煤尘组分对瓦斯/煤尘复合爆炸下限的影响研究

瓦斯和煤尘复合爆炸是煤矿井下爆炸灾害的主要形式之一,研究瓦斯/煤尘复合爆炸下限变化规律,是有效防治煤矿爆炸灾害的必备条件。为研究煤尘组分对瓦斯/煤尘复合爆炸下限的影响,特选用2种组分不同的煤尘(烟煤和无烟煤)。依据EN 14034标准,使用10 kJ化学点火头在标准20L球形爆炸容器中,分别对2种煤尘的最小爆炸浓度、相同试验条件下的瓦斯爆炸下限以及煤尘与瓦斯的复合爆炸下限进行了测量。试验测得烟煤和无烟煤的最小爆炸浓度分别为50 g/m^3和70 g/m^3,瓦斯爆炸下限为4%。当煤尘中分别通入1%、2%、3%、4%的瓦斯后,烟煤最小爆炸浓度分别降低至40、20、5、0 g/m^3,无烟煤最小爆炸浓度分别降低至50、20、5、0 g/m^3。基于上述测量结果,对比分析了煤尘组分对瓦斯/煤尘复合爆炸下限变化规律的影响,并探讨了Le Chatelier、Bartknecht、Jiang等气粉复合爆炸下限预测模型对瓦斯/煤尘复合体系的适用性。结果表明:2种煤尘的最小爆炸浓度均随瓦斯浓度的增大而降低,但挥发分含量低的煤尘降幅更大,即瓦斯对低挥发分煤尘最小爆炸浓度的影响更为显著。Jiang模型预测值远远偏离实际测量值;Le Chatelier模型预测值高于实际测量值,且误差随瓦斯浓度的增大而增大;Bartknecht模型适用性相对较好,且更适用于低挥发分瓦斯/煤尘复合体系。     

A novel PEM fuel cell remaining useful life prediction method based on singular spectrum analysis and deep Gaussian processes

Accurate remaining useful life (RUL) prediction of proton exchange membrane fuel cells (PEMFCs) can assess the reliability of fuel cells to determine the occurrence of failures and mitigate their operational risk. However, is it quite challenging to design a high-precision prediction method because the implicit degradation details of PEMFCs are difficult to learn well from the measurement data with high-frequency noise. Recognizing this, a novel RUL prediction method based on singular spectrum analysis (SSA) and deep Gaussian process (DGP) is proposed in this paper. The SSA-based method is firstly employed to preprocess the measurement data, which can strengthen the effective information of PEMFC degradation data at the same time remove the noise and spikes that interfere with degradation prediction. As a deep structural model, DGP has strong feature learning ability which can represent the nonlinear details of degradation data and give more accurate prediction results. At the same time, it serves as a probabilistic model that can provide the confidence interval to enhance reliability of RUL prediction. The effectiveness of the proposed method is evaluated by experimental data of the PEMFCs under steady-state conditions, and the results show that the SSA-DGP method has higher accuracy and reliability than conventional methods.     

Performance degradation prediction of proton exchange membrane fuel cell using a hybrid prognostic approach

The proton exchange membrane fuel cell has been widely used for industrial systems; however, its performance gradually degrades during use. Therefore, the study on the performance degradation prediction of fuel cells is helpful to extend its lifespan. In this paper, a novel hybrid approach using a combination of model-based adaptive Kalman filter and data-driven NARX neural network is proposed to predict the degradation of fuel cells. The overall degradation trend (i.e., irreversible degradation process) is captured by an empirical aging model and adaptive Kalman filter. Meanwhile, the detail degradation information (i.e., reversible degradation process) is depicted by the NARX neural network. Moreover, the correlation analysis of the reversible voltage time series is carried out to obtain the number of delays of the NARX neural network based on the autocorrelation function and the partial autocorrelation function. Then, the total degradation prediction is the sum of the overall degradation prediction and the detail degradation prediction. Finally, the prognostic capability of the proposed method is verified by two aging datasets, and the results show the effectiveness and superiority of the proposed method which can provide accurate degradation forecasting and remaining useful life.     

注塑机注射速度的模型预测控制及其仿真

注塑过程具有随机性、非线性以及时变性等特点,常规比例积分微分控制方法很难使注射速度控制达到理想的效果,为此提出了一种基于模型预测的注射速度控制方法。首先介绍了注塑机注塑工作原理,分析了注射速度控制系统,并通过模型预测算法得到当前采样时刻控制量以及下一时刻的控制量。仿真结果表明,基于模型预测的注射速度控制能够很好地跟踪快速变化的速度设定曲线,拥有较好的稳定性和抗干扰性。     

煤矿冲击矿压预测和防治技术浅析

结合镇城底煤矿22605工作面的地质情况和矿压情况,提出了煤炭生产中冲击矿压的预测和防治措施。通过对22605工作面的地质情况和监测数据分析处理并探究了该工作面矿压显现规律,为其设计了一套适合本工作面的冲击矿压监测和防治体系。防治体系有预防和临时解危双重防治措施,从这两方面考虑可以做到全面防治冲击矿压。该体系可以实现矿井的安全生产,保证工作人员的安全。另通过分析冲击矿压发生的基本原理和监测到的数据,建立煤矿冲击矿压防治体系,能够及时有效地将蕴含在煤体中的冲击矿压释放和消除,达到安全生产的目的。     

基于P波模量的原位胶结充填体强度预测模型研究

原位胶结充填体质量评价通常采用单轴抗压强度作为表征指标,由于在现场工程中无法快速、准确获取充填体的强度值,因此需要建立一种参数易于获取且准确的原位胶结充填体强度预测模型。基于胶结充填体物理力学参数的内在联系,从量纲平衡的角度探索了胶结充填体单轴抗压强度与P波模量的关系。根据C矿和I矿两种原位胶结充填体的密度、P波速度及取芯强度的测试数据,采用线性拟合的方法获得了基于P波模量的原位胶结充填体强度预测模型。通过对C矿和I矿的强度预测模型拟合效果分析可知,P波模量与取芯强度呈正相关性,且拟合效果较好,证明原位胶结充填体强度预测模型精度高,具有很强的实用性。     

非对称因素对热轧纯钛中厚板出口楔形的影响

针对纯钛中厚板热轧过程中可能出现的轧件断面楔形问题,结合四辊轧机设备和工艺的非对称特点,基于影响函数法建立双悬臂梁辊系弹性变形模型,研究对中误差、机架刚度差、坯料楔形、横向温差等非对称因素对轧件断面楔形的影响。结果表明对中误差、机架刚度差、横向温差对出口楔形的影响随着板宽和压下量的增大而增大,入口楔形对出口楔形的影响随着板宽增大和压下量的减小而增大。     

高碱煤燃烧过程中碱金属沾污特性的预测模型研究

为了克服传统预测方法的局限性,笔者提供了一种能够准确预测高碱煤燃烧沾污特性的模型,该预测模型还可以根据煤的沾污特性给出其适用的温度范围。本预测模型采用三步化学萃取法来检测煤样中的钠含量,以避免对煤进行灰化时造成钠的挥发损失,因此能够直接精确地测定煤样中的总钠含量及各个形态的钠含量。另外,本预测模型不仅考虑钠、钾和固相沾污源的影响,同时考虑到其它易挥发组分(如碱土金属、硫和氯)对煤沾污特性的影响,并将温度引入沾污模型中。按本模型获得的沾污指数R_T预测量化区间如下:R_T≤0.60,弱沾污性;0.601.00,强沾污性。为验证该预测模型的准确性,分别以沙尔湖煤和神华准东煤为试验对象对预测模型进行了验证,验证结果表明:①700℃时,R_T=0.59<0.60,沙尔湖煤处于弱沾污区;850℃时,0.601.0,沙尔湖煤处于强沾污区。②神华准东煤相比于沙尔湖煤沾污性较弱。850℃时,R_T=0.53<0.60,神华准东煤处于弱沾污区;900℃时,0.60相似文献   

综合物探方法在天然气高瓦斯隧道超前地质预报中的应用

天然气高瓦斯隧道中的瓦斯不可预见性很大。施工过程中，在遇到隧道洞身段局部岩体节理裂隙发育、围岩破损带、断层处，均可能发生瓦斯逸出甚至瓦斯突涌现象，现场存在很大的瓦斯安全隐患。主要研究了TSP探测、地质雷达、超前钻探等方法在瓦斯隧道施工中的应用情况，多种物探手段与钻探相结合对不良地质体进行综合预测，取得了较好的预报效果，有力保障了现场施工安全。     

综机设备集中化管理实践

综机设备是煤矿采掘生产效率的重要支撑，如果没有先进的综机设备，要想提高采掘生产效率是不可能的。从综机设备集中化和综机设备检修的专业化，分别阐述了其发展趋势，简要总结了中煤新集多年的实践经验，并针对目前管理存在的问题提出相应的建议。