EXPLOSIVE HARDENING OF HIGH Mn STEEL

The explosive hardening of high Mn Steel was simulated by using light gas gun under selected ranges of impact load from 10 to 20 GPa and pulse duration from 0.04 to 1.6μs.The experi- mental results showed that a lot of twins formed in the shocked high Mn steel may be the prin- cipal cause of explosive hardening.

Hardening Effect on Machined Surface for Precise Hard Cutting Process with Consideration of Tool Wear

During hard cutting process there is severe thermodynamic coupling effect between cutting tool and workpiece, which causes quenching effect on finished surfaces under certain conditions. However, material phase transformation mechanism of heat treatment in cutting process is different from the one in traditional process, which leads to changes of the formation mechanism of damaged layer on machined workpiece surface. This paper researches on the generation mechanism of damaged layer on machined surface in the process of PCBN tool hard cutting hardened steel Cr12MoV. Rules of temperature change on machined surface and subsurface are got by means of finite element simulation. In phase transformation temperature experiments rapid transformation instrument is employed, and the effect of quenching under cutting conditions on generation of damaged layer is revealed. Based on that, the phase transformation points of temperature under cutting conditions are determined. By experiment, the effects of cutting speed and tool wear on white layer thickness in damaged layer are revealed. The temperature distribution law of third deformation zone is got by establishing the numerical prediction model, and thickness of white layer in damaged layer is predicted, taking the tool wear effect into consideration. The experimental results show that the model prediction is accurate, and the establishment of prediction model provides a reference for wise selection of parameters in precise hard cutting process. For the machining process with high demanding on surface integrity, the generation of damaged layer on machined surface can be controlled precisely by using the prediction model.

Optimization strategy in end milling process for high speed machining of hardened die/mold steel

An optimization strategy for high speed machining of hardened die/mold steel based on machining feature analysis was studied. It is a further extension of the previously presented study on the thermal mechanism of end milling and constant cutting force control. An objective function concerning machining cost and associated optimization algorithm based on machining time and cutting length calculation was proposed. Constraints to satisfy specific machining strategies when high speed machining the hardened die/mold steel, trochoid tool path pattern in slot end milling to avoid over-heat and feed rate adaptation to avoid over-load, were also discussed. As a case study, the tool selection problem when machining a die part with multiple machining features was investigated.

GRINDING TEMPERATURE AND COOLING RATE DURING GRIND-HARDENING OF 40Cr STEEL

The mathematical model of the grinding temperature is established. The grinding temperature and the cooling rate are measured in the grind-hardening process of 40Cr steel under different conditions. Moreover, the grind-hardening effects are investigated. Experimental results show that the calculated temperatures are comparatively close to the measured ones, and the required temperature and cooling rate can be achieved. Furthermore, the microstructure of the hardened zone is similar to that obtained through the high-frequency induction technique. The average hardness of the entirely hardened zone is HV670 and the thickness of the hardened layer is adjacent to 1.3 mm. It indicates that the hardening mechanism induced by the grinding heat and high-frequency heating is identical. Finally, the fine needlelike martensite is obtained.

The Results of Research to Determine the Parameters of HardeningWorking Area of the Gin and Linter Grates

The article provides substantiation of the choice of the quenching parametersfor the working zone of gin and linter grates and the quenchingparameters.The results of bench and industrial tests of the grate with ahardened working zone are also given.

ANALYSIS AND SIMULATION ON THE MECHANISM OF A NOVEL DUAL-WAVE SHOCK TEST MACHINE

For qualifying the anti-shock performance of shipboard equipments and simulating actual underwater explosion environments, a novel dual-wave shock test machine is proposed to increase testing capability of shock test machines as well as to meet certain shock testing specification. The machine can generate a double-pulse acceleration shock for test articles according to specification defined in BV043/85. On the basis of the impact theory, a nonlinear dynamic model of the hydraulically-actuated test machine is established with thorough analysis on its mechanism which involves conversion of gas potential energy and dissipation of kinetic energy. Simulation results have demonstrated that the machine can produce a double-pulse acceleration shock in the time domain or a desired shock response spectrum in the frequency domain, which sets a theoretical base for the construction of the proposed machine.

Evaluating data-driven algorithms for predicting mechanical properties with small datasets:A case study on gear steel hardenability

Data-driven algorithms for predicting mechanical properties with small datasets are evaluated in a case study on gear steel hardenability.The limitations of current data-driven algorithms and empirical models are identified.Challenges in analysing small datasets are discussed,and solution is proposed to handle small datasets with multiple variables.Gaussian methods in combination with novel predictive algorithms are utilized to overcome the challenges in analysing gear steel hardenability data and to gain insight into alloying elements interaction and structure homogeneity.The gained fundamental knowledge integrated with machine learning is shown to be superior to the empirical equations in predicting hardenability.Metallurgical-property relationships between chemistry,sample size,and hardness are predicted via two optimized machine learning algorithms:neural networks(NNs)and extreme gradient boosting(XGboost).A comparison is drawn between all algorithms,evaluating their performance based on small data sets.The results reveal that XGboost has the highest potential for predicting hardenability using small datasets with class imbalance and large inhomogeneity issues.

Machinability Investigation and Optimization of Process Parameters in Cryogenic Assisted Sustainable Turning of AISI‑L6 Tool Steel

The application of cutting fluid is significantly increased in the machining sector to improve productivity.However,the inherent characteristics of cutting fluids on ecology,environment,and society shift the interest of researchers to work on environmentally friendly cooling conditions such as cryogenic cooling.Here,the effect of cutting speed and feed rate on the machining performance of the AISI‑L6 tool steel is investigated under cryogenic cooling conditions.Then,the L9 Taguchi based grey relational analysis(GRA)is conducted to investigate the essential machining indices such as cutting energy,surface roughness,tool wear,and material removal rate(MRR).The results indicate that the cutting speed of 160 m/min and feed rate of 0.16 mm/r are the optimum parameters that significantly improves the machining performance of AISI‑L6 tool steel.

High Quality Fixture Quenching Fixture Types, Levels of Automation and Machine Types

The paper shows, how the quality of workpieces to be heat treated can be improved by using the technology of fixture-quenching. Different fixture systems, like fixed mandrel, expanding mandrel and lamellar mandrel are described. In the next section there is a comparison between manual operation of hardening machines vs. automated lines. Since there are applications for each, manual and fully automated hardening systems, HEESS has not only focused to develop automated lines, but also refined manual operated hardening machines (SP-Series). These take advantage of the latest technology, like for example quick tool change and PLC-control with workpiece parameter database. An overview over different machine types is given.

智慧矿山系统工程及关键技术研究与实践

针对智慧矿山复杂巨系统建设过程中存在的问题,提出了智慧矿山建设的总体技术架构,并分别从智慧矿山系统模型构建、地下空间重构与模型动态更新、机器视觉测量技术、瓦斯环境射频防爆测试方法、矿山安全闭环管控体系、智慧矿山标准体系等方面进行了详细阐述。将智慧矿山分为信息感知支撑层、边缘计算层、云数据中心、多型网络、矿山智能生产管控平台、矿山智能生产系统、智慧矿山运维管理系统,构建了基于多系统深度融合的智慧矿山技术架构。基于智慧矿山知识图谱及信息抽取技术,构建了以数据创新为驱动、通信网络为基础、数据算力为核心的智慧矿山系统模型。构建了以机器视觉感知信息为主、其他感知信息为辅的矿山井下三维视觉空间模型,提出了矿山井下场景三维视觉与空间重建框架,实现了矿山井下三维空间重构与动态更新。开发了基于机器视觉技术的井下设备位姿与煤岩界面识别算法,实现了对井下综采装备群及煤岩分界面的同时空测量。探讨了井下瓦斯环境下现行防爆标准对5G基站功率的限制及存在的不足,设计开发了射频电磁能防爆专用试验装置,为提升井下5G基站功率阈值提供了方法借鉴。提出了融合灾害信息全面感知、防控方案自主决策、防控装备协同控制的矿井灾害闭环管控系统技术架构,实现井下灾害的超前预测预警与协同防控。构建了智能化煤矿标准体系框架,剖析了我国煤矿与金属矿山智能化建设典型案例,提出了智慧矿山建设发展趋势及建议。

气压搅水式自动蔬菜清洗机的设计

蔬菜清洗机的主要作用是洗掉蔬菜上残留的农药、化肥、泥土及虫子,使蔬菜保持一定的清洁度,从而满足市场对净菜的供应需求。目前大部分蔬菜清洗机采用的工作原理是利用水与蔬菜、蔬菜与蔬菜之间的摩擦作用进行清洗,导致蔬菜破损率较高。利用正压气体在水中的爆气原理,设计一种气压搅水式自动蔬菜清洗机,增加水流对蔬菜的柔性,减少蔬菜与蔬菜之间的硬性摩擦。试验表明,该机生产率高,对蔬菜破坏作用小,洗净率高。

基于XGBoost模型岩体可爆性研究

岩体可爆性是衡量岩体爆破难易程度的一个重要指标,准确对岩体可爆性评价能够为合理爆破设计提供依据。选取岩石密度、单轴抗压强度、岩石抗拉强度、岩石脆性指数、动载强度和完整性系数等作为岩体可爆性数据集的指标,采用Z-Score方法标准化岩体可爆性数据集,消除量纲对模型预测影响,分别采用朴素贝叶斯、支持向量机和XGBoost模型进行岩体可爆性分级,结果表明:采用XGBoost模型能够准确评价岩体的可爆性,为岩体可爆性评价提供一种新的方法。

影响15-5PH沉淀硬化不锈钢硬度的因素

炼制了两炉化学成分不同的15-5PH马氏体沉淀硬化不锈钢并制备了试样。对试样进行了1040℃保温90 min油冷的固溶处理及铣削、钻削、磨削试验和分别在400~620℃时效1.5、4、8和12 h。随后检测了试样的硬度和显微组织。结果表明:切削加工对15-5PH马氏体沉淀硬化不锈钢的硬度无明显影响;在450℃时效,随着时效时间延长至4 h,15-5PH钢的硬度提高,并达到了44~46 HRC的硬度要求;15-5PH钢的最佳时效工艺为450℃保温4 h。

超塑成形工艺及设备浅析

超塑成形/扩散焊接(SPF/DB)技术是利用材料在超塑性状态下良好的固态粘合性能而发展起来的一种组合工艺技术。本文对超塑成形/扩散焊接(SPF/DB)成形工艺、热成形机和真空氩气成形系统进行了详细介绍分析。

炸药压制成型机参数采集系统开发

为进一步实现质量控制与安全生产,研制一套炸药压机参数实时采集系统。基于压机控制系统和传感器,利用高级语言编程从压制过程实时读取相关参数并在人机界面显示,操作人员可实时观测压制过程的工作参数,以便自适应调整参数控制药柱质量、监测压机运行状态并做应急预案。结果表明:该压机参数采集系统性能稳定、操作简单方便,满足参数采集、存储、显示功能。

某型号曲轴表面感应淬火改性的加工工艺设计

曲轴在长时间运动中容易因异常磨损及疲劳裂纹而产生失效,为了提升曲轴表面的耐磨性能和抗疲劳性能,针对某型号发动机曲轴表面感应淬火改性的偿试,对加工工艺进行了分析、设计,重点针对变形控制提出工艺措施,并通过工艺实验验证加工工艺的可行性。

基于小波散射变换的煤矿瓦斯和煤尘爆炸声音识别方法

为解决煤矿瓦斯与煤尘爆炸灾害报警方法误报率和漏报率高等问题,提高煤矿瓦斯和煤尘爆炸感知准确率,提出了基于小波散射变换的煤矿瓦斯和煤尘爆炸声音识别方法:在煤矿井下重点监测区域安装矿用拾音设备,实时采集设备工作声音和环境音;将采集到的声音通过小波散射变换得到小波散射系数,构建声音信号的小波散射系数图,通过计算小波散射系数图的图像灰度梯度共生矩阵得到由小梯度优势、大梯度优势、能量、灰度平均、梯度平均、灰度均方差、梯度均方差、相关性、灰度熵、梯度熵、混合熵等构成的十一维特征参数,构成表征该声音信号的特征向量,输入到支持向量机(SVM)中训练得到煤矿瓦斯和煤尘爆炸声音识别模型;对待测声音信号同样提取其小波散射系数图的灰度梯度共生矩阵得到十一维特征向量,输入到训练好的煤矿瓦斯和煤尘爆炸声音识别模型中进行声音识别分类,并进行试验验证。采取声音信号的特征提取试验,分析了不同声音的小波散射图及其特征参数分布特点,瓦斯和煤尘爆炸声音的小波散射系数图及其十一维特征向量与煤矿井下其他声音差异明显,证明了所提特征提取方法的可行性;通过贝叶斯优化完成支持向量机超参数优化试验,选取更符合训练模型的超参数,识别试验结果表明,所提方法的识别率为95.77%,明显优于其他对比算法,能够满足煤矿瓦斯和煤尘爆炸识别的需求。

连采机后配套梭式防爆蓄电池运煤车的设计

结合设计的运煤车的主要特点、总体结构和技术参数,详细说明了关键部件装煤斗的设计过程,并对安全制动系统、后轮辅助驱动系统、液压系统、电气系统等设计过程做了简单介绍。井下工业性试验结果表明,该运煤车性能可靠,能够满足连采工作面对运煤车辆的生产需求。

海洋石油平台钻修机防爆电气设备管理

防爆电气设备管理是石油工作的重点,但因海洋石油钻井平台所处环境温度大,空气潮湿、含盐量高,要求防爆电气设备具备极高的防腐等级和防护能力,并要求相关部门对平台上所使用的电气设备进行核查,并颁发防爆合格证。简要分析了钻修机防爆电气设备管理现状,明确了平台爆炸危险区的划分标准及具体内容,最后深入提出了海洋石油平台钻修机防爆电气设备管理措施,以期实现对防爆电气设备的高强度管控,防止爆炸事故发生。

水电工程石方洞挖数码电子雷管联网方案及耗量分析方法研究

自2021年在水电工程爆破开挖中强制推行应用数码电子雷管后,关于数码电子雷管的爆破联网设计方案、实际消耗量、成本分析等研究尚处于空白阶段。笔者从数码电子雷管与非电毫秒雷管爆破联网设计方案对比分析入手,研究两者的爆破联网方式差异,理论推导两者耗量调整系数。同时采用无约束支持向量机模型构建雷管耗量与岩石级别、开挖断面的函数关系,计算数码电子雷管替换非电毫秒雷管后的耗量调整系数,并采用单一变量试验验证计算数据的准确性。结果表明,实测数据结果与理论推导结果、数学模型分析结果保持一致,证明两种研究方法的可靠性。