HYBRID CONTROL OF HYDRAULIC PRESS MACHINE BASED ON ROBUST CONTROL

A robust control algorithm is proposed to focus on the non-linearity and variables of the hydraulic press machine with the proportional vatve. The proposed robust controller does not need to design stable compensator in advance, which is simple in design and has large scope of uncertainty applications. The feedback gains of the proposed robust controller are small, so it is easily implemented in engineering applications. The theoretical and experimental research on the position and speed control of the hydraulic press machine is carried out. The control requirements of the hydraulic press machine during the working process are met in the position and speed at the same time. Experimental results show that the proposed controller has better robustness subject to load variables and adaptability of parameter variations of the hydraulic press machine with the proportional valve.

Reliability Analysis of Heavy-Duty CNC Machine Hydraulic System Based on Fuzzy Goal Oriented Method

There is a common sense that heavy-duty CNC machine strongly depends on its foundation and can be easily affected by many factors.Hydraulic system,the most important part in CNC machine,is a complex and multi-loop system.In order to make up for the shortcomings of traditional fault tree analysis method and traditional GO method,the most effective method named fuzzy GO method is proposed to analyze the reliability of hydraulic system.And then some ideas are provided for system reliability assessment,fault diagnosis and maintenance by qualitative and quantitative analysis.

A soft-sensing model on hydraulic excavator's backhoe vibratory excavating resistance based on fuzzy support vector machine

In order to measure the backhoe vibratory excavating resistance of a hydraulic excavator fast and precisely,the influences of vibratory excavating depth,angle,vibratory frequency,amplitude,bucket inserting velocity and soil type on the vibratory excavating resistance were analyzed.Simulation analysis was carded out to establish the bucket inserting velocity,amplitude and vibratory frequency considered as secondary variables and excavating resistance as primary variable.A fttzzy membership function was introduced to improve the anti-noise capacity of support vector machine,which is a soft-sensing model on the hydraulic excavator＇s backhoe vibratory excavating resistance based on fuzzy support vector machine.The simulation result reveals that its maximum relative training and testing error are nearly 0.68% and-0.47%,respectively.It is concluded that the model has quite high modeling precision and generalization capacity,and it can measure the vibratory excavating resistance accurately,reliably and fast in an indirect way.

A machine learning-based study of multifactor susceptibility and risk control of induced seismicity in unconventional reservoirs

A comprehensive dataset from 594 fracturing wells throughout the Duvernay Formation near Fox Creek, Alberta, is collected to quantify the influences of geological, geomechanical, and operational features on the distribution and magnitude of hydraulic fracturing-induced seismicity. An integrated machine learning-based investigation is conducted to systematically evaluate multiple factors that contribute to induced seismicity. Feature importance indicates that a distance to fault, a distance to basement, minimum principal stress, cumulative fluid injection, initial formation pressure, and the number of fracturing stages are among significant model predictors. Our seismicity prediction map matches the observed spatial seismicity, and the prediction model successfully guides the fracturing job size of a new well to reduce seismicity risks. This study can apply to mitigating potential seismicity risks in other seismicity-frequent regions.

基于FluidSIM-Hydraulic的注塑机液压回路控制分析

基于FluidSIM-Hydraulic软件对注塑机液压回路控制系统进行分析。介绍了注塑机的结构原理,并优化设计了液压回路及电气控制系统,通过二者有效的结合成功地将模拟仿真后的模型应用到了实际生产中,取得了良好的效果。

基于MATLAB/SimHydraulics的型材冷弯回路仿真分析

介绍了型材冷弯机的液压系统工作原理,利用MATLAB/SimHydraulics工具箱内液压元器件模型,对冷弯机液压系统主回路进行了实物仿真研究,得出主缸受力、活塞杆速度和位移响应曲线、油液流量变化等性能曲线。结果表明SimHydraulics在冷弯机液压回路研究中具有可行性,为其他液压系统回路仿真研究提供了一种参考。

基于MATLAB/SimHydraulics的全自动铝棒冷剪机液压系统仿真分析

介绍一种全自动铝棒冷剪机的液压系统及工作过程,为了全面了解该设备液压系统各工作过程的动态参数,采用MATLAB/Simulink软件对该设备液压系统进行建模、仿真,获得了各液压缸的动态曲线,为该设备液压元件参数的确定提供了参考意见,经验证参数切实可行,动态性能与仿真一致,为类似的液压系统设计提供了参考。

Nonlinear Static and Dynamic Stiffness Characteristics of Support Hydraulic System of TBM

Full-face hard rock tunnel boring machines(TBM)are essential equipment in highway and railway tunnel engineering construction.During the tunneling process,TBM have serious vibrations,which can damage some of its key components.The support system,an important part of TBM,is one path through which vibrational energy from the cutter head is transmitted.To reduce the vibration of support systems of TBM during the excavation process,based on the structural features of the support hydraulic system,a nonlinear dynamical model of support hydraulic systems of TBM is established.The influences of the component structure parameters and operating conditions parameters on the stiffness characteristics of the support hydraulic system are analyzed.The analysis results indicate that the static stiffness of the support hydraulic system consists of an increase stage,stable stage and decrease stage.The static stiffness value increases with an increase in the clearances.The pre-compression length of the spring in the relief valve a ects the range of the stable stage of the static stiffness,and it does not a ect the static stiffness value.The dynamic stiffness of the support hydraulic system consists of a U-shape and reverse U-shape.The bottom value of the U-shape increases with the amplitude and frequency of the external force acting on the cylinder body,however,the top value of the reverse U-shape remains constant.This study instructs how to design the support hydraulic system of TBM.

Spatial-temporal evolution of injection-induced earthquakes in the Weiyuan Area determined by machine-learning phase picker and waveform cross-correlation

Anthropogenic induced seismicity has been widely reported and investigated in many regions,including the shale gas fields in the Sichuan basin,where the frequency of earthquakes has increased substantially since the commencement of fracking in late 2014.However,the details of how earthquakes are induced remain poorly understood,partly due to lack of high-resolution spatial-temporal data documenting the evolution of such seismic events.Most previous studies have been based on a diffusive earthquake catalog constructed by routine methods.Here,however,we have constructed a high resolution catalog using a machine learning detector and waveform cross-correlation.Despite limited data,this new approach has detected one-third more earthquakes and improves the magnitude completeness of the catalog,illuminating the comprehensive spatial-temporal migration of the emerging seismicity in the target area.One of the clusters clearly delineates a potential unmapped fault trace that may have led to the Mw 5.2 in September 2019,by far the largest earthquake recorded in the region.The migration of the seismicity also demonstrates a pore-pressure diffusion front,suggesting additional constraints on the inducing mechanism of the region.The patterns of the highly clustered seismicity reconcile the causal link between the emerging seismicity and the activity of hydraulic fracturing in the region,facilitating continued investigation of the mechanisms of seismic induction and their associated risks.

Safety evaluation system for hydraulic metal structures based on knowledge engineering

A comprehensive safety evaluation system taking the most influential factors into account has been developed to evaluate the reliability of hydraulic metal structures. Applying the techniques of AI and DB, the idea of a one-machine and three-base system is proposed. The framework of the three-base system has been designed and the structural framework constructed in turn. A practical example is given to illustrate the process of using this system and it can be used for comparison and analysis purposes. The key technology of the system is its ability to reorganize and improve the expert system＇s knowledge base by establishing the expert system. This system utilizes the computer technology inference process, making safety evaluation conclusions more reasonable and applicable to the actual situation. The system is not only advanced, but also feasible, reliable, artificially intelligent, and has the capacity to constantly grow.

Studying the direction of hydraulic fracture in carbonate reservoirs:Using machine learning to determine reservoir pressure

Hydraulic fracturing(HF)is an effective way to intensify oil production,which is currently widely used in various conditions,including complex carbonate reservoirs.In the conditions of the field under consideration,the hydraulic fracturing leads to a significant differentiation of technological efficiency indicators,which makes it expedient to study the patterns of crack formation in detail.Studies were carried out for all wells,which were considered as the objects of impact,to assess the spatial orientation of the cracks formed.The developed indirect method was used for this purpose,the reliability of which was confirmed by geophysical methods.During the analysis,it was found that in all cases,the crack is oriented in the direction of the section of the development system element characterized by the maximum reservoir pressure.At the same time,the reservoir pressure values for all wells were determined at one point in time(at the beginning of HF)using machine learning methods.The reliability of the machine learning methods used is confirmed by the high convergence with the actual(historical)reservoir pressures obtained during hydrodynamic studies of wells.The obtained conclusion about the influence of the reservoir pressure on the patterns of fracture formation should be taken into account when planning hydraulic fracturing under the conditions studied.

综采液压支架中部跟机多模态人机协同控制系统

我国煤矿智能化综采工作面建设处于初级阶段,液压支架电液控自动化技术已广泛应用,但目前液压支架单一固化的自动化控制逻辑难以适应复杂、多变、动态的工作面生产场景,现场实际控制过程仍大多采用自动化+人工干预方式。针对综采工作面复杂场景中液压支架人机交互协作任务需求,提出液压支架中部跟机多模态人机协同控制系统的理论方法与技术原理。首先,设计了人工式、分工式、批准式、否决式4种人机协同模态,以煤层地质、瓦斯粉尘、采煤机速度、液压支架智能水平、系统状态、岗位工技术水平、任务负荷等为判别因素,构建了基于AOG的液压支架人机协同模态选择模型,实现了人工、机器偏好的模态选择。然后,设计了液压支架中部跟机人机协同控制决策机制,提出液压支架中部跟机再次调控策略AI推理技术思路,利用现场数据学习人工操作经验,分别构建了液压支架是否再次调控决策树分类模型和再次拉架时间贝叶斯回归模型,基于上述模型开发了液压支架人机协同控制决策程序,实现了基于多模态与或推理和再次调控策略AI推理的液压支架人机协同控制。最后,采用云-边-端架构软硬件技术,开发了液压支架多模态人机协同控制系统,实现了模型进化、运算推理、程序执行等液压支架多模态人机协同控制功能。该系统在沙曲二矿3404工作面进行了工业试运行,相比于系统使用前,该工作面液压支架中部跟机效率平均提高2%。

盐冻耦合作用下水工混凝土耐久性及寿命预测

为研究西北地区冻融盐侵环境下水工混凝土的耐久性,制备了不同粉煤灰掺量的混凝土试件,以不同浓度的硫酸钠溶液作为介质开展了冻融循环试验,阐明了不同循环次数下试件的外观、质量、抗压强度和动弹模量的变化规律,基于XGBoost模型建立了混凝土寿命预测模型并对其进行了评价和验证。研究结果表明,随着冻融循环次数增加,混凝土质量、抗压强度和动弹模量逐渐减小;冻融循环次数和硫酸钠溶液浓度是影响混凝土寿命的关键因素,8%硫酸钠溶液破坏度最高,此溶液浓度下冻融150次后混凝土质损率达4.55%;粉煤灰的掺入量对混凝土耐久性有一定影响;最优粉煤灰掺量为10%,此掺量下冻融150次后混凝土质损率为3.99%;XGBoost模型在混凝土寿命预测方面具有较高的精确性和可靠性。本研究可为混凝土结构的耐久性设计和寿命预测提供参考。

机液串联式钻机推进系统设计与仿真分析

针对工程钻机推进系统存在的行程大而造成体积和质量大的问题,基于其工作机制进行研究,提出一种机液串联式的钻机推进系统,详细阐述了其工作原理,推导了钻机推进位移与电液比例阀阀门开度的函数关系式。理论分析和仿真验证表明:机液串联式的推进系统具有省距不省力的特点;在钻机工作过程中,动力头的推进速度和位移可达到液压油缸的2倍,液压油缸传递至动力头的推进力为液压油缸活塞输出力的一半,从而减少了钻机桅杆的长度,降低了推进系统的体积和质量;通过电液比例阀调节阀门开度,可以调节动力头的推进位移和速度,使得钻机推进系统满足不同工况的需求。

基于对比学习的电液转辙机故障智能诊断方法

道岔转辙机是铁路运行调度的关键设备,由于其外部使用环境恶劣、内部设备结构复杂,使得转辙机在工作过程中容易产生不同的运行故障。针对广泛应用于高速铁路的电液转辙机,提出基于对比学习的电液转辙机故障智能诊断方法:对电液转辙机左右液压缸油压监测信号使用对比学习的思想正则化特征空间;使用实例级权重策略增强模型泛化能力;使用多种数据增强方法提高模型鲁棒性。最后通过电液转辙机的运行故障实验验证本方法的有效性与优越性。

基于PSO−ELM的综采工作面液压支架姿态监测方法

针对基于惯性测量单元的液压支架姿态解算方法会产生累计误差、校正结果不准确的问题,提出一种基于粒子群优化(PSO)−极限学习机(ELM)的综采工作面液压支架姿态监测方法。以液压支架顶梁俯仰角为监测对象,采用倾角传感器和陀螺仪采集液压支架顶梁支护姿态实时信息,对采集到的数据进行预处理,将处理后的数据输入PSO−ELM误差补偿模型中,得到解算误差预测值;同时通过卡尔曼滤波融合进行液压支架姿态解算,得到解算值;再用误差预测值对解算值进行误差补偿,从而求得更加准确的顶梁支护姿态数据。该方法只考虑加速度和角速度数据与解算误差的关系,不依赖具体的物理模型,可有效降低姿态解算累计误差。实验结果表明:液压支架顶梁俯仰角平均绝对误差由补偿前的1.4208°减少到0.0580°,且误差曲线具有良好的收敛性,验证了所提方法可持续稳定地监测液压支架的支护姿态。

基于STM32的动态注塑信号调节器设计

文中设计了一种基于STM32芯片与UCOSIII操作系统的动态注塑信号调节器。采用DDS芯片AD9833与数字电位器MCP41010配合实现了P/Q信号的发生与调幅;采用运算放大器OP07组成的加法器实现P/Q振动信号与P/Q静态信号的合成;基于RS485接口与Modbus通讯协议实现动态注塑信号调节器与上位机的实时通讯;基于emWin图形库设计了人机交互界面,可以在触摸屏上设定选定注塑参数。试验测试表明:动态注塑信号调节器能够根据上位机反馈的通讯信息在不同工序下输出不同波形、频率与幅值的P/Q动态注塑信号,满足泵控液压激振系统与动态注塑的应用需求。

基于神经网络的液压机状态监测系统研究

神经网络是一种类似于人类神经系统的人工智能模型,利用神经网络可以对传统的监测数据进行组合和筛选,以提高故障检测的准确度。为提升液压机状态监测系统的故障评估性能,利用基于神经网络的机器学习方法的优势,提出一种设备状态监测解决新方案。对大量数据进行神经网络模型训练及特征提取,从而实现对液压机监测系统故障的准确识别。

水工结构变形预测模型构建与解释

现有基于机器学习算法的水工结构安全监控模型结果的可解释性较差。为提高安全监控模型的可解释性,发展一种基于集成学习算法的水工结构变形预测模型构建与解释方法。简述改进统计模型及随机森林(RF)、极端梯度提升树(XGBoost)两种常用的集成学习算法,引入沙普利值可加性解释(SHAP)方法实现集成学习算法模型结果的可解释性,阐述SHAP方法的原理和推导过程。以某运行初期特高拱坝变形数据为例验证方法的有效性和实用性。结果表明,XGBoost模型具有较高的预测精度,预测集决定系数大于0.982,改进统计模型精度次之,RF模型精度相对较低;SHAP方法可以分离不同自变量对效应量的影响大小,并能给出全局和局部的影响机制,实现模型拟合和预测结果的可解释性。提出的方法综合了“机理驱动”和“数据驱动”模型的优势,可为水工结构运行管理提供决策参考。

盾构螺机后仓门液压系统仿真控制研究

针对传统盾构螺旋输送机后仓门紧急关闭过程中液压系统流量大小不稳定及油缸和蓄能器关键参数设置不合理而易引起液压冲击,造成机械部件损伤等缺陷。提出一种带压力补偿的插装式比例流量阀控制系统流量大小。通过分析其结构组成及原理,建立了该阀AMEsim模型,并对模型仿真特性曲线进行了分析,得出其有较好的流量稳定性,控制精度高、动态响应性好,且利用仿真环境建立了螺机后仓门液压系统的AMEsim模型,分析了系统中蓄能器与液压缸的关键参数对后仓门紧急关闭的影响规律,结合该影响规律及比例流量阀的工作特性,为螺机后仓门液压系统的进一步升级改造提供理论依据。