. By the multi-layer configuration, the model hierarchically expresses the role of the uncertainty in the intensity of load history, the randomness in load peaks within a specific load history, the uncertainty of load action number, and the uncertainty of component strength. By utilizing discrete time variable (i.e. load action number), product property degrading with load cycles can be exactly incorporated in failure criterion. The model, taking on either the form of multi-layer integral or the form of multilayer summation, can synthetically reflect the effects of the uncertainty of random load environment including statistical risk over operation period, the dependence among component failures, the uncertainty of load action number in a specified time interval, the uncertainty of material strength and its deteriorating path. Besides, this model incorporates both fatigue criterion and ultimate tensile failure criterion uniformally, and is applicable to both mechanical component and series system. Since no assumption on the independence between component failures, the reliability model can naturally reflect the effect of failure dependence, and the (conditional) probability distributions of the individual variates involved in the models can be easily determined.

Reliability concepts, models and methods have been developed in different fields and applied to a variety of engineering cases from component, system to process. Besides the great amount of successive applications, challenges are everywhere including the understanding to the role of random load environment, especially its uncertainty in reliability estimation and experiment, the mechanism to produce the bathtub type failure rate curve, the modeling of component/system reliability under complex load environment and with multiple failure modes, and so on. Focused in the present paper are general load-strength interaction analysis method and related failure rate modeling approach, statistical dependence among component failures, characterization and expression of the statistical property of random load environment, and the incorporation of the factors describing time, space and failure mechanism to develop comprehensive reliability models capable of reflecting stochastic load environment and material degradation behavior.

Electronic systems are widely used in many engineer and civil fields, such as aviation, energy, communication, military and automatic etc. Usually the more the components that a system includes the poorer the system reliability is. But the failures of components are usually dependent. In this paper, a reliability model of dependent failure of electronic system is built and the influences of strength decentrality and load decentrality is discussed. The results of two examples prove the validity and superiority of the method in the application of the reliability modeling and assessment of system and the model that considered failure dependent is more reasonable than those conventional reliability models.

Acoustic emission(AE) of material is a common phenomenon; In fact, it has relation with the material states. In this paper, the acoustic emission test method is used and the characteristics of different phases of aluminum alloy cracks are analyzed. Artificial neural network(ANN) is used to recognize the pattern of AE of fatigue cracks. Practical test shows the above method could test the cracks that common method could not test. The result of pattern recognition is rather accurate, and is of practical engineering significance.

The plate specimen tensile test is a common material mechanical property test in practical engineering, but the gripping deviation of plate specimen will bring tensile test result an error. In this paper, a finite element model of aluminum alloy notched specimen is built and a static finite element analysis is carried on, the influence of the plate specimen tensile test gripping position deviation rightness of experiment to the test result is studied. The result expresses that the gripping deviation of plate specimen will bring tensile test result an error bigger. It is necessary to raise the accuracy request of the gripping position of plate specimen tensile test.

Fitting P-S-N curve with small-size sample of fatigue test data is significant in engineering applications. Although several small sample-based P-S-N curve fitting methods have been developed, complexity in mathematics and/or the unrealistic assumption of the methods hinder their application seriously. Based on the principle of probabilistically mapping from the probability distribution of specimen property to that of fatigue life of the specimen, this paper presents a new, easy to apply P-S-N curve fitting method. By collecting the life distribution information dispersed in several small-size samples of fatigue lives tested under different cyclic stress levels, a large-size sample of equivalent fatigue life data can be built based on the mapping mechanism as well as the uniqueness of the relationship between fatigue life standard deviation and cyclic stress level. The basic viewpoint is that the fatigue lives tested at any cyclic stress levels can be equivalently converted to an arbitrary baseline stress level according to the life distribution–stress relationship, and this principle can be applied to determine the P-S-N curves with a limited number of test data. Test results illustrate that the P-S-N curves obtained by such methods with 30, 24 or 20 samples, respectively, are close to those obtained by the conventional test method with 60 or 40 samples.