基于PMOPSO方法的H型铲齿凸轮优化设计

给出一种H型铲齿凸轮的标准设计方法,用于解决多升程H型铲齿凸轮的优化设计问题。针对传统铲齿凸轮存在的过渡点冲击问题,提出基于H型凸轮从动件运动规律的铲齿凸轮设计方案。以凸轮面积为设计目标函数,以从动件的偏置量和初始位移为设计变量,在凸轮一般设计准则的基础上,考虑理论廓线曲率范围和压力角分布的约束条件,建立H型铲齿凸轮的优化设计模型。多升程H型铲齿凸轮的优化设计问题具有约束条件多、非线性强和计算复杂度高的特点,将多项式变异算子和标准粒子群优化结合,提出多项式变异粒子群优化方法。以此优化方法为基础,通过构造罚函数处理设计约束,分别求解三升程和四升程的H型铲齿凸轮优化设计问题。计算结果表明,提出的标准设计方法可显著降低多升程H型铲齿凸轮的工作轮廓面积,使铲削机构更加紧凑。     

基于改进Mask Scoring R-CNN的铲齿磨损检测研究

为了实现在电铲工作过程中对铲齿磨损进行实时检测，防止因铲齿磨损而影响电铲开采效率，提出了一种基于改进Mask Scoring R-CNN（region convolutional neural network，区域卷积神经网络）的铲齿实例分割模型。首先，以ResNet-101（residual network， 残差网络）和改进的FPN（feature pyramid networks，特征金字塔网络）作为主干网络，提取高、低特征层的语义信息和细节特征并融合，结合ROI Align层对局部特征层进行裁剪和归一化处理，以完成目标检测与实例分割；然后，基于获取的铲齿分割效果图以及二值化掩码图形信息，计算实例分割后图像中铲齿部分的像素面积，以判断其磨损情况。结果表明，以ResNet-101和改进FPN为主干网络的铲齿实例分割模型在测试集上的平均像素精度为90.76%，平均交并比为83.62%，相比于以ResNet-101和传统FPN为主干网络的实例分割模型分别提升了1.18%和1.21%。在电铲采掘工作现场进行8次铲齿磨损检测实验，检测到的每颗铲齿的磨损程度波动幅度均小于2%，均方差为0.7左右，说明所提出的实例分割模型对铲齿有较好的分割效果和稳定性，基本满足磨损检测要求。研究结果可为铲齿磨损状态的智能化检测提供新思路。     

对数螺线在铲齿成形铣刀CAD中的应用研究

在新的制造条件下,以对数螺线作为铲齿成形铣刀的齿背曲线,可使得刀具重磨前刀面后,切削刃上各点的后角保持不变,保证了刀具的切削性能稳定.运用AutoCAD的内嵌编程语言VBA,开发了此类铣刀的CAD系统,实现了对数螺线齿背曲线的自动生成,以及刀具设计中的变参数设计和适应性设计,从而提高了设计效率和质量,为对数螺线铲齿成形铣刀的CAD/CAM一体化技术应用于生产实践奠定了良好的基础.     

An Invesigation in Corrosion of Low-alloy Steel in Marine Environment

利用电化学手段和激光拉曼光谱研究了低合金钢在海洋环境中腐蚀行为及产物.结果表明,低合金钢在海水环境中自然暴露0.5个月,其腐蚀状态进入相对稳定的阶段,供氧情况的差异致使低合金钢锈层分为内、外两层,试验用低合金钢短期腐蚀速率可用方程V=0.3227t-0.2489拟合.     

海洋环境下低合金钢腐蚀行为研究

利用电化学手段和激光拉曼光谱研究了低合金钢在海洋环境中腐蚀行为及产物.结果表明,低合金钢在海水环境中自然暴露0.5个月,其腐蚀状态进入相对稳定的阶段,供氧情况的差异致使低合金钢锈层分为内、外两层,试验用低合金钢短期腐蚀速率可用方程V=0.3227t-0.2489拟合.     

WK-4型挖掘机行走机构与改造

WK-4电铲走车Z33在生产中经常断齿，打牙，提出在中心距不变，把Z33齿改为Z32的解决方案。     

爆炸消除焊接残余应力研究

用条状炸药对碳钢、低合金钢、调质钢和奥氏体不锈钢进行爆炸消除焊接残余应力试验。已经在压力容器、石油化工反应塔、氧化铝厂脱硅槽、水电站压力钢管等大中型焊接结构上使用。     

核电设备用碳钢和低合金钢的断裂韧性设计的研究

本文主要是关于核电设备用碳钢和低合金钢的断裂韧性设计的研究。化学成分、热处理工艺、材料缺陷以及试验的取样情况都有可能对断裂韧性试验结果造成影响。设计核电设备材料时,可通过夏比冲击试验和落锤试验考核碳钢和低合金钢的断裂韧性,还应充分考虑影响材料韧性的各种因素,制定合适的技术要求。     

深松机关键部件小变量范围内的试验研究

通过对深松铲铲尖的工作阻力主要影响因素的分析及各因素的参数范围的确定,采用二次正交旋转设计试验方案,加工23组不同结构参数的铲尖,每组铲尖加工3个,试验时每组3个铲尖同时进行作业,牵引阻力取三个铲尖的平均牵引阻力。     

EBZ160Z掘进机装运机构的设计

装运机构的主要作用是将切割下来的物料装载并转运的机构,其性能的好坏直接影响着设备生产的能力和工作效率。自从掘进机切割功率达到160k W以上之后,更快的切割效率对掘进机装运机构的工作能力也提出了新的要求。EBZ160Z的装运机构分为铲板部和第一运输机两部分。铲板部采用镜面双向大倾角,液压马达直接驱动三齿星轮。第一运输机为平直机构,与铲板构成共同滑移,且采用边双链结构、液压马达驱动和油缸张紧加卡板的形式。     

Transfer Learning for Chest X-rays Diagnosis Using Dipper ThroatedAlgorithm

Most children and elderly people worldwide die from pneumonia, which is a contagious illness that causes lung ulcers. For diagnosing pneumonia from chest X-ray images, many deep learning models have been put forth. The goal of this research is to develop an effective and strong approach for detecting and categorizing pneumonia cases. By varying the deep learning approach, three pre-trained models, GoogLeNet, ResNet18, and DenseNet121, are employed in this research to extract the main features of pneumonia and normal cases. In addition, the binary dipper throated optimization (DTO) algorithm is utilized to select the most significant features, which are then fed to the K-nearest neighbor (KNN) classifier for getting the final classification decision. To guarantee the best performance of KNN, its main parameter (K) is optimized using the continuous DTO algorithm. To test the proposed approach, six evaluation metrics were employed namely, positive and negative predictive values, accuracy, specificity, sensitivity, and F1-score. Moreover, the proposed approach is compared with other traditional approaches, and the findings confirmed the superiority of the proposed approach in terms of all the evaluation metrics. The minimum accuracy achieved by the proposed approach is (98.5%), and the maximum accuracy is (99.8%) when different test cases are included in the evaluation experiments.     

Optimization of Electrocardiogram Classification Using Dipper Throated Algorithm and Differential Evolution

Electrocardiogram (ECG) signal is a measure of the heart’s electrical activity. Recently, ECG detection and classification have benefited from the use of computer-aided systems by cardiologists. The goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization (DTO) and Differential Evolution Algorithm (DEA) into a unified algorithm to optimize the hyperparameters of neural network (NN) for boosting the ECG classification accuracy. In addition, we proposed a new feature selection method for selecting the significant feature that can improve the overall performance. To prove the superiority of the proposed approach, several experiments were conducted to compare the results achieved by the proposed approach and other competing approaches. Moreover, statistical analysis is performed to study the significance and stability of the proposed approach using Wilcoxon and ANOVA tests. Experimental results confirmed the superiority and effectiveness of the proposed approach. The classification accuracy achieved by the proposed approach is (99.98%).     

Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection Systems

The Internet of Things (IoT) is a modern approach that enables connection with a wide variety of devices remotely. Due to the resource constraints and open nature of IoT nodes, the routing protocol for low power and lossy (RPL) networks may be vulnerable to several routing attacks. That’s why a network intrusion detection system (NIDS) is needed to guard against routing assaults on RPL-based IoT networks. The imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network attacks. Therefore, we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique (LSH-SMOTE). The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization algorithms. To prove the effectiveness of the proposed approach, a set of experiments were conducted to evaluate the performance of NIDS for three cases, namely, detection without dataset balancing, detection with SMOTE balancing, and detection with the proposed optimized LSH-SOMTE balancing. Experimental results showed that the proposed approach outperforms the other approaches and could boost the detection accuracy. In addition, a statistical analysis is performed to study the significance and stability of the proposed approach. The conducted experiments include seven different types of attack cases in the RPL-NIDS17 dataset. Based on the proposed approach, the achieved accuracy is (98.1%), sensitivity is (97.8%), and specificity is (98.8%).     

Estimation of Parameters of Universal Distribution of Moments of Failure of Products

A method is proposed for estimating the parameters of a mixture of exponential and Weibull distributions for which the accuracy of preliminary estimates obtained by graphical analysis is refined in accordance with the criterion of maximum likelihood. The efficiency of the proposed method is supported by the results of statistical modeling.     

Evaluation of optical properties of highly scattering media by moments of distributions of times of flight of photons

A novel method for the determination of the optical properties of tissue from time-domain measurements is presented. The data analysis is based on the evaluation of the first moment and the second centralized moment, i.e., the mean time of flight and the variance of the measured distribution of times of flight (DTOF) of photons injected by short (picosecond) laser pulses. Analytical expressions are derived for calculation of absorption and of reduced scattering coefficients from these moments by application of diffusion theory for infinite and semi-infinite homogeneous media. The proposed method was tested on experimental data obtained with phantoms, and results for absorption and reduced scattering coefficients obtained by the proposed method are compared with those obtained by fitting of the same data with analytical solutions of the diffusion equation. Furthermore, the accuracy of the moment analysis was investigated for a range of integration limits of the DTOF. The moment analysis may serve as a comparatively fast method for evaluating optical properties with sufficient accuracy and can be used, e.g., for on-line monitoring of optical properties of biological tissue.     

卧式金属罐容量的测量结果不确定度

本文根据多年的实践检定经验 ,参照JJF1 0 59- 1 999《测量不确定度评定与表示》以及《测量不确定度表达 1 0讲》 ,对卧式金属罐容量的测量结果不确定度进行了评定。     

盐酸浓度不确定度的评估

通过对盐酸浓度标定的过程分析，找出影响结果的各个分量，进行不确定度的评定，按照计量技术规范给出标准的表示法。