Sparse identification for ball-screw drives considering position-dependent dynamics and nonlinear friction

Establishing accurate dynamic models in a form that is suitable for integration with model-based control methods, is of great significance for further improving the dynamic motion control precision of ball-screw drives. However, due to the nonlinear time-varying factors such as position-dependent dynamics and nonlinear friction disturbance, it is difficult to model the dynamic characteristics of ball-screw drives accurately, concisely and efficiently. To overcome this challenge, a sparse identification method for ball-screw drives is proposed. Ball-screw drives are modeled as discrete-time linear parameter-varying systems under nonlinear friction disturbance, and two types of dictionary function libraries are designed to represent the position-dependent dynamics and nonlinear friction respectively. After constructing the regression form of the system model, a stepwise sparse regression policy is proposed to solve all the coefficients of dictionary functions. The proposed method is verified in both simulation and real environments. The results both show that by the proposed method, an accurate and linearizable dynamic model of ball-screw drives can be identified only using the data from only one global random excitation experiment covering the working stroke.     

Digital twin-driven manufacturing equipment development

Currently, expectations of shorter time-to-market and improved product performance are placing greater demands on manufacturing companies. However, the optimization and redesign work between the design stage and the prototype design and manufacturing stage in the traditional product development process lengthens the required product development cycle time (which lasts up to several years in extreme cases). The manufacturing phase for the physical prototype of the product is especially time-consuming and costly. The above reasons make the common product development process increasingly unable to meet the demands of market needs. Motivated by this need, the digital twin (DT)-driven manufacturing equipment (ME) development method is studied in this paper. This method contains three main core elements of the design method based on axiomatic design (AD) theory, the construction of DT models related to ME development, and DT-based validation analysis. The advantage of this method is that it can incorporate the physical prototype manufacturing stage into the digital space with the high-fidelity model provided by the DT technology, which ensures the confidentiality of the design scheme validation while freeing it from the physical prototype stage. This avoids the cost of physical prototyping, shortens the product development cycle, and improves the efficiency of new ME development. At the end of this paper, a case study of the development of a virtual machining dynamic performance test bench (VM-TB) is carried out to show the implementation flow of this proposed method, and its operability and effectiveness are verified.     

Formation Theory and Printability of Photocurable Hydrogel for 3D Bioprinting

Bio-ink has gradually transited from ionic-crosslinking to photocrosslinking due to photocurable bio-hydrogel having good formability and biocompatibility. It is very important to understand and quantify the crosslinking process of photocurable hydrogels, otherwise, bioprinting cannot be standardized and scalable. However, there are few studies on hydrogel formation process and its photocrosslinking behavior which cannot be accurately predicted. Herein, the photoinitiated radical polymerized bio-hydrogels are taken as an example to establish the formation theory. Three typical crosslinking reactions are first distinguished. It is further proposed that not all double-bonds consumed during crosslinking contributeequally to polymerization. Then the concept of effective double-bond conversion (EDBC) is elicited. Deriving from EDBC, several important formation indices are defined. According to theory, it is predicted that slow crosslinking can improve the crosslinking degree. Furthermore, based on the slow crosslinking effect, a new strategy of projection-based 3D printing (PBP) is proposed, which significantly improved printing quality and efficiency. Overall, this work will fill the gap in hydrogel's formation theory, making it possible to accurately quantify the formation process.     

Three Potential Elements of Developing Nerve Guidance Conduit for Peripheral Nerve Regeneration

Autograft replaced by a nerve guidance conduit (NGC) is challenging in peripheral nerve injury because current NGC is still limited by precise conductivity and excellent biocompatibility in vivo, which influences the peripheral nerve repair even for a long lesion gap repair. Several particular elements have the potential function for nerve conductivity acceleration based on the traditional three factors of neural tissue engineering. The review aims to address three questions: 1) What is the superior factor for nerve conduction in the application? 2) How can a more conductive regenerative scaffold be constructed in vivo? 3) What is the next step in nerve regeneration for NGC? The bibliometrics analysis of NGC-related references is adopted to acquire that the conductive material, manufacturing technology of neural scaffold, and electrical stimulation (ES) play essential roles in the acceleration of nerve conduction. This review visually analyses the research status and summarizes the main types of conductive materials, the manufacturing technologies of neural scaffolds, and the characteristics of ES. The viewpoints and outlook of developing NGC are also discussed in this review. The proposed three elements are expected to improve the nerve conduction of NGC in vivo and even address the dilemma of long-distance peripheral nerve injury.     

Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization

This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.     

基于声发射参数分析的滑动轴承故障诊断方法研究

本文基于声发射产生机理,对基于声发射参数分析法进行滑动轴承故障诊断方法进行理论和实验研究。首先,通过汽轮机发电机组模拟转子实验台模拟了滑动轴承三种润滑状态,通过实验台以及设计的实验方案,利用声发射采集设备对不同润滑状态的声发射信号进行采集。其次,针对采集到的不同润滑状态声发射信号,对其能量均值以及功率谱熵均值进行计算,提出了基于声发射能量均值和功率谱熵均值的散度指标的滑动轴承润滑状态诊断方法,并利用这种方法对模拟信号进行诊断,同时将其与单一能量参数分析法进行对比,发现能量参数分析法不能很好的反映出滑动轴承的三种润滑状态,而文中所提的采用多参数结合的指标诊断方法具有更好的信号适应性以及更高的区分度。     

Output feedback adaptive RISE control for uncertain nonlinear systems

In this article, committed to extending the robust integral of the sign of the error (RISE) feedback control to the working condition of output feedback, a novel output feedback controller with a continuously bounded control input which combines the adaptive control and integral robust feedback will be proposed for trajectory tracking of a family of nonlinear systems subject to modeling uncertainties. A novel adaptive state observer (ASO) with disturbance rejection performance is creatively constructed to derive real-time estimation of the unmeasured state signals. Moreover, a projection-type adaption law is integrated to handle parameter uncertainties and an integral robust term is employed to deal with external disturbances. It is shown that asymptotic estimation performance and meanwhile asymptotic tracking result can eventually be derived. Simulation validations are implemented to demonstrate the high tracking performance of the presented controller. Notably, the synthesized control algorithm can be readily extended to the Euler–Lagrange systems. Typically, it can be extended to practical electromechanical equipment such as three-dimensional vector forming robots to improve the real-time forming accuracy.     

掺烧煤质差异较大煤种对“W”火焰炉运行参数的影响

针对掺烧煤质差异较大煤种时锅炉运行参数变化不确定的问题,以一台660 MW“W”火焰炉为研究对象、100%热耗率验收工况为锅炉负荷条件,研究在燃用现行煤种义马烟煤（烟煤）的基础上,按照不同比例掺烧金竹山无烟煤（无烟煤）对锅炉运行参数的影响。利用数值模拟得到2种煤化程度差异较大煤种按照不同比例掺烧时,锅炉有效利用热、烟气速度和温度以及NOx、SOx、CO产量的变化情况。模拟结果表明:锅炉在以高负荷运行时,65%无烟煤+35%烟煤的掺烧比例可以提高锅炉使用寿命,降低炉膛受热面发生腐蚀的概率,但对煤粉的着火和稳燃无促进作用;50%无烟煤+50%烟煤的掺烧比例可以满足锅炉额定效率,同时能显著降低发电成本,但炉膛受热面的腐蚀情况会较为严重。     

基于CFD的风道旋流燃烧器优化分析

基于计算流体动力学理论（CFD）,对某型风道旋流燃烧器进行了数值仿真计算,主要分析了有无助燃风道导流板对该型燃烧器的流场分布和排放污染物质量浓度的影响,以及不同的燃烧温度对尾气中污染物质量浓度影响,并与实际试验燃烧的测点数值进行对比。结果表明:模拟计算的CO质量浓度值与同工况下的试验结果相近,仿真结果具备工程参考价值;增加导流板后风道流场分布得到了明显的改善,燃烧效率显著提高,尾气中CO质量分数降低了约18.83%;通过比较不同温度下的燃烧产物质量浓度,可以发现该型风道燃烧器在1 800~1 900 ℃的燃烧温度区间内,尾气中NO和CO的质量浓度都达到了最佳可控范围。     

基于能量和?的抛物线槽式太阳能集热器性能分析

基于热力学方程以及实际集热器参数,对抛物线槽式太阳能集热器建立了热模型并进行了热力学分析;然后,从热力学第一定律和第二定律的角度,分析和讨论了集热器的热效率及?效率的影响因素。分析表明:影响槽式集热器性能的主要因素有太阳辐射、换热工质温度和流量、真空条件以及环境条件（如风速）等;光学损失是最主要的能量损失,吸收管的吸热?损失是最主要的?损。