Late Quaternary Large Earthquakes on the Western Branch of the Xiaojiang Fault and Their Tectonic Implications

The Xiaojiang fault is a major active left-lateral fault along the southeastern margin of the Tibetan Plateau.The largest historical earthquake in Yunnan Province, with a magnitude 8 and a mean coseismic left-lateral displacement of ~ 6.9 m, occurred on the western branch of the Xiaojiang fault.Studying this fault is important in understanding current deformation and kinematic characteristics of the Tibetan Plateau.Activities and stretches have been well undertaken on the Xiaojiang fault, while paleoseismic research work is always the weak link on this fault.To investigate the paleoseismic history and large earthquake activity of the Xiaojiang fault, we opened a large trench at the northern edge of Caohaizi sag pond on the western branch of the Xiaojiang fault.Six paleoseismic events have been identified, and named E1 through E6 from the oldest to the youngest.Charcoal and woods are abundant, 20 samples were dated to constrain the ages of the paleoseismic events at 40 000–36 300 BC, 35 400–24 800 BC, 9 500 BC–AD 500, AD 390–720, AD 1120–1620 and AD 1750–present.We associate the youngest event E6 with the 1833 M8 earthquake.Events E4, E5 and E6 show a continuous record of the western strand of the Xiaojiang fault in the late Holocene, with a average recurrence interval of 370–480 yr.Large earthquake recurrence in the late Holocene is far less than the recurrence of 2000–4000 yr posed in previous studies.Thus, the seismic hazard on the Xiaojiang fault should be reevaluated.Furthermore, the irregular recurrence of large earthquakes on the Xiaojiang fault and other faults in the Xianshuihe-Xiaojiang system, indicates the uneven southeastward extrusion of the Sichuan-Yunnan block along the southeastern margin of the Tibetan Plateau.

Static-deformation based fault diagnosis for damping spring of large vibrating screen

Based on the statics theory, a novel and feasible twice-suspended-mass method(TSMM) was proposed to deal with the seldom-studied issue of fault diagnosis for damping springs of large vibrating screen(LVS). With the static balance characteristic of the screen body/surface as well as the deformation compatibility relation of springs considered, static model of the screen surface under a certain load was established to calculate compression deformation of each spring. Accuracy of the model was validated by both an experiment based on the suspended mass method and the properties of the 3D deformation space in a numerical simulation. Furthermore, by adopting the Taylor formula and the control variate method, quantitative relationship between the change of damping spring deformation and the change of spring stiffness, defined as the deformation sensitive coefficient(DSC), was derived mathematically, from which principle of the TSMM for spring fault diagnosis is clarified. In the end, an experiment was carried out and results show that the TSMM is applicable for diagnosing the fault of single spring in a LVS.

Design on Vibration Monitoring and Fault Diagnosis System of Large Water Pump Motor

Large water pump motor,whose operation decides the reliability of the whole production line,plays a very important role.Therefore,its online condition monitoring can help companies better know its operation,process fault analysis and protection.The essay mainly studies and designs large water pump motor′s real time vibration monitoring and fault diagnosis system.The essay completes the systems project design,the establishment of the system and performance test.Eddy-currentsensor,XM-120 vibration module,XM-320 axial translation module,XM-362 temperature module,XM-360 process amount module and XM-500 gateway module are used to measure the axial vibration and displacement of main motors.Laboratory tests prove that the system can meet the requirements of motor vibration monitoring.

LARGE-SCALE STRAIN PATTERNS,GREAT EARTHQUAKE BREAKS,AND LATE PLEISTOCENE SLIP-RATE ALONG THE ALTYN TAGH FAULT (CHINA)

Fieldwork along several segments of the Altyn Tagh Fault,between 85 and 95°E,confirms that it ranks as one of the most active faults of Asia.In the East,near Aksay,the active fault trace offsets numerous stream channels,terrace risers and fans tens to hundreds of meters. 14 C dating of organic remains and charcoal within terrace gravels indicates that most of the terraces were emplaced after the beginning of the Holocene,implying a left\|slip rate of about 2cm/a.Large mole tracks attest to the occurrence of great earthquakes.Even larger mole tracks are found north of Lenghu,within the Altun Shan push\|up,a 6000 m high range in a restraining bend of the fault,now sliced by its most active strand.North of Huatougou,at the transition between another push\|up mountain and a recent pull\|apart basin,a spectacular sequence of five flat\|floored,hanging channels,beheaded by the fault from a unique source in the mountain,have been horizontally displaced by up to 1250m.Cosmogenic dating of the abandonment of these channels and of nearby offset terrace risers confirms the slip\|rate at Aksay.Several km to the west,pressure ridges exceeding 10m in height across a large young fan,imply the repeat of several great earthquakes in a relatively short time span.

A prediction method of operation trend for large axial-flow fan based on vibration-electric information fusion

As the critical equipment,large axial-flow fan(LAF)is used widely in highway tunnels for ventilating.Note that any malfunction of LAF can cause severe consequences for traffic.Specifically,fault deterioration is suppressed tremendously when an abnormal state is detected in the stage of early fault.Thus,the monitoring of the early fault characteristics is very difficult because of the low signal amplitude and system disturbance(or noise).In order to overcome this problem,a novel early fault judgment method to predict the operation trend is proposed in this paper.The vibration-electric information fusion,the support vector machine(SVM)with particle swarm optimization(PSO),and the cross-validation(CV)for predicting LAF operation states are proposed and discussed.Finally,the results of the experimental study verify that the performance of the proposed method is superior to that of the contrast models.

North slope transition zone of Songnan-Baodao sag in Qiongdongnan Basin and its control on medium and large gas fields,South China Sea

Based on analysis of newly collected 3D seismic and drilled well data,the geological structure and fault system of Baodao sag have been systematically examined to figure out characteristics of the transition fault terrace belt and its control on the formation of natural gas reservoirs.The research results show that the Baodao sag has the northern fault terrace belt,central depression belt and southern slope belt developed,among them,the northern fault terrace belt consists of multiple transition fault terrace belts such as Baodao B,A and C from west to east which control the source rocks,traps,reservoirs,oil and gas migration and hydrocarbon enrichment in the Baodao sag.The activity of the main fault of the transition belt in the sedimentary period of Yacheng Formation in the Early Oligocene controlled the hydrocarbon generation kitchen and hydrocarbon generation potential.From west to east,getting closer to the provenance,the transition belt increased in activity strength,thickness of source rock and scale of delta,and had multiple hydrocarbon generation depressions developed.The main fault had local compression under the background of tension and torsion,giving rise to composite traps under the background of large nose structure,and the Baodao A and Baodao C traps to the east are larger than Baodao B trap.Multiple fault terraces controlled the material source input from the uplift area to form large delta sand bodies,and the synthetic transition belt of the west and middle sections and the gentle slope of the east section of the F12 fault in the Baodao A transition belt controlled the input of two major material sources,giving rise to a number of delta lobes in the west and east branches.The large structural ridge formed under the control of the main fault close to the hydrocarbon generation center allows efficient migration and accumulation of oil and gas.The combination mode and active time of the main faults matched well with the natural gas charging period,resulting in the hydrocarbon gas enrichment.Baodao A transition belt is adjacent to Baodao 27,25 and 21 lows,where large braided river delta deposits supplied by Shenhu uplift provenance develop,and it is characterized by large structural ridges allowing high efficient hydrocarbon accumulation,parallel combination of main faults and early cessation of faulting activity,so it is a favorable area for hydrocarbon gas accumulation.Thick high-quality gas reservoirs have been revealed through drilling,leading to the discovery of the first large-scale gas field in Baodo 21-1 of Baodao sag.This discovery also confirms that the north transition zone of Songnan-Baodao sag has good reservoir forming conditions,and the transition fault terrace belt has great exploration potential eastward.

Fault diagnosis method of link control system for gravitational wave detection

To maintain the stability of the inter-satellite link for gravitational wave detection,an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed.Different from the traditional fault diagnosis optimization algorithms,the fault intelligent learning method pro-posed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong cou-pling nonlinearity.By constructing a two-layer learning network,the method enables efficient joint diagnosis of fault areas and fault parameters.The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s,and the fault diagnosis efficiency is improved by 99.8%compared with the traditional algorithm.

Fault Detection and Test Response Compaction with Array of Two-Input Linear Logic

The design of space-efficient support hardware for built-in self-testing is of great significance in very large scale integration circuits and systems, particularly in view of the paradigm shift in recent times from system-on-board to system-on-chip technology. The subject paper proposes a new approach to designing aliasing-free or zero-aliasing space compaction hardware targeting specifically embedded cores-based system-on-chips for single stuck-line faults extending well-known concept from conventional switching theory, viz. that of compatibility relation as used in the minimization of incomplete sequential machines. For a pair of response outputs of the circuit under test, the method introduces the notion of fault detection compatibility and conditional fault detection compatibility （conditional upon some other response output pair being simultaneously fault detection compatible） with respect to two-input XOR/XNOR logic. The process is illustrated with design details of space compressors for the International Symposium on Circuits and Systems or ISCAS 85 combinational and ISCAS 89 full-scan sequential benchmark circuits using simulation programs ATALANTA and FSIM, attesting to the usefulness of the technique for its relative simplicity, resultant low area overhead and full fault coverage for single stuck-line faults, thus making it suitable in commercial design environments.

井下断层活动的定量监测及其对冲击地压的影响研究

为建立断层活动与冲击地压之间的定量关系,实现煤矿冲击地压有效防控。通过理论分析义马矿区地质构造环境,以及耿村煤矿13200工作面与断层影响带的相对位置关系,研究了断裂构造对冲击地压的宏观控制作用。计算了井田构造应力并进行了构造应力区划分,分析了构造应力分区对冲击地压的控制作用。提出了井下断层活动性的定量监测方法,构建了“震源区煤岩体与动力核区尺度等量,震源能量随传递距离逐渐衰减”的模型,建立了大能量微震事件与断层活动的关系,确定了断层活动性对冲击地压的影响。研究结果表明:义马煤田内相对复杂的逆冲推覆构造体系,构成了义马矿区冲击地压的地质构造背景条件。F_(16)断层的影响带范围为7000~7600 m,13200工作面全部处于F_(16)断层的影响带内,在开采活动的影响下进一步增大了冲击地压的发生危险。Ⅰ-2断裂、Ⅲ-4断裂和Ⅳ-7断裂等控制的区域是冲击地压和大能量微震事件显现的主要区域,且冲击地压和大能量微震事件大多位于应力梯度区范围内。在大能量微震事件孕育和发生期间,F_(16)断层位移分别增长50 mm和45 mm;大能量微震事件发生前,断层活动拉力的增幅均相对最高,分别为2.58 kN和2.93 kN,断层位移量的快速增加和较高的应力增幅构成了大能量微震事件的主要能量来源。表明大能量微震事件和冲击地压的发生均与断层的活动联系紧密。井下断层的实际定量监测方法可以广泛应用于矿井冲击地压预测与防控的指导工作中。

Active Probing Based Method for Fault Diagnosis Using Bayesian Network

Fault diagnosis on large-scale and complex networks is a challenging task, as it requires efficient and accurate inference from huge data volumes. Active probing is a cost-efficient tool for fault diagnosis. However almost all existing probing-based techniques face the following problems: 1) performing inaccurately in noisy networks; 2) generating additional traffic to the network; 3) high cost computation. To address these problems, we propose an efficient probe selection algorithm for fault diagnosis based on Bayesian network. Moreover, two approaches which could significantly reduce the computational complexity of the probe selection process are provided. Finally, we implement the new proposed algorithm and a former representative probing-based algorithm (BPEA algorithm) on different settings of networks. The results show that, the new algorithm performs much faster than BPEA does without sacrificing the diagnostic quality, especially in large, noisy and multiple-fault networks.

四川康定—磨西断裂强震危险背景研究

本文对四川西部鲜水河断裂带上的康定—磨西断裂的强震危险性作了分析探讨。该断裂位于川西—滇东第Ⅲ弧形挤出构造带的弧顶转折部位,这里应力高度集中,块体左旋大幅度滑移,断裂两侧垂直差异运动幅度达1000~2000 m,为大陆板块内部断裂活动性较高的地震区。鲜水河断裂带是我国地震活动性和重复性都很高的一条左旋走滑断裂带,自1725年至今接近300年的时间里,鲜水河断裂带上重复出现了2期地震活动,地震重复周期为100~200年。康定—磨西断裂于1786年发生过7¾级大地震,此地震发生迄今已237年,断裂一直处于能量积累的相对平静期。近期地震活跃起来,2022年9月6.8级四川沪定磨西地震以后5.6级以下的中小震频繁发生,并沿着磨西断裂成带分布,是否预示着该断裂又重新活动起来,进入新的地震活动期?这些特征表明康定—磨西断裂具有大地震孕育发生的背景条件。

NPR锚索对跨断层软岩大变形隧道控制技术研究

为探究NPR锚索对东马场跨断层软岩大变形隧道控制效果,首先对NPR锚索进行静力拉伸试验,验证其恒阻大变形的能力和具有良好的抵御外力的效果;随后开展NPR锚索对东马场隧道围岩变形控制的三维物理模型试验。试验现象和数据表明:在开挖过程中,隧道围岩也没有出现较大垮落和坍塌,NPR锚索对软岩隧道围岩有较好的支护效果。在加载完成后,NPR锚索对非断层处的隧道围岩最大位移约为14 mm,断层处的围岩最大位移约为21 mm,隧道区域所受应力分布的不规律性,导致隧道围岩出现挤压变形,位移曲线呈振荡状。在NPR锚索的支护下,围岩应力最大发生在左拱肩,围岩临空面3 cm处切应力最大(0.3 MPa),隧道未出现大规模的不对称破坏现象,隧道总体呈现出“小塌而不垮”,变形总体可控。

穿断层破碎带隧道围岩大变形控制双梯度注浆机制

近些年,中国西部大量深埋隧道工程因关键线路控制无法避让一些活动性断裂,常常在跨越断裂带范围内出现围岩大变形破坏现象,例如侵限、偏压、塌方、底鼓等灾害,严重影响隧道工程施工和运营的安全可持续发展。为了控制断层破碎带隧道围岩大变形,隧道工程设计者和建设者采用了多种控制方案,例如超前注浆、多层钢拱架被动支护、锚杆索主动支护等,但是都因断层破碎带围岩强度过低而出现超前注浆诱发围岩拉裂破碎、主动支护锚杆锚固力不足等现象。为解决上述难题,首先,提出一种增强穿断层破碎带隧道围岩强度的双梯度注浆技术,建立双梯度注浆概念模型,构建3种双梯度注浆模式;然后,确定特定工况下注浆材料粒径梯度与注浆压力梯度的适配条件;最后,通过理论分析、物理模型试验和现场试验,探索双梯度注浆机制及其控制效果。研究结果表明:1)随着开挖步序的增加,穿断层破碎带隧道拱肩变形最大,构造应力对围岩稳定性影响较大。2)在双梯度注浆作用下,浆液扩散效果良好,围岩未出现大面积脱落破坏,隧道周围岩体应力分布均匀。3)双梯度注浆形成了坚硬交叉浆脉骨架,达到了应力补偿效果,将围岩变形量从原来的3 100 mm控制到278 mm以内,实现了“零换拱、零侵限、零突涌”的目标。

基于时序卷积残差网络和鹈鹕优化算法的新能源电网安全稳定控制方法

随着“双碳”目标的推进,随机波动的新能源接入电网的规模和容量日益提升,严重影响电网的安全稳定运行。针对大干扰故障电压稳定控制问题,文章提出了一种基于时序卷积残差网络和鹈鹕优化算法的新能源电网电压安全稳定控制策略。首先,利用时序卷积信息损失少、感受野宽以及残差网络深层特征提取能力强的优势,构建基于时序卷积残差网络的电压稳定预测模型,映射出敏感节点电压时序特征和电压稳定之间的关系;其次,构建电压稳定控制模型,利用鹈鹕优化算法收敛速度快、搜索能力强的优势求解控制模型,得出最佳切机和切负荷动作措施;最后,进行了仿真验证。验证结果表明,所提方法提高了新能源电网电压安全稳定预测的准确性,通过最佳的电压稳定控制策略提高了电网故障后的安全稳定运行水平。

复杂大电网非预设性运行工况下的继电保护动作适应性仿真分析

非预设性运行工况下的突发事件多,导致继电保护逻辑的适应性较差,不合理区域较多,为此,进行复杂大电网非预设性运行工况下继电保护动作适应性仿真分析。分析历史常规故障,标记故障点最常发生位置,构建零序、负序方向元件模型、距离元件模型、纵联电流差动元件模型,观察复杂大电网非预设性运行工况下的电网参数变化情况,第一时间掌握电网的耦合性,不断选择电网所需的继电保护动作逻辑,确认继电保护动作适应性。仿真实验表明,将故障点设置在保护区域内和区域外,继电保护动作能够根据故障选择不同保护模型进行故障母线切除或者保护不动作,适应性好。

活动断裂带大调整量无砟轨道设计与试验研究

研究目的:为满足跨活动断裂带线路铺设无砟轨道需求,提升该地区无砟轨道的线路平顺性与舒适性,提出一种大调整量活动承轨台式无砟轨道。采用ANSYS有限元软件建立整体和轨枕局部有限元模型,分析活动承轨台式无砟轨道的受力特性,在此基础上进行大调整量无砟轨道结构参数优化研究以及疲劳试验研究,分析结构刚度、位移和应变变化情况。研究结论:(1)活动承轨台式无砟轨道在列车荷载与温度荷载叠加作用下,最大拉应力出现在轨枕位置,为3.47 MPa,各部件应力均满足强度要求且在轨枕尺寸和材料优化后进一步降低;(2)疲劳试验中随着疲劳加载次数增加,结构横、纵向刚度在疲劳前后变化分别为3.4%和24.2%,结构应变小幅增加,未见塑性变形与明显损伤;(3)仿真与试验结果可为活动断裂带地区无砟轨道设计提供参考和借鉴。

稠油开采注汽锅炉在线综合预警关键技术

为了对工作在高温高压下注汽锅炉的各项运行参数进行在线准确监测和异常预警,本文在对稠油开采注汽锅炉工况参数进行采集、处理、分析的基础上,提出对注汽锅炉显性故障和隐性故障进行检测的方案。采用长期短期记忆神经网络,利用锅炉的时序数据对系统进行分析和建模,完成锅炉显性故障检测和预警,并通过预测数据的方式缓解锅炉大时滞的特性;利用深度异常检测技术,将无故障判别标准的数据进行隐性故障分析和预警。本文提出的综合预警方案对克拉玛依油田注汽锅炉进行了实验验证,预测误差仅有0.08%,同时异常检测范围也在设定值范围内。

基于关联规则的油田大型机泵设备振动故障数据采集方法

为了在不同工况下获取完整的振动故障数据,设计关联规则的油田大型机泵设备振动故障数据采集方法.提取大型机泵设备振动故障数据特征,在数据标准阈值中设定预警值与报警值,获取故障数据的全频域信息;基于关联规则方法优化振动故障数据采集完整性,通过分解、排序、更新三个步骤在处理噪声的同时保证数据完整性;引入连续采集算法判定振动数据故障阈值,优化完成油田大型机泵设备振动故障数据采集.实验表明,该数据采集方法可以在六种工况下,有效获取机泵设备回旋振动与纵向振动的完整故障数据,具备实际可行性.

从BERT到ChatGPT:大模型训练中的存储系统挑战与技术发展

以ChatGPT为代表的大模型在文字生成、语义理解等任务上表现卓越,引起了工业界和学术界的广泛关注.大模型的参数量在3年内增长数万倍,且仍呈现增长的趋势.首先分析了大模型训练的存储挑战,指出大模型训练的存储需求大,且具有独特的计算模式、访存模式、数据特征,这使得针对互联网、大数据等应用的传统存储技术在处理大模型训练任务时效率低下,且容错开销大.然后分别阐述了针对大模型训练的3类存储加速技术与2类存储容错技术.针对大模型训练的存储加速技术包括:1)基于大模型计算模式的分布式显存管理技术,依据大模型计算任务的划分模式和计算任务间的依赖关系,设计模型数据在分布式集群中的划分、存储和传输策略;2)大模型训练访存感知的异构存储技术,借助大模型训练中的访存模式可预测的特性,设计异构设备中的数据预取和传输策略;3)大模型数据缩减技术,针对大模型数据的特征,对模型训练过程中的数据进行缩减.针对大模型训练的存储容错技术包括:1)参数检查点技术,将大模型参数存储至持久化存储介质;2)冗余计算技术,在多张GPU中重复计算相同版本的参数.最后给出了总结和展望.