声学探测技术在海上风电桩基检测中的应用

海上风机维护是保障海上风电场正常运行的重要工作,水声学海底探测方法在海上风电场运维中的应用越来越广泛。提出在风电桩基检测中综合使用多波束测深仪、侧扫声纳、浅地层剖面仪的联合探测作业技术,利用多波束获取全覆盖水深地形,利用侧扫声纳获取海底地貌,利用浅地层剖面仪获取海缆埋藏状态,通过对3类声纳数据综合分析,确定风电桩基及附近地形、地貌、电缆等的位置、深度、状态等信息。将该方法应用于阳江风电场故障风机抢修项目中,验证了方法的有效性。实践表明:该方法可以广泛应用于海上风电桩基检测等海洋工程领域,对其他海上风电场桩基检测有一定借鉴意义。

基于双边截断的双参数海上风电站SAR图像CFAR检测

文章提出了1种基于双边截断的双参数海上风电站SAR图像CFAR检测器DTCS-TPCFAR,目的是提高在具有多个目标海上区域和石油泄漏区域等环境下对海上风电站的检测性能。DTCS-TPCFAR所提出的双边截断杂波的方法,能够同时消除高强度和低强度异常值的干扰,同时保留真实的杂波样本。通过使用最大似然估计计算双边截断后样本的均值和标准差,然后通过这2个参数估计值计算出截断阈值,最后再结合指定的虚警率(Probability of False Alarm,PFA)来对测试单元(Test Cell,TC)进行判断,完成最终的目标检测。这也是首次将CFAR检测器用于检测海上风电站。文章通过Sentinel-1数据集来验证该方法的有效性。实验结果表明,文章所提出的算法在相同指定虚警率下,具有更高的检测率(Detection Rate,DR)和更低的误报率(False Alarm Rate,FAR)。

基于矿用风筒检测系统的正压风筒漏风率研究与分析

基于矿用风筒检测系统,通过控制局部通风机模拟井下实际运行的通风系统工况,针对矿用风筒的漏风孔口面积、位置、个数3种主要因素研究风筒漏风率的关系并进行分析。结果表明,当风筒其他结构参数不变的前提下,随着孔口面积的增加,风筒漏风率呈二次曲线增加,并得到拟合曲线方程,拟合数据与实测数据误差为2.7%;当风筒其他结构参数不变的前提下,随着孔口位置与风机距离的增加,风筒漏风率基本呈直线关系下降,最低为13.4%;当风筒其他结构参数不变的前提下,随着风筒孔口个数增加,风筒漏风率呈二次曲线增加,并得到拟合数据,与其实测数据相比误差为1.7%;采用正交实验,研究了风筒漏风孔口面积、位置、个数对风筒漏风率的影响,影响风筒漏风的主次顺序为:漏风孔口直径、个数、位置。研究对改善风筒漏风现象提供了相关数据参考。

基于专利数据的全球海上风电检测技术发展态势与我国发展对策研究

海上风电作为应对全球能源危机和促进可持续发展的关键清洁能源,其安全和稳定运行至关重要。在此背景下,全球海上风电检测技术的发展态势与我国发展对策成为研究焦点。本文利用IncoPat专利库中的数据,通过IPC号共现分析和技术成熟度分析,深入探讨了全球海上风电检测技术的专利动态、地域分布、申请者构成及技术方向等。研究发现,海上风电检测技术正处于快速成长阶段,中国在专利数量上全球领先,主流技术集中于降低运维成本、提升系统的安全性和可靠性。本文的创新点在于揭示了关键技术的演进路径和未来发展趋势,并结合我国的实际情况,提出了具体的发展对策。分析表明,未来技术的发展将进一步聚焦于智能化和自动化检测系统的集成应用。本文的分析为全球海上风电检测技术的创新和应用提供了有价值的洞见,对于推动该领域的技术进步和产业升级具有重要参考意义。

无人机智能巡检在风电光伏故障检测中的应用

随着我国社会经济形势的发展,社会的能源需求量也不断提升。目前,以清洁型能源为主的风力发电、光伏发电取得了社会大众的广泛认可,但风电光伏发电站的人工故障检修工作难度较大、成本较高且效率较低,为进一步提高风电光伏故障检测工作的效率,降低风电光伏的运维成本,可引入无人机智能巡检技术,实现智能化风电光伏运维。文章简要介绍了风电光伏故障检测中的无人机智能巡检技术,并分别阐述了无人机智能巡检在风电故障检测及光伏故障检测中的应用。

无人机智能巡检用于风电光伏故障检测的研究分析

风电光伏的系统使用环境存在特殊性,风电光伏的设备组件在发生故障的情况下,必须要进行准确的故障检测以及故障修复操作。在目前的现状下,采取无人机的故障巡检模式能够促进风电光伏的设备故障得到更加准确完整的显示,同时对于风电光伏的系统安全风险实现了必要的控制降低。因此,本文探讨了风电光伏的无人机智能故障检测基本实施思路,改进无人机的智能巡检系统设计措施。

高精度风向检测方法研究与应用

自动气象站作为一种自动观测和存储气象观测数据的设备,弥补了空间区域上气象探测数据空白。风向是气象站所测量的重要气象要素之一,对气象和相关领域的发展都有着及其重要的意义。如今风向传感器大多采用的是光电风向传感器,其使用的格雷码盘输出为离散的数字信号,测量精度不高。设计了一种满角度电位器及风向检测算法,研制了一套基于STM32的风向检测装置,并在LCD上显示。实验测试表明,该系统能较好地实现对风向的检测,测量精度明显提高。

DX-400水冷中波发射机风流动检测电路的原理与调整

本文介绍了DX-400水冷中波发射机的风流动检测电路的构成和检测部位,通过分析不同电路的工作原理,针对不同部位的风流动检测电路引起的故障,提出进相应的调整办法。

无人机智能巡检在风电光伏故障检测中的应用

现阶段,在电力市场中,新能源发电所占比例越来越大。风电与光伏作为非水可再生能源中的两大明星,增势尤为显著。根据 彭博新能源财经《2018 新能源市场长期展望(NEO)》预测,到 2050 年风电与光伏发电量将达到全球发电量的 50%,共占半壁江山。而全 球三大国际评级机构之一的惠誉在对可再生能源基础设施领域的首次调研中发现,太阳能在可再生能源方面的表现超越了风能。惠誉表示, 从全球市场来看,太阳能项目的运营风险较低,项目资产表现更稳定。“从评级角度来看,太阳能项目的表现也优于风电项目。 ”惠誉董事 长安德·鲁乔伊特说。

瓦斯抽采钻孔密封质量的简易监测方法及现场试验

目前我国煤层瓦斯抽采钻孔的密封还存在一定问题,这与缺乏简单有效的钻孔密封质量的检测手段有关。常见的瓦斯浓度检测法存在较大的问题,主要表现在光学瓦斯检测仪检测出来的瓦斯浓度仅为瓦斯中的甲烷浓度,而压风检测法在现场应用的可操作性不强。通过孔内和孔口压差来判断瓦斯抽采钻孔密封质量的方法(压差检测法),能直观地观测出钻孔的密封效果,是一种简单、直观的判断钻孔密封效果的方法,且成本低廉,操作简单。

浅谈高层住宅厨房排烟道系统

本文介绍了高层住宅烟道的发展历程,并结合《重庆市住宅厨房、卫生间排烟(风)道性能检测标准》对烟道系统做了简单的分析。

Determination of Astragaloside IV in Yupingfeng Oral Solution by HPLC-ELSD Method

[Objective] This study aimed to establish a method for determining the content of Astragaloside IV in Yupingfeng oral solution.[Method] The HPLC-ELSD method was adopted.The chromatographic column was Venusil MP（4.6 mm × 150 mm,5 μm）.The mobile phase was acetonitrile-water（35∶65）.The ELSD evaporator tube temperature was 65 ℃.N2 was used as the carrier gas（pressure,30 psi）.[Result] When the content of Astragaloside IV ranged from 0.5 to 5.0 μg,the Astragaloside IV content showed a good linear relationship with peak area（r=0.999,n=6）.The average recovery was 96.36%,and the RSD was 2.46%.[Conclusion] This method is accurate and reliable,and can be applied in the quality control of Yupingfeng oral solution.

基于多激光光束后向散射的大气风场检测和时域信号分析

系统地研究了一种基于后向散射信号的光学闪烁机理的多激光光束风场测量(MLBM)系统及其性质。在实时检测过程中,使用光学互相关方法对信号进行分析得出了固定距离200m处的近场风速及风向信息;同时,测量并计算了在不同时刻和不同系统摆放情况时的风速。实验结果表明,测量得到的风速与参照风速之间的相对误差小于5%。

Reduced Popdc3 expression correlates with high risk and poor survival in patients with gastric cancer

AIM： To investigate the expression of Popeye domain containing 3 （Popdc3） and its correlation with clinicopathological features and prognosis of gastric cancer.METHODS： The method of immunohistochemistry was used to investigate the expression of Popdc3 in 306 cases of human gastric cancer and 84 noncancerous gastric tissues. Simultaneously, the relationship between Popdc3 expression and the survival of the patients was retrospectively analyzed.RESULTS： Popdc3 was detected in 72 （85.71%） of 84 human nontumor mucosa. High expression of Popdc3protein was detected in 78 （25.49%） of 306 human gastric cancer cases, and low expression was detected in 228 （74.51%）. Low expression of Popdc3 correlated with depth of invasion （P 〈 0.0001）, regional lymph nodes （P 〈 0.0001） and distant metastasis （P =0.02）, and tumor, nodes, metastasis （TNM） stages （P 〈 0.0001）. On multivariate analysis, only the patient＇s gender, regional lymph node metastasis, distant metastasis, TNM stages, and the expression of Popdc3 were independent prognostic factors in patients with gastric cancer. The Kaplan-Meier plot showed that low Popdc3 expression had a much more significant effect on the survival of those patients with early-stage tumors X^2 = 104.741, P 〈 0.0001）, with a 〉 51.9% reduction in the three-year survival compared with high Popdc3 expression. In late stages, the difference was also significant X^2 = 5.930, P = 0.015）, with a 32.6% reduction in the three-year survival.CONCLUSION： Reduced expression of Popdc3 may play a significant role in the carcinogenesis and progression of gastric cancer. Popdc3 may be an independent prognostic factor.

Quantitative risk assessment & leak detection criteria for a subsea oil export pipeline

A quantitative risk assessment （QRA） based on leak detection criteria （LDC） for the design of a proposed subsea oil export pipeline is presented in this paper. The objective of this QRA/LDC study was to determine if current leak detection methodologies were sufficient, based on QRA results, while excluding the use of statistical leak detection; if not, an appropriate LDC for the leak detection system would need to be established. The famous UK PARLOC database was used for the calculation of pipeline failure rates, and the software POSVCM from MMS was used for oil spill simulations. QRA results revealed that the installation of a statistically based leak detection system （LDS） can significantly reduce time to leak detection, thereby mitigating the consequences of leakage. A sound LDC has been defined based on QRA study results and comments from various LDS vendors to assist the emergency response team （ERT） to quickly identify and locate leakage and employ the most effective measures to contain damage.

Rough Outlier Detection Based Security Risk Analysis Methodology

Security is a nonfunctional information system attribute that plays a crucial role in wide sensor network application domains. Security risk can be quantified as the combination of the probability that a sensor network system may fail and the evaluation of the severity of the damage caused by the failure. In this paper, we devise a methodology of Rough Outlier Detection (ROD) for the detection of security-based risk factor, which originates from violations of attack requirements (namely, attack risks). The methodology elaborates dimension reduction method to analyze the attack risk probability from high dimensional and nonlinear data set, and combines it with rough redundancy reduction and the distance measurement of kernel function which is obtained using the ROD. In this way, it is possible to determine the risky scenarios, and the analysis feedback can be used to improve the sensor network system design. We illustrate the methodology in the DARPA case set study using step-by-step approach and then prove that the method is effective in lowering the rate of false alarm.

A STUDY ON PCR FOR DETECTING INFECTION WITH M.LEPRAE

Objective. So far, it has not been established a satisfactory method for early diagnosis and studying on epidemiology for leprosy, we want to develop a molecular biological method for solving this point. Materials and methods. Based on the M. leprae gene coding groEL, 65kD and 16S rRNA, three polymerase chain reactions were developed by using plikaytis’, Woods’ and Pattyn’s procedures. It was optimized that the experimental parameters for each PCR, and a comparative study on practivity among three PCRs was also conducted for practical purpose.Results and conclusion. For detecting infection with M. leprae, all of PCRs established by us were highly sensitive and specific, but for practicl purpose, the woods’ PCR optimized by us ought to be chosen firstly.

Application of Signal Detection Theory to Ascertain Driving Risk and Mitigation in a Flooded Urban Area

Signal Detection Theory （SDT） offers an unparalleled deterministic set of decision variables necessary to formulate applied risks in transportation. SDT has distinct advantages over basic prediction models since the latter may not represent an entirely accurate analysis. Thresholds based on elements of stimulus （signal and noise） and response for： a Type I discrimination of response variable where decision outcomes and rates are computed for metacognition to discriminate a Type II of decision outcomes was set. We also adapted the classical Dijkstra＇s shortest path algorithm within a GIS environment using Avenue programming. Contours derived from LiDARwere used to set flood levels while satellite imagery corresponding to Red River of the North inundated （signal） areas were acquired amongst other spatial datasets. The signal information was further dichotomized using a binary yes-no model. Origin and destination points constrained within Fargo-Morehead were generated using a random point generator. From these points, trips were generated with some connected segments traversing through flooded areas. By analyzing False Alarm Rate （FAR） and Corrected Rejection （CRR） computation, we found out that, when Hit Rate （HR） and FAR are both low then there was an increased corresponding sensitivity. At 30-35 ft flood level, the values for FAR and HR was 0.97 and 0.91 respectively.When FAR〉HR, lower set flood levels offered numerous route choices. Corresponding routes with associated impedance can be classified for risk-averse drivers or risk-takers While the risk-averse avoid risky and unfavorable routes, the risk-taker optimizes at an adjustment factor of ω = 0.1 or ω = 0.2. An idealistic stage is achieved for a conservative, co, equal to 0.4 or 0.5, which indicates maximum achievement in terms of time gain and safety simultaneously. At ω = 0.0 the prevailing conditions can be considered unrealistic since they incorporate areas considered impassable with absolute resistance like segments with a ＂Road Closed＂ or ＂Detour＂ sign. The applicability of our approach can be used to design multi-level and multi-modal transportation systems involving risk.

Change Point Detection and Trend Analysis for Time Series

Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends.

A Physics-Based Dual-Frequency Approach for Altimeter Wind Speed Retrieval

The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future study.