Weak Fault Detection of Rotor Winding Inter-Turn Short Circuit in Excitation System Based on Residual Interval Observer

Aiming at the fact that the rotor winding inter-turn weak faults can hardly be detected due to the strong electromagnetic coupling effect in the excitation system,an interval observer based on current residual is designed.Firstly,the mechanism of the inter-turn short circuit of the rotor winding in the excitation system is modeled under the premise of stable working conditions,and electromagnetic decoupling and system simplification are carried out through Park Transform.An interval observer is designed based on the current residual in the two-phase coordinate system,and the sensitive and stable conditions of the observer is preset.The fault diagnosis process based on the interval observer is formulated,and the observer gain matrix is convexly optimized by linear matrix inequality.The numerical simulation and experimental results show that the inter-turn short circuit weak fault is hardly detected directly through the current signal,but the fault is quickly and accurately diagnosed through the residual internal observer.Compared with the traditional fault diagnosis method based on excitation current,the diagnosis speed and accuracy are greatly improved,and the probability of misdiagnosis also decreases.This method provides a theoretical basis for weak fault identification of excitation systems,and is of great significance for the operation and maintenance of excitation systems.

Intrusion Detection Algorithm Based on Model Checking Interval Temporal Logic

Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is still a high rate of false negatives in detecting these complex attack patterns.To solve this problem,we use interval temporal logic formulae to describe concurrent attacks and piecewise attacks.On this basis,we formalize a novel algorithm for intrusion detection based on model checking interval temporal logic.Compared with the method based on model checking linear temporal logic,the new algorithm can find unknown succinct attacks.The simulation results show that the new method can effectively reduce the false negative rate of concurrent attacks and piecewise attacks.

Statistical damage detection method for frame structures using a confidence interval

A novel damage detection method is applied to a 3-story frame structure, to obtain statistical quantification control criterion of the existence, location and identification of damage. The mean, standard deviation, and exponentially weighted moving average （EWMA） are applied to detect damage information according to statistical process control （SPC） theory. It is concluded that the detection is insignificant with the mean and EWMA because the structural response is not independent and is not a normal distribution. On the other hand, the damage information is detected well with the standard deviation because the influence of the data distribution is not pronounced with this parameter. A suitable moderate confidence level is explored for more significant damage location and quantification detection, and the impact of noise is investigated to illustrate the robustness of the method.

Implementation of a Multi-sampling-frequency System for RR-interval Timing and Blood Pressure Detection

In order to analyze the experimental cardiovascular signal with high accuracy, a system, integrating real-time monitoring and off-line further analysis, was developed and verified. The design, data processing and analysis methods as well as testing results are described. With 5 sampling frequency choices and 8 channel data acquisition, the system achieved high performances in beat-to-beat monitoring, signal processing and analysis. Tests were carried out to validate its performance in real-time monitoring, effectiveness of digital filters, QRS and blood pressure detection reliability, and RR-interval timing accuracy. The QRS detection rate was at least 99.46% for the records with few noises from MIT-BIH arrhythmia database using the algorithm for real-time monitoring, and no less than 96.43% for the records with some noises. In the condition that noise amplitude levels were less than 80%,the standard deviations for RR-interval timing were less than 1 ms with a generated ECG corrupted with various noises from MIT-BIH Noise Stress Test Database. Besides, the system is open for function expansion to meet further study-specific needs.

Confidence Interval Estimation of the Correlation in the Presence of Non-Detects

This article deals with correlating two variables that have values that fall below the known limit of detection (LOD) of the measuring device;these values are known as non-detects (NDs). We use simulation to compare several methods for estimating the association between two such variables. The most commonly used method, simple substitution, consists of replacing each ND with some representative value such as LOD/2. Spearman’s correlation, in which all NDs are assumed to be tied at some value just smaller than the LOD, is also used. We evaluate each method under several scenarios, including small to moderate sample size, moderate to large censoring proportions, extreme imbalance in censoring proportions, and non-bivariate normal (BVN) data. In this article, we focus on the coverage probability of 95% confidence intervals obtained using each method. Confidence intervals using a maximum likelihood approach based on the assumption of BVN data have acceptable performance under most scenarios, even with non-BVN data. Intervals based on Spearman’s coefficient also perform well under many conditions. The methods are illustrated using real data taken from the biomarker literature.

Sessile serrated adenoma detection rate is correlated with adenoma detection rate

AIM To investigated the association between adenoma detection rate(ADR) and sessile serrated ADR(SSADR) and significant predictors for sessile serrated adenomas(SSA) detection.METHODS This study is a retrospective, single-center analysis. Total colonoscopies performed by the gastroenterologists at the University of Tokyo Hospital between January and December 2014 were retrospectively identified. Polyps were classified as low-grade or high-grade adenoma, cancer, SSA, or SSA with cytological dysplasia, and the prevalence of each type of polyp was investigated. Predictors of adenoma and SSA detection were examined using logistic generalized estimating equation models. The association between ADR and SSADR for each gastroenterologist was investigated by calculating a correlation coefficient weighted by the number of each gastroenterologist's examination.RESULTS A total of 3691 colonoscopies performed by 35 gastroenterologists were assessed. Overall, 978 (26.5%) low-and 84 (2.2%) high-grade adenomas, 81 (2.2%) cancers, 66 (1.8%) SSAs, and 2 (0.1%) SSAs with cytological dysplasia were detected. Overall ADR was 29.5%(men 33.2%, women 23.8%) and overall SSADR was 1.8%(men 1.7%, women 2.1%). In addition, 672 low-grade adenomas (68.8% of all the detected lowgrade adenomas), 58 (69.9%) high-grade adenomas, 29 (34.5%) cancers, 52 (78.8%) SSAs, and 2 (100%) SSAs with cytological dysplasia were found in the proximal colon. Adenoma detection was the only significant predictor of SSA detection (adjusted OR: 2.53, 95%CI: 1.53-4.20; P < 0.001). The correlation coefficient between ADR and SSADR weighted by the number of each gastroenterologist's examinations was 0.606(P < 0.001).CONCLUSION Our results demonstrated that ADR is correlated to SSADR. In addition, patients with adenomas had a higher prevalence of SSAs than those without adenomas.

Intraprocedural bowel cleansing with the Jet Prep cleansing system improves adenoma detection

AIM: To investigate the impact of Jet Prep cleansing on adenoma detection rates.METHODS: In this prospective,randomized,crossover trial,patients were blindly randomized to an intervention arm or a control arm.In accordance with the risk profile for the development of colorectal carcinoma,the study participants were divided into high-risk and low-risk groups.Individuals with just one criterion(age > 70 years,adenoma in medical history,and first-degree relative with colorectal cancer) were regarded as high-risk patients.Bowel preparation was performed in a standardized manner one day before the procedure.Participants in the intervention arm underwent an initial colonoscopy with standard bowel cleansing using a 250-m L syringe followed by a second colonoscopy that included irrigation by the use of the Jet Prep cleansing system.The reverse sequence was used in the control arm.The study participants were divided into a high-risk group and a low-risk group according to their respective risk profiles for the development of colorectal carcinoma.RESULTS: A total of 64 patients(34 men and 30 women) were included in the study; 22 were included in the high-risk group.After randomization,30 patients were assigned to the control group(group A) and 34 to the intervention group(group B).The average Boston Bowel Preparation Scale score was 5.15 ± 2.04.The withdrawal time needed for the first step was significantly longer in group A using the Jet Prep system(9.41 ± 3.34 min) compared to group B(7.5 ± 1.92 min).A total of 163 polyps were discovered in 64 study participants who underwent both investigation steps.In group A,49.4% of the polyps were detected during the step of standard bowel cleansing while the miss rate constituted 50.7%.Group B underwent cleansing with the Jet Prep system during the first examination step,and as many as 73.9% of polyps were identified during this step.Thus,the miss rate in group B was a mere 26.1%(P < 0.001).When considering only the right side of the colon,the miss rate in group A during the first examination was 60.6%,in contrast to a miss rate of 26.4% in group B(P < 0.001).CONCLUSION: Jet Prep is recommended for use during colonoscopy because a better prepared bowel enables a better adenoma detection,particularly in the proximal colon.

Outsourced Privacy-Preserving Anomaly Detection in Time Series of Multi-Party

Anomaly detection has practical significance for finding unusual patterns in time series.However,most existing algorithms may lose some important information in time series presentation and have high time complexity.Another problem is that privacy-preserving was not taken into account in these algorithms.In this paper,we propose a new data structure named Interval Hash Table(IHTable)to capture more original information of time series and design a fast anomaly detection algorithm based on Interval Hash Table(ADIHT).The key insight of ADIHT is distributions of normal subsequences are always similar while distributions of anomaly subsequences are different and random by contrast.Furthermore,to make our proposed algorithm fit for anomaly detection under multiple participation,we propose a privacy-preserving anomaly detection scheme named OP-ADIHT based on ADIHT and homomorphic encryption.Compared with existing anomaly detection schemes with privacy-preserving,OP-ADIHT needs less communication cost and calculation cost.Security analysis of different circumstances also shows that OP-ADIHT will not leak the privacy information of participants.Extensive experiments results show that ADIHT can outperform most anomaly detection algorithms and perform close to the best results in terms of AUC-ROC,and ADIHT needs the least time.

Early Detection of QoE Deterioration in HTTP Adaptive Streaming

Apart from video rate (or requested bitrate), Mean Opinion Score (MOS) has increasingly become a primary term representing Quality of Experience (QoE) in HTTP adaptive streaming (HAS). By monitoring this metric, QoE management can effectively maximize QoE for the users. However, due to various behaviors of particular commercial HAS players, deciding an appropriate monitoring interval has not been fully investigated yet. In this paper, an optimal interval is proposed to be equal to duration of a video chunk in order to aid service managers in early detecting QoE deterioration and limiting the probability of video rate deterioration. The optimal monitoring interval is evaluated by comparing with other values of interval in terms of ratio of video rate deterioration. Furthermore, MOS-based QoE monitoring method which takes into account the proposed interval is thus compared with video rate based monitoring method. The results show that with optimal interval, MOS monitoring guarantees a low ratio of video rate deterioration (around 10% for buffering state and 40% for steady state) and small average CPU Load (about 11.45%).

基于数据到达间隔的网络大流检测方法

大流检测是网络监管中的重要任务。现有的检测方法主要围绕流的大小来进行筛选评判。然而,真实的大流往往与数量众多的老鼠流混合在一起,尤其是当路由器存储空间有限时,依靠所能记录下来的流大小信息通常不能准确实现大流检测。为此提出一种新的大流检测方法,该方法根据流的新旧及数据到达间隔来滤除老鼠流。实验显示该方法在有限的存储空间条件下,表现出良好的检测准确性。

基于FPGA的高分辨率电容检测系统设计

针对环境湿度可以改变湿敏电容的容值这一特性,提出了一种基于现场可编程门阵列(FPGA)的高分辨率电容检测系统设计方法,对系统方案、数据采集、误差来源进行了全面的分析。文中使用电容-频率电路将电容的容值变化转化为脉冲信号的持续时间。利用FPGA设计时间间隔测量电路,使用系统时钟控制的同步计数器保证整个检测电路的量程大小,采用延迟单元设计延迟链以进一步提高测量分辨率。分析了测量误差来源并提出了相应解决办法。实验结果表明,该时间间隔测量电路达到了皮秒量级,可测量的脉冲信号持续时间的精度在2 s之内,可以测量皮法量级的电容变化。

重力数据探测地下目标的贝叶斯方法研究

针对地下目标空间位置和形状均未知的情况,基于重力数据,分别以区域测量和线测量2种场景进行建模分析,研究贝叶斯推断用于地下目标探测的效果。结果表明,将贝叶斯推断用于重力梯度探测,比微重力探测更具优势,能有效反演出目标的未知参数。

基于分布假设检验的风电机组静态偏航误差诊断方法研究

通过确定敏感风速区间并检测功率分布,实现对风电机组静态偏航误差值的估计。利用风电机组的实际运行数据对所提方法的有效性进行验证,并与基于功率曲线的诊断方法进行对比。结果表明,所提方法能够准确量化不同偏航误差区间的数据分布差异,精准识别出静态偏航误差所在的偏航角区间,诊断的准确性较高。

基于核回归区间模型的电液位置伺服系统故障检测

针对电液位置伺服系统在运行过程中存在非线性、干扰性、复杂性以及参数不确定性等问题,提出了基于核回归区间模型的电液位置伺服系统故障检测方法。该方法利用反映系统诸多不确定性的无故障可测输入-输出数据,建立能控制核回归模型精度、又能平衡该模型结构复杂性的区间模型,用于判断电液位置伺服系统的实际输出是否越过系统健康运行时的区间输出,进而实现故障检测。该方法由于考虑了基于区间的动态阈值对故障进行检测,消除了传统的固定阈值易引起故障误报现象,所以具有一定的自适应性能力。实验论证了所提出的故障检测方法,可用于电液位置伺服系统故障的实时检测。

基于到达时间间隔差的ADS-B位置消息验证方法

广播式自动相关监视(ADS-B)是一种新型的航空器监视技术,具有定位精度高、更新速度快及覆盖范围广等优势,在民用航空监视领域获得广泛应用。由于ADS-B消息以广播方式传输,未采用加密与认证机制,ADS-B系统易受外部欺骗源的干扰。为解决该问题,提出了一种基于到达时间间隔差(IDOA)的ADS-B位置消息验证方法。建立基于IDOA的ADS-B位置消息验证系统模型,理论分析给出检验统计量的表达式及其统计特性,进一步分析给出检测门限的确定方法,通过仿真验证所提方法的正确性与有效性。结果表明:所提方法与基于到达时间差(TDOA)的验证方法具有相同的检测性能,且对时间测量误差和ADS-B位置误差不敏感,但所提方法可克服基于TDOA的验证方法存在的对地面站时间同步误差敏感的缺点。

洞桩法车站小净距下穿运营线路施工力学分析

基于某近接下穿运营线路区间新建洞桩法车站工程,采用数值分析软件对施工过程进行模拟分析,研究运营线路区间变形规律、最大及最小主应力变化趋势和发生位置;现场施工监测的发展趋势、发生位置均与模拟结果拟合度较高,且现场监测值均满足规范要求。

光缆SZ反转点定位的实现

本文阐述了SZ绞合反转点定位的非金属光缆设计原理及生产过程中的工艺控制原理,保证此类光缆在生产中能够对SZ反转点完全标识,并在实际施工中可以方便地识别出反转点的精确位置,实现施工中对光缆进行精确开剥。

Comparison of Time Interval Statistic and Pulse Shape Discrimination in Fast Neutron Detection Method with Liquid Scintillation Detector Loaded Gd

Neutron usually appears with gamma,which is requiring the detector has the capability of n gamma discrimination.Pulse shape discrimination(PSD)is a common approach of n,gamma judgment,but required a complex process to select a suitable discrimination factor,and poor performance in the low energy range.A method based on the time interval of adjacent Signals was disrupted and adopted to compare to pulse shape discrimination in the fast neutron detection method.A good agreement between the adopted method and PSD method was achieved,including the total count ratio and neutron count ratio.The comparison proves the correctness of the theoretical derivation and validates the method in practice.The advantages and limitations of the method based on time Interval of adjacent signals were analyzed.The method provides an effective way to confirm the calibration of the neutron detection of a liquid scintillation detector.Also,as a simple way only requiring the time information about events,the described method has large application potential in some case of fast neutron flux or intensity measurement.

一类区间值时间序列IO型异常点检测方法及其在金融时序分析中的应用

针对区间值时间序列的异常点检测问题,从区间数据的区间中心和区间半径出发,基于ARIMA的点值时间序列IO型异常点检测原理,构造一类区间值时间序列IO型异常区间的检测方法。其中,对区间值时间序列IO型异常区间的概念和类型进行了具体的界定,给出了区间值时间序列IO型异常区间的检测步骤。最后,针对上证指数2016年1月4日到2018年12月28日每日最高价和最低价构成区间值时间序列且其每日收盘价构成点值时间序列,用所提方法进行IO型异常区间的检测,通过和传统点值异常检测结果的对比分析表明,所提方法能够更有效地识别出金融时间序列中存在的异常状况。

基于超程时间测量的电磁继电器故障检测

针对现有电磁继电器隐性故障检测率较低的问题,提出一种基于超程时间测量的电磁继电器故障检测方法。首先,通过离线优化获取最优模糊阈值,然后应用线性回归方法,对超程时间监测数据进行在线预测,并利用拟合误差将预测值扩展为预测区间;其次,根据最优模糊阈值,将监测数据和预测区间分别转换为当前和预测故障证据,利用区间证据推理迭代融合积累、当前、预测3种故障证据,获取更新后的积累故障证据;最后,按照故障判据,由积累故障证据得到继电器故障检测结果。所提方法充分考虑了继电器隐性故障的渐变性特征以及超程时间测量过程所包含的不确定性,使故障证据更贴近于继电器实际工况。实验结果表明,与现有方法相比,所提方法在证据准确性和收敛速度上具有显著优势,能够有效提升电磁继电器隐性故障的检测精度。