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QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

《结构与土木工程前沿（英文）》 2023年第17卷第1期页码 25-36 doi: 10.1007/s11709-022-0908-z

摘要： In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.

关键词： tunnel boring machine control parameter optimization quantum particle swarm optimization artificial neural network tunneling energy efficiency

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Processing parameter optimization of fiber laser beam welding using an ensemble of metamodels and MOABC

《机械工程前沿（英文）》 2022年第17卷第4期 doi: 10.1007/s11465-022-0703-5

摘要： In fiber laser beam welding (LBW), the selection of optimal processing parameters is challenging and plays a key role in improving the bead geometry and welding quality. This study proposes a multi-objective optimization framework by combining an ensemble of metamodels (EMs) with the multi-objective artificial bee colony algorithm (MOABC) to identify the optimal welding parameters. An inverse proportional weighting method that considers the leave-one-out prediction error is presented to construct EM, which incorporates the competitive strengths of three metamodels. EM constructs the correlation between processing parameters (laser power, welding speed, and distance defocus) and bead geometries (bead width, depth of penetration, neck width, and neck depth) with average errors of 10.95%, 7.04%, 7.63%, and 8.62%, respectively. On the basis of EM, MOABC is employed to approximate the Pareto front, and verification experiments show that the relative errors are less than 14.67%. Furthermore, the main effect and the interaction effect of processing parameters on bead geometries are studied. Results demonstrate that the proposed EM-MOABC is effective in guiding actual fiber LBW applications.

关键词： laser beam welding parameter optimization metamodel multi-objective

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1000 MW ultra-supercritical turbine steam parameter optimization

FENG Weizhong

《能源前沿（英文）》 2008年第2卷第2期页码 187-193 doi: 10.1007/s11708-008-0030-5

摘要： The 2 × 1000 MW ultra-supercritical steam turbine of Shanghai Waigaoqiao Phase III project, which uses grid frequency regulation and overload control through an overload valve, is manufactured by Shanghai Turbine Company using Siemens technology. Through optimization, the steam pressure is regarded as the criterion between constant pressure and sliding pressure operation. At high circulating water temperature, the turbine overload valve is kept closed when the unit load is lower than 1000 MW while at other circulating water temperatures the turbine can run in sliding pressure operation when the unit load is higher than 1000 MW and the pressure is lower than 27 MPa This increases the unit operation efficiency. The 3D bending technology in the critical piping helps to reduce the project investment and minimize the reheat system pressure drop which improves the unit operation efficiency and safety. By choosing lower circulating water design temperature and by setting the individual Boiler Feedwater Turbine condenser to reduce the exhaust steam flow and the heat load to the main condenser, the unit average back pressure and the terminal temperature difference are minimized. Therefore, the unit heat efficiency is increased.

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Energy efficient cutting parameter optimization

Xingzheng CHEN, Congbo LI, Ying TANG, Li LI, Hongcheng LI

《机械工程前沿（英文）》 2021年第16卷第2期页码 221-248 doi: 10.1007/s11465-020-0627-x

摘要： Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

关键词： energy efficiency cutting parameter optimization machining process

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Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

《机械工程前沿（英文）》 2021年第16卷第2期页码 393-409 doi: 10.1007/s11465-020-0613-3

摘要： As an important part of product design and manufacturing, assembly sequence planning (ASP) has a considerable impact on product quality and manufacturing costs. ASP is a typical NP-complete problem that requires effective methods to find the optimal or near-optimal assembly sequence. First, multiple assembly constraints and rules are incorporated into an assembly model. The assembly constraints and rules guarantee to obtain a reasonable assembly sequence. Second, an algorithm called SOS-ACO that combines symbiotic organisms search (SOS) and ant colony optimization (ACO) is proposed to calculate the optimal or near-optimal assembly sequence. Several of the ACO parameter values are given, and the remaining ones are adaptively optimized by SOS. Thus, the complexity of ACO parameter assignment is greatly reduced. Compared with the ACO algorithm, the hybrid SOS-ACO algorithm finds optimal or near-optimal assembly sequences in fewer iterations. SOS-ACO is also robust in identifying the best assembly sequence in nearly every experiment. Lastly, the performance of SOS-ACO when the given ACO parameters are changed is analyzed through experiments. Experimental results reveal that SOS-ACO has good adaptive capability to various values of given parameters and can achieve competitive solutions.

关键词： assembly sequence planning ant colony optimization symbiotic organisms search parameter optimization

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Optimization of power and efficiency for an irreversible Diesel heat engine

Shiyan ZHENG, Guoxing LIN

《能源前沿（英文）》 2010年第4卷第4期页码 560-565 doi: 10.1007/s11708-010-0018-9

摘要： A cyclic model of an irreversible Diesel heat engine is presented, in which the heat loss between the working fluid and the ambient during combustion, the irreversibility inside the cyclic working fluid resulting from friction, eddies flow, and other irreversible effects are taken into account. By using the thermodynamic analysis and optimal control theory methods, the analytical expressions of power output and efficiency of the Diesel heat engine are derived. Variations of the main performance parameters with the pressure ratio of the cycle are analyzed and calculated. The optimum operating region of the heat engine is determined. Moreover, the optimum criterion of some important parameters, such as the power output, efficiency, pressure ratio, and temperatures of the working fluid at the related state points are illustrated and discussed. The conclusions obtained in the present paper may provide some theoretical guidance for the optimal parameter design of a class of internal-combustion engines.

关键词： Diesel heat engine irreversibility power output efficiency parameter optimization

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MSSSA：一种针对全局优化问题的多策略增强型麻雀搜索算法 Research Article

孟凯1,2,陈晨1,2,辛斌1,2

《信息与电子工程前沿（英文）》 2022年第23卷第12期页码 1828-1847 doi: 10.1631/FITEE.2200237

摘要：麻雀搜索算法(SSA)是一种新的元启发式优化方法，具有简单和灵活的优点。然而，在处理多模态优化问题时，该算法仍存在早熟收敛、探索与开发不平衡等缺陷。针对上述问题，本文提出一种多策略增强的麻雀搜索算法(MSSSA)。首先，引入混沌映射以获取高质量的初始种群，并采用对立学习策略增加种群的多样性。其次，设计了一种自适应参数控制策略，以在全局探索与局部开发之间保持适当的平衡。最后，在个体更新阶段嵌入混合扰动机制，以避免算法陷入局部最优。为了验证所提方法的有效性，在IEEE CEC2014和IEEE CEC2019测试集的40个函数，以及10个不同维度的经典函数上进行了大量的实验。实验结果表明，与一些先进的算法相比，所提出的MSSSA表现出突出的优化性能。该算法还成功地应用于两个工程优化问题，证明了MSSSA在解决实际问题方面的优越性。

关键词：群智能；麻雀搜索算法；自适应参数控制策略；混合扰动机制；优化问题

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Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

《机械工程前沿（英文）》 2018年第13卷第1期页码 85-95 doi: 10.1007/s11465-018-0491-0

摘要：

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

关键词： injection molding intelligent methods process parameters optimization

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液压冲击机构工作参数调节机理与控制策略S

刘忠,,褚福磊,龙国键,廖永忠

《中国工程科学》 2005年第7卷第10期页码 73-77

摘要：

针对目前国内外液压冲击机械工作参数调节方法的局限性，提出了行程无级调节原理，设计了一种新型的行程无级调节装置，并对该装置进行了数字仿真研究；在此基础上设计了一种基于微机控制的无级调节工作参数的液压冲击机构，论述了其设计原理、结构特点、技术性能和控制策略。

关键词：液压冲击机构无级调节工作参数控制系统

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Design and control optimization of energy systems of smart buildings today and in the near future

Shengwei WANG, Wenjie GANG

《工程管理前沿（英文）》 2017年第4卷第1期页码 58-66 doi: 10.15302/J-FEM-2017005

摘要： Buildings contribute to a major part of energy consumption in urban areas, especially in areas like Hong Kong which is full of high-rise buildings. Smart buildings with high efficiency can reduce the energy consumption largely and help achieve green cities or smart cities. Design and control optimization of building energy systems therefore plays a significant role to obtain the optimal performance. This paper introduces a general methodology for the design and control optimization of building energy systems in the life cycle. When the design scheme of building energy systems is optimized, primary steps and related issues are introduced. To improve the operation performance, the optimal control strategies that can be used by different systems are presented and key issues are discussed. To demonstrate the effect of the methods, the energy system of a high-rise building is introduced. The design on the chilled water pump system and cooling towers is improved. The control strategies for chillers, pumps and fresh air systems are optimized. The energy saving and cost from the design and control optimization methods are analyzed. The presented methodology will provide users and stakeholders an effective approach to improve the energy efficiency of building energy systems and promote the development of smart buildings and smart cities.

关键词： Design optimization Optimal control Smart building Energy efficiency

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Design optimization of a wind turbine gear transmission based on fatigue reliability sensitivity

Genshen LIU, Huaiju LIU, Caichao ZHU, Tianyu MAO, Gang HU

《机械工程前沿（英文）》 2021年第16卷第1期页码 61-79 doi: 10.1007/s11465-020-0611-5

摘要： Fatigue failure of gear transmission is one of the key factors that restrict the performance and service life of wind turbines. One of the major concerns in gear transmission under random loading conditions is the disregard of dynamic fatigue reliability in conventional design methods. Various issues, such as overweight structure or insufficient fatigue reliability, require continuous improvements in the reliability-based design optimization (RBDO) methodology. In this work, a novel gear transmission optimization model based on dynamic fatigue reliability sensitivity is developed to predict the optimal structural parameters of a wind turbine gear transmission. In the model, the dynamic fatigue reliability of the gear transmission is evaluated based on stress–strength interference theory. Design variables are determined based on the reliability sensitivity and correlation coefficient of the initial design parameters. The optimal structural parameters with the minimum volume are identified using the genetic algorithm in consideration of the dynamic fatigue reliability constraints. Comparison of the initial and optimized structures shows that the volume decreases by 3.58% while ensuring fatigue reliability. This work provides new insights into the RBDO of transmission systems from the perspective of reliability sensitivity.

关键词： gear transmission fatigue reliability reliabi-lity sensitivity parameter optimization

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一种基于参数扰动的芯片成品率双目标优化框架

Xin LI,Jin SUN,Fu XIAO,Jiang-shan TIAN

《信息与电子工程前沿（英文）》 2016年第17卷第2期页码 160-172 doi: 10.1631/FITEE.1500168

摘要：

随着收缩技术的发展，工艺，电压和温度（PVT）参数的可变性显着影响了芯片设计的成品率分析和优化。先前的产量估计算法已经限于预测时序或功率产量。但是，忽略功率和延迟之间的相关性将导致明显的产量损失。这些方法中的大多数都还具有较高的计算复杂度和较长的运行时间。我们提出了一种基于Chebyshev仿射算术（CAA）和自适应加权和（AWS）方法的新型双目标优化框架，在该框架中将功率和时序收益两者均设置为目标函数。同时优化两个目标以保持它们之间的相关性。所提出的方法首先在任意相关性的假设下预测泄漏和延迟分布的保证概率边界。然后，通过计算累积分布函数（CDF）边界来建立功率延迟双目标优化模型。最后，将AWS方法应用于功率延迟优化，以生成分布良好的一组Pareto最优解。在ISCAS基准电路上的实验结果表明，该双目标框架能够在功率和时序产量之间提供足够的权衡信息。

关键词：参数变化，参数收益率，多目标优化，切比雪夫仿射，自适应加权和，

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Dymola-based multi-parameters integrated optimization for high speed transfer system of LED chip sorter

Jie OUYANG, Bin LI, Shihua GONG

《机械工程前沿（英文）》 2013年第8卷第2期页码 118-126 doi: 10.1007/s11465-013-0253-y

摘要：

To enhance the performance of high speed transfer system of LED chip sorting equipment, its control parameters need to be well matching with the mechanical system. In practical issues, it is difficult and time-consuming work to get these parameters matched because their selection is strongly depended on individuals. In current work, an integrated optimization method was carried out to solve this problem, in which the multiple control parameters optimization, modeling and simulation were included, i.e., a multi-domain model of transfer system performed on Dymola platform. Based on this model, the searching area of the key control parameters was narrowed by performing integrated optimization. After that a group of parameters were selected from this narrowed area to perform the equipment’s controls. The result showed this method possesses a simple and reliable nature. The optimal solutions also indicated that the optimized control parameters can well satisfy the requirements of transfer system. On the other hand, it greatly reduced the engineering adjustment time by using this method.

关键词： LED chip sorter multi-domain modeling and simulation parameter optimization modelica language

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参数自寻优模糊控制器在中央空调温度控制系统中的应用

吴爱国,杜春燕,宋晓强

《中国工程科学》 2004年第6卷第11期页码 84-87

摘要：

在中央空调温度控制系统中设计应用了一种参数自寻优模糊控制器。针对中央空调温度控制系统被控对象非线性、大滞后和时变等特点，该模糊控制器在规则可调整模糊控制器基础上引入了加权因子α和比例因子K_u的在线调整优化算法。运行结果表明，这种算法增强了系统的鲁棒性，在不同工作条件下，系统保持了良好的控制品质。

关键词：中央空调系统温度控制模糊控制器参数自寻优

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Footholds optimization for legged robots walking on complex terrain

《机械工程前沿（英文）》 2023年第18卷第2期 doi: 10.1007/s11465-022-0742-y

摘要： This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains. The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles, and to improve its stability and safety when walking on complex terrain. By relying on the depth camera installed on the robot and obtaining the terrain heightmap, the algorithm converts the discrete grid heightmap into a continuous costmap. Then, it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion. Compared with most existing footholds selection algorithms that rely on discrete enumeration search, as far as we know, the proposed algorithm is the first to use a continuous optimization method. We successfully implemented the algorithm on a hexapod robot, and verified its feasibility in a walking experiment on a complex terrain.

关键词： footholds optimization legged robot complex terrain adapting hexapod robot locomotion control