超高层劲性结构及大型机械设备立体协同施工技术

基于某超高层建筑群项目的主体施工阶段,对超高层劲性结构建筑群项目施工过程中可能遇到的问题,诸如大型机械立体协同、钢结构与钢筋连接节点优化、钢结构桁架层施工等重难点进行总结分析,并提出相应的解决方案以供探讨,可为同类型工程提供参考经验。     

A novel adaptive convolutional neural network for fault diagnosis of hydraulic piston pump with acoustic images

As an essential part of hydraulic transmission systems, hydraulic piston pumps have a significant role in many state-of-the-art industries. Thus, it is important to implement accurate and effective fault diagnosis of hydraulic piston pumps. Owing to the heavy reliance of shallow machine learning models on the expertise and experience of engineers, fault diagnosis based on deep models has attracted significant attention from academia and industry. To construct a deep model with good performance, it is necessary and challenging to tune the hyperparameters (HPs). Since many existing methods focus on manual tuning and use common search algorithms, it is meaningful to explore more intelligent algorithms that can automatically optimize the HPs. In this paper, Bayesian optimization (BO) is employed for adaptive HP learning, and an improved convolutional neural network (CNN) is established for fault feature extraction and classification in a hydraulic piston pump. First, acoustic signals are transformed into time–frequency distributions by a continuous wavelet transform. Second, a preliminary CNN model is built by setting initial HPs. The range of each HP to be optimized is identified. Third, BO is employed to select the optimal combination of HPs. An improved model called CNN-BO is constructed. Finally, the diagnostic efficiency of CNN-BO is analyzed using a confusion matrix and t-distributed stochastic neighbor embedding. The classification performance of different models is compared. It is found that CNN-BO has a higher accuracy and better robustness in fault diagnosis for a hydraulic piston pump. This research will provide a basis for ensuring the reliability and safety of the hydraulic pump.     

Joint tracking coefficients and the time delay of a nonstationary linear system,preceded by a static nonlinearity

The paper considers a block-oriented nonlinear Hammerstein system that consists of a linear block with real-valued time-varying unknown coefficients and a pure time delay, preceded by the static nonlinearity. The joint tracking of linear block coefficients and the time delay while processing observation samples is under consideration. The difficulty of the tracking process consists in the initial nonconvexity of the objective function to be minimized, in respect of the time delay. To obtain current estimates of the true coefficients and the time delay it is necessary to overcome the multiextremality of the objective function. A global optimization problem could be solved by changing a form of the nonconvex objective function into a convex one. The optimization problem has been subdivided into two problems that are analyzed in this article, as well. The first one consists of removal of the objective function multiextremality in respect of the time delay, while hunting for the global extremum. Therefore, the well-known approach based on the method of corrective operators, which is used to transform the multiextremal criterion into a unimodal function for the nonstationary Wiener system, is developed here for the Hammerstein one. The other problem consists of the applicability of unified adaptive algorithms, used for Wiener systems in the case of Hammerstein systems. The recursive parametric identification technique, based on the adaptive algorithm procedures, is developed here for the nonstationary block-oriented Hammerstein systems, too. The applicability of algorithms is supported by various simulation tests solved by computer for distinct inputs and for two static nonlinearities.     

接触器触头系统振动机理分析及算法优化

为了解决合闸过程中动、静触头接触引起的振动弹跳问题.本文建立了接触系统的二自由度运动微分方程,并利用遗传算法对交流接触器吸合过程进行优化,同时通过高速摄影实验对接触弹跳的全过程进行了观察和分析.结果表明:理论与实验结果高度一致,铁心在触头分离前发生碰撞,进一步加剧触头弹跳;铁芯弹跳再次碰撞时,触头的弹跳不受影响;在接触器运行过程中,动铁芯的运动会引起系统轻微振动;采用遗传算法优化的接触器触头弹跳时间和最大振幅均减小.研究结果为进一步控制和减小接触弹跳提供了理论依据.     

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids, carbohydrates, and lipids, as well as protein synthesis from the consumed food, the liver has many diverse responsibilities and functions that are to be performed. Liver disease may impact the hormonal and nutritional balance in the human body. The earlier diagnosis of such critical conditions may help to treat the patient effectively. A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver. The proposed approach can recognize the abnormalities with better accuracy without training, unlike in supervisory procedures requiring considerable computational efforts for training. In the earlier stages, the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation. Then, the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted–-Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information, which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts. It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%. The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.     

基于响应曲面法的涡轮增压器废气阀门激光焊接工艺优化研究

激光焊接技术凭借其高效、高精度的特点已广泛应用在汽车制造产业,在涡轮增压器的生产中,激光焊接也逐步被应用于实现废气阀门与阀杆的连接。虽然当前对于激光焊接的工艺研究很多,但对工艺参数的优化也一直缺少一个科学有效的方法。本文以熔接深度、熔接宽度和内部缺陷作为响应变量,选取焊接功率、焊接速度作为因子,运用响应曲面法(RSM)设计实验方案,通过对响应结果进行分析,研究焊接参数对焊接质量的影响,拟合能够预测最优参数的数学模型,最终将获得的最优参数运用到生产中进行验证。     

大跨度机库钢桁架中的预应力钢绞线穿束施工技术

以成都天府国际机场国航基地工程(机务维修一期)101号维修机库大跨度边桁架中的预应力钢绞线施工为背景,针对预应力钢绞线超长、单束钢绞线数量多、钢绞线穿束时质量大、摩擦力大等难点,提出钢绞线设计分束优化、增加增强隔板、研发穿束牵引装置等方案,通过实施该方案,减小了穿管时的牵引力,大大降低了钢绞线穿管损伤风险,同时大幅节省了穿管措施费用。     

Modeling and optimization of ammonia process: Effect of hydrogen unit performance on the ammonia yield

The main object of this research is the development of a mathematical framework to simulate a commercial ammonia plant and obtaining the optimal operating conditions of process at steady state condition. The considered ammonia plant consists of steam and autothermal reforming reactors, low and high temperature shift converters, hydrogen purification section, methanation, and ammonia synthesis reactors. The catalytic reactors are heterogeneously modeled based on the mass and energy balance equations considering heat and mass transfer resistances in the gas and catalyst phases. In addition, an equilibrium model is applied to simulate the absorption column. Then, the accuracy of developed framework is investigated against plant data. The results show that the internal mass transfer resistance in the commercial catalyst limits the syngas production in the reforming section. In the second step, an optimization problem is formulated to enhance the ammonia production considering safety and operating limitations. The formulated optimization problem is handled employing the genetic algorithm. The results show that more syngas production in the optimized hydrogen unit is one of the main reasons for higher ammonia synthesis in the considered plant. Applying optimal conditions on the process increases ammonia production potential from 1890 to 2179 mol s⁻¹.     

Pore-scale study of effects of different Pt loading reduction schemes on reactive transport processes in catalyst layers of proton exchange membrane fuel cells

Reducing the Platinum (Pt) loading while maintaining the performance is highly desired for promoting the commercial use of proton exchange membrane fuel cells (PEMFCs). Different methods have been adopted to fabricate catalyst layers (CLs) with low Pt loading, including utilizing lower Pt/C catalysts (MA), mixing high Pt/C catalysts with bare carbon black particles (MB), and reducing CL thickness while maintaining high Pt/C ratio (MC). In this study, self-developed pore-scale model is adopted to investigate the performance of the three Pt reduction methods. It is found that MA shows the best performance while MB shows the worst. Then, effects of Pt dispersion are further explored. The results show that denser Pt sites will result in higher local oxygen flux and thus higher local transport resistance. Therefore, MA method, which shows the better Pt dispersion, leads to improved performance. Third, CLs with quasi-realistic structures are investigated. Higher tortuosity resulting from the random pores produces higher bulk resistance along the thickness direction, while MA still exhibits the best performance. Finally, improved CL structures are investigated by designing perforated CL structures. It is found that adding perforations can significantly reduce the bulk transport resistance and can improve the CL performance. It is demonstrated that CL structure plays important roles on performance, and there are still huge potentials to further improve CL performance by increasing Pt dispersion and optimizing CL structures.     

Simulation and analysis of dual-reflux pressure swing adsorption using silica gel for blue coal gas initial separation

A dual-reflux pressure swing adsorption (DR-PSA) process was proposed and simulated to initially separate the blue coal gas, aiming to capture carbon dioxide (CO₂) and enrich hydrogen (H₂), simultaneously. With a feed flow rate of 7.290 slpm, a light product reflux flow rate of 0.505 slpm and the heavy product reflux flow rate of 3.68 slpm, the developed DR-PSA process could capture CO₂ up to 64.01% with a recovery of 99.60% and enrich H₂ up to 34.66% with a recovery of 97.63% from the blue coal gas (36.2% N₂/28.5% H₂/13.9% CO/12.7% CO₂/8.7% CH₄). In addition, in order to optimize the process, the effects of various operating parameters on the DR-PSA process performance in terms of product purity and recovery were discussed in detail, including the feed position, the light product reflux ratio and the heavy product reflux ratio. Moreover, the dynamic distribution behaviors of pressure, temperature and gas-solid concentration were presented to explain and evaluate the process separation performance in depth under different operating conditions.