Reliability-based maintenance optimization under imperfect predictive maintenance

The reliability-based maintenance optimization model has been focused by the engineers and scholars but it has never been solved effectively to formulate the effect of a maintenance action on the optimization model.In existing works,the system reliability was assumed to be increased to 1 after a predictive maintenance.However,it is very difficult in the most practical systems.Therefore,a new reliability-based maintenance optimization model under imperfect predictive maintenance (PM) is proposed in this paper.In the model,the system reliability is only restored to Ri (0相似文献   

New optimization method, the algorithms of changes, for heat exchanger design

Heat exchangers are widely used in the process engineering such as the chemical industries,the petroleum industries,and the HVAC applications etc.An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption.In this paper,a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger.This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts.In AOC,the hexagram operations in I Ching are generalized to binary string case and an iterative process,which imitates the I Ching inference,is defined.Before applying the AOC to the heat exchanger design problem,the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP).Based on the TSP results,the AOC is shown to be superior to the genetic algorithms (GA).The AOC is then used in the optimal design of heat exchanger.The shell inside diameter,tube outside diameter,and baffles spacing are treated as the design (or optimized) variables.The cost of the heat exchanger is arranged as the objective function.For the heat exchanger design problem,the results show that the AOC is comparable to the GA method.Both methods can find the optimal solution in a short period of time.     

Nonparametric control scheme for monitoring phase II nonlinear profiles with varied argument values

Profile monitoring is used to check the stability of the quality of a product over time when the product quality is best represented by a function at each time point.However,most previous monitoring approaches have not considered that the argument values may vary from profile to profile,which is common in practice.A novel nonparametric control scheme based on profile error is proposed for monitoring nonlinear profiles with varied argument values.The proposed scheme uses the metrics of profile error as the statistics to construct the control charts.More details about the design of this nonparametric scheme are also discussed.The monitoring performance of the combined control scheme is compared with that of alternative nonparametric methods via simulation.Simulation studies show that the combined scheme is effective in detecting parameter error and is sensitive to small shifts in the process.In addition,due to the properties of the charting statistics,the out-of-control signal can provide diagnostic information for the users.Finally,the implementation steps of the proposed monitoring scheme are given and applied for monitoring the blade manufacturing process.With the application in blade manufacturing of aircraft engines,the proposed nonparametric control scheme is effective,interpretable,and easy to apply.     

Multi-parameter Sensitivity Analysis and Application Research in the Robust Optimization Design for Complex Nonlinear System

The current research of complex nonlinear system robust optimization mainly focuses on the features of design parameters, such as probability density functions, boundary conditions, etc. After parameters study, high-dimensional curve or robust control design is used to find an accurate robust solution. However, there may exist complex interaction between parameters and practical engineering system. With the increase of the number of parameters, it is getting hard to determine high-dimensional curves and robust control methods, thus it’s difficult to get the robust design solutions. In this paper, a method of global sensitivity analysis based on divided variables in groups is proposed. By making relevant variables in one group and keeping each other independent among sets of variables, global sensitivity analysis is conducted in grouped variables and the importance of parameters is evaluated by calculating the contribution value of each parameter to the total variance of system response. By ranking the importance of input parameters, relatively important parameters are chosen to conduct robust design analysis of the system. By applying this method to the robust optimization design of a real complex nonlinear system-a vehicle occupant restraint system with multi-parameter, good solution is gained and the response variance of the objective function is reduced to 0.01, which indicates that the robustness of the occupant restraint system is improved in a great degree and the method is effective and valuable for the robust design of complex nonlinear system. This research proposes a new method which can be used to obtain solutions for complex nonlinear system robust design.     

Product modular design incorporating preventive maintenance issues

Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.     

RESEARCH ON MECHANICAL MEASUREMENT-ORIENTED INTELLIGENT VIRTUAL CONTROLS

Intelligent virtual control (IVC) is an intelligent measurement instrument unit with the function of actual measurement instruments, and the unit can be used as basic building block for a variety of more complex virtual measurement instruments on a PC. IVC is a further advancement from virtual instrument (Ⅵ), and it fuses the function modules and the controls modules so that the relationship between the functions and controls of an instrument is imbedded in one or more units. The design, implementation and optimization methods of IVCs are introduced. The computer software representation of IVCs is discussed. An example of an actual Ⅵ constructed with the building blocks of IVCs is given.     

KEY TECHNIQUES IN R＆D OF OUT-SIZE EXTRUSION PRESS WITH OIL-DRIVEN DOUBLE ACTION

A modern design method,in which traditional design formulas are conjoined with numerical simulation and optimization,is successfully used to design the out-size extrusion frame precisely so that the press cost can be saved. A new technology used for decompressing by a multi-steps dynamical mode is put forward,which makes it possible to decompress the large flow-volume high-pressure oil in the main cylinders. In addition,a method for realizing the fixed mandrel process by hydraulic support is proposed and its control equation is established. Pre-tightening frame tests are carried out by over-operating pressure on 100 MN aluminium extrusion press with oil-driven double action,which is developed based on the above key techniques and is the largest press so far in the world,and the results show that the frame structure designed is reasonable and reliable,and the modern design method used is an useful tool for designing large and out-size heavy plastic forming machinery. The results of decompressing curve in main cylinder and noise inspection indicate that multi-steps dynamical mode for decompressing the large flow-volume high pressure oil is valid and reliable. Meanwhile,the fixed mandrel process is well realized based on the control equation. These key techniques have been used in the development of 125 MN aluminium extrusion press with oil-driven double action.     

Integrated power and single axis attitude control system with two flywheels

The existing research of the integrated power and attitude control system(IPACS) in satellites mainly focuses on the IPACS concept,which aims at solving the coupled problem between the attitude control and power tracking.In the IPACS,the configuration design of IPACS is usually not considered,and the coupled problem between two flywheels during the attitude control and energy storage has not been resolved.In this paper,an integrated power and single axis attitude control system using two counter rotating magnetically suspended flywheels mounted to an air table is designed.The control method of power and attitude control using flywheel is investigated and the coupling problem between energy storage and attitude control is resolved.A computer simulation of an integrated power and single axis attitude control system with two flywheels is performed,which consists of two counter rotating magnetically suspended flywheels mounted to an air rotary table.Both DC bus and a single axis attitude are the regulation goals.An attitude & DC bus coordinator is put forward to separate DC bus regulation and attitude control problems.The simulation results of DC bus regulation and attitude control are presented respectively with a DC bus regulator and a simple PD attitude controller.The simulation results demonstrate that it is possible to integrate power and attitude control simultaneously for satellite using flywheels.The proposed research provides theory basis for design of the IPACS.     

Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.     

Adaptive Optimal Control of a Heavy Lathe Operation

To create control laws of the cutting process on the heavy lathe, the temperature-force model of optimization of cutting conditions for turning was selected. The models to manage the process of cutting on heavy lathe in real time were created. It was found that the optimization of the cutting process must be carried out according to the criteria： productivity, cost and tool life. The hardware structure of the adaptive control system for heavy lathe was developed and its dynamic performance was investigated. The system provides function of the cutting speed of adaptive control and the possibility of compensation of linear, nonlinear and temperature-related inaccuracies. Research results were implemented in the prototype of adaptive control system for heavy lathe and the integral complex of optimal control of an adaptive technological system.     

Optimization on the impeller of a low-specific-speed centrifugal pump for hydraulic performance improvement

In order to widen the high-efficiency operating range of a low-specific-speed centrifugal pump, an optimization process for considering efficiencies under 1.0Q_d and 1.4Q_d is proposed. Three parameters, namely, the blade outlet width b_2, blade outlet angle β_2, and blade wrap angle φ, are selected as design variables. Impellers are generated using the optimal Latin hypercube sampling method. The pump efficiencies are calculated using the software CFX 14.5 at two operating points selected as objectives. Surrogate models are also constructed to analyze the relationship between the objectives and the design variables. Finally, the particle swarm optimization algorithm is applied to calculate the surrogate model to determine the best combination of the impeller parameters. The results show that the performance curve predicted by numerical simulation has a good agreement with the experimental results. Compared with the efficiencies of the original impeller, the hydraulic efficiencies of the optimized impeller are increased by 4.18% and 0.62% under 1.0Q_d and 1.4Q_d, respectively. The comparison of inner flow between the original pump and optimized one illustrates the improvement of performance. The optimization process can provide a useful reference on performance improvement of other pumps, even on reduction of pressure fluctuations.     

Antiskid control of railway train braking based on adhesion creep behavior

In modern trains wheelset skidding leads to the deterioration of braking behavior,the degradation of comfort,as well as a boost in system hazards.Because of the nonlinearity and unknown characteristics of wheelset adhesion,simplifications are widely adopted in the modeling process of conventional antiskid controllers.Therefore,conventional antiskid controllers usually cannot perform satisfactorily.In this paper,systematic computer simulation and field tests for railway antiskid control system are introduced.The operating principal of antiskid control system is explained,which is fundamental to the simulation of antiskid brakes,and the simulation model is introduced,which incorporates both the adhesion creep curve and a pneumatic submodel of antiskid control system.In addition,the characteristics of adhesion curves and the simulation target are also provided.Using DHSplus,the pneumatic submodel is created to analyze the performance of the different control strategies of antiskid valves.Then the system simulation is realized by combining the kinematical characteristics of railway trains and the pneumatic submodel.The simulation is performed iteratively to obtain the optimized design of the antiskid control system.The design result is incorporated in the hardware design of the antiskid control system and is evaluated in the field tests in Shanghai Subway Line 1.Judging by the antiskid efficiency,the antiskid braking performance observed in the field tests shows the superiority of the optimized design.Therefore,the proposed simulation method,especially in view of its ease of application,appears to be a useful one for designing railway antiskid control systems.     

Design to conditioning circuits of dynamic compensation of reactive power in the intelligence voltage controller

<正>The paper introduces one design idea that making use of SCM to control Real-timely the dynamic compensation of reactive power.Firstly,design one Circuit to Sample the voltage and current,and by these datas we can easily calculate the power factor,and Voltage controller in the microcontroller to determine whether input the compensation capacitance according to the size of power factor,the paper also analyzes the principle of capacitance compensation and calculation method. Dynamic compensation for the entire process is quick and accurate.     

Intelligent Optimization Methods for the Design of an Overhead Travelling Crane

In design optimization of crane metal structures, present approaches are based on simple models and mixed variables, which are difficult to use in practice and usually lead to failure of optimized results for rounding variables. Crane metal structure optimal design(CMSOD) belongs to a constrained nonlinear optimization problem with discrete variables. A novel algorithm combining ant colony algorithm with a mutation-based local search(ACAM) is developed and used for a real CMSOD for the first time. In the algorithm model, the encoded mode of continuous array elements is introduced. This not only avoids the need to round optimization design variables during mixed variable optimization, but also facilitates the construction of heuristic information, and the storage and update of the ant colony pheromone. Together with the proposed ACAM, a genetic algorithm(GA) and particle swarm optimization(PSO) are used to optimize the metal structure of a crane. The optimization results show that the convergence speed of ACAM is approximately 20% of that of the GA and around 11% of that of the PSO. The objective function value given by ACAM is 22.23% less than the practical design value, a reduction of 16.42% over the GA and 3.27% over the PSO. The developed ACAM is an effective intelligent method for CMSOD and superior to other methods.     

Control Design for Harmonic Disturbance Rejection for Robot Manipulators with Bounded Inputs

Currently most of control methods are of one degree of freedom(1-DOF) control structure for the robot systems which are affected by unmeasurable harmonic disturbances,at the same time in order to obtain perfect disturbance attenuation level,the controller gain must be increased.In practice,however,for robotic actuators,there are physical constraints that limit the amplitude of the available torques.This paper considers the problem of tracking control under input constraints for robot manipulators which are affected by unmeasurable harmonic disturbances.A new control scheme is proposed for the problem,which is composed of a parameter-dependent nonlinear observer and a tracking controller.The parameter-dependent nonlinear observer,designed based on the internal model principle,can achieve an estimation and compensation of a class of harmonic disturbances with unknown frequencies.The tracking controller,designed via adaptive control techniques,can make the systems asymptotically track the desired trajectories.In the control design,the continuous piecewise differentiable increasing function is used to limit control input amplitude,such that the control input saturation is avoided.The Lyapunov stability of closed loop systems is analyzed.To validate proposed control scheme,simulation results are provided for a two link horizontal robot manipulator.The simulation results show that the proposed control scheme ensures asymptotic tracking in presence of an uncertain external disturbance acting on the system.An important feature of the methodology consists of the fact that the designed controller is of 2-DOF control structure,namely,it has the ability to overcome the conflict between controller gain and robustness against external disturbances in the traditional 1 -DOF control structure framework.     

Vehicle active steering control research based on two-DOF robust internal model control

Because of vehicle’s external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.     

Metamodel-based global optimization using fuzzy clustering for design space reduction

High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strat     

Optimization of the dressing parameters in cylindrical grinding based on a generalized utility function

The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type АС32 and АС80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions(dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility function has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing parameters.     

Effect of honeycomb seals on loss characteristics in shroud cavities of an axial turbine

The loss in efficiency due to shroud leakage or tip clearance flow accounts for a substantial part of the overall losses in turbomachinery.It is important to identify the leakage loss characteristics in order to optimize turbomachinery.At present,little information is available in the open literature concerning the effect of honeycomb seals on the loss characteristics in shroud cavities of an axial turbine,despite of the widespread use of the honeycomb seals.Therefore,interaction between rotor labyrinth seal leakage flow with and without honeycomb facings and main flow is investigated to provide the loss characteristics of the mixing process of the re-entering leakage flow into the main flow.The effects of honeycomb seals on the flow in shroud cavities and interaction with the main flow are analyzed.An additional study on the impact of subtle shroud cavity exit geometry is also presented.The investigation results indicate that the honeycomb seal affects the over tip leakage flow and reduces mixing losses when compared to the solid labyrinth seal.The leakage flow interactions with the main flow have considerably changed the flow fields in the endwall regions.The proposed research reveals the effects of honeycomb seals on the loss characteristics in shroud cavities and the impact of subtle shroud cavity exit geometry,and it is helpful for the design optimization of turbomachinery.