Quality Monitoring Techniques Research Articles

Moving variance-based signal quality monitoring method for spoofing detection

Signal quality monitoring (SQM) techniques, originally designed for multipath detection, were recently found to be useful to identify underway spoofing attacks. Conventional SQM-based methods directly employ the values of the SQM metrics to monitor spoofing attacks. They have good feasibility with simple structures but suffer from significant performance loss for frequency unlocked spoofing cases due to the drift of the relative carrier phase. We developed an enhanced SQM technique for detecting an onset of spoofing. It is known that the value of the SQM metric fluctuates significantly during the interaction stage between the counterfeit signal and authentic signal. As the variance of metric can better reflect this fluctuation, we choose the moving variance (MV) of the SQM metric as a new metric to detect the occurrence of spoofing. The basic principle of the proposed method is introduced. Its ability to detect spoofing has been validated using the Texas Spoofing Test Battery dataset and compared with the classic SQM methods and a moving average-based method. The results show that the proposed MV-based SQM method is advantageous in the detection of an onset of a frequency unlocked spoofing attack.

GNSS Spoofing Detection by Means of Signal Quality Monitoring (SQM) Metric Combinations

Global navigation satellite system (GNSS) signal is vulnerable and easily interfered by spoofing because of its opening signal structure and weak signal power. A signal quality monitoring (SQM) technique has been shown to be viable to detect spoofing attacks on GNSS signals. However, the effectiveness of spoofing detection employing a single SQM metric alone is limited and conditional upon the features extracted of that specific SQM metric. The complementary features among various SQM metrics can be exploited to implement joint detection to overcome the deficiency of the individual SQM metric. Motivated by this idea, this paper investigates the multi-metric joint detection technique, which combines various SQM metrics into a composite SQM metric to detect spoofing attacks. This paper proposes two combination strategies, namely amplitude combination mode and probability of false alarm combination mode (PfaM). The overall performance of different metric combinations was verified using simulations and the Texas Spoofing Test Battery dataset. Results show that the PfaM detector outperforms all single SQM metric detectors under various scenarios.

Analysis and Mitigation of Power Quality Issues in Distributed Generation Systems Using Custom Power Devices

This paper discusses the power quality issues for distributed generation systems based on renewable energy sources, such as solar and wind energy. A thorough discussion about the power quality issues is conducted here. This paper starts with the power quality issues, followed by discussions of basic standards. A comprehensive study of power quality in power systems, including the systems with dc and renewable sources is done in this paper. Power quality monitoring techniques and possible solutions of the power quality issues for the power systems are elaborately studied. Then, we analyze the methods of mitigation of these problems using custom power devices, such as D-STATCOM, UPQC, UPS, TVSS, DVR, etc., for micro grid systems. For renewable energy systems, STATCOM can be a potential choice due to its several advantages, whereas spinning reserve can enhance the power quality in traditional systems. At Last, we study the power quality in dc systems. Simpler arrangement and higher reliability are two main advantages of the dc systems though it faces other power quality issues, such as instability and poor detection of faults.

Characterization of Signal Quality Monitoring Techniques for Multipath Detection in GNSS Applications.

The performance of Signal Quality Monitoring (SQM) techniques under different multipath scenarios is analyzed. First, SQM variation profiles are investigated as critical requirements in evaluating the theoretical performance of SQM metrics. The sensitivity and effectiveness of SQM approaches for multipath detection and mitigation are then defined and analyzed by comparing SQM profiles and multipath error envelopes for different discriminators. Analytical discussions includes two discriminator strategies, namely narrow and high resolution correlator techniques for BPSK(1), and BOC(1,1) signaling schemes. Data analysis is also carried out for static and kinematic scenarios to validate the SQM profiles and examine SQM performance in actual multipath environments. Results show that although SQM is sensitive to medium and long-delay multipath, its effectiveness in mitigating these ranges of multipath errors varies based on tracking strategy and signaling scheme. For short-delay multipath scenarios, the multipath effect on pseudorange measurements remains mostly undetected due to the low sensitivity of SQM metrics.

First study to explore the feasibility of applying microbial fuel cells into constructed wetlands for COD monitoring

Chemical oxygen demand (COD) is one of the major targets to remove in constructed wetlands (CWs) system. Traditional method for COD measurement is a complex, time-consuming and highly toxic reagents participated procedure. In this study, microbial fuel cell (MFC) was successfully integrated into CW for indicating COD concentration. Results showed that there are two linear correlations between bioelectrical signals (output voltage from MFC) and COD concentration (acetate), which are COD from 0 to 500mg/L (101.99±7.42 to 631.74±7.41mV, R2=0.9710) and then from 500 to 1000mg/L (631.74±7.41 to 668.46±0.01mV, R2=0.9245). Furthermore, results also revealed the specificity of the system in terms of different types of carbon source. Overall, this work presented the feasibility of using CW-MFC for in-situ sensing COD during the wastewater treatment process, which will be a promising technique for water quality monitoring within CWs.

Analysis and Inversion of the Nutritional Status of China’s Poyang Lake Using MODIS Data

Lakes are important water resources. Unfortunately, natural factors and human activities, have resulted in declining water quality and eutrophication. These changes directly affect lake ecological environments and the ability for people to live off of the affected water. Satellite remote sensing data is important because it can quickly provide comprehensive, real-time, dynamic water quality information; it must supplement conventional water quality monitoring techniques. In this study, water from the Poyang Lake entryway and surface was collected from April to December in 2009 and analyzed via MODIS remote sensing data. The data and a comprehensive scoring method was used to establish surface water transparency, total phosphorus inversion model, and nutritional status. The results showed that eutrophication averaged at 59.8.; however, the nutritional status varies greatly in the wet season, normal season, and dry season. The nutritional status is highest in dry season, followed by normal season, and lowest in wet season. Moreover, the eutrophication degree increases gradually year by year.

Computer Vision Techniques for Quality Assessment of Dates

Computer vision (CV) is a technique in which the image of an object is obtained through any imaging system and the image is analyzed to characterize the quality of the object objectively. The advancement in electronics has made this technique utilized in various fields. In North America, food industry is one of the top ten industries utilizing CV technique for quality monitoring. However, CV technique is not much utilized in the food industries in Asia. Dates is an important fruit crop in Oman and many other Arab countries. The quality assessment of dates during handling and processing are mainly carried out through manual inspection method. But this method has many challenges such as the efficiency of a worker, subjectivity, and so on. There are lots of opportunities to utilize CV technique for measuring and monitoring various quality aspects of dates. Through an Open Research Grant program funded by The Research Council (TRC), Oman, potential of CV technique for various internal and external qualities of dates was determined. This paper describes the efficiency of CV systems for variety identification, surface crack detection, texture and hardness determination.

Assessing water quality by ratio of the number of dominant bacterium species between surface/subsurface sediments in Haihe River Basin

Sedimentary microorganisms can be used as a sensitive indicator of integrated aquatic environment quality assessment and indicate long-term water quality or toxicity. According to the Chinese National Standards of GB 3838-2002 and GB 18918-2002, the comprehensive water quality in Haihe River Basin has been described. Results showed that the comprehensive water quality in 6 sites, 4 sites, and 20 sites were good, bad, and medium. Furthermore, 162 dominant bacterial species were identified in surface and subsurface sediments in the 30 sampling sites. As revealed by two initial models constructed by logistic regression, the comprehensive water quality exhibited a pattern from good to bad as the ratio of the number of dominant bacterial species in surface sediments to that in subsurface sediments increased from 1 to 2.1. This finding possibly bridged a traditional gap between aquatic microbe indicators and water quality assessment or monitoring techniques.

Room Temperature Photoluminescence Characterization of Interface Quality of SiN/SiO2/Si Prepared under Various Deposition Techniques and Conditions

Various types of stacked dielectric films are used in complimentary metal-oxide-semiconductor (CMOS) devices in gates, capacitors and device isolation structures. They are also used as insulating materials between conductors, as inter-metal dielectrics (IMD) and inter-layer dielectrics (ILD). The preparation technique, structure and properties of dielectrics strongly influence the quality of the dielectrics/Si interface. Nominally, similar dielectrics/Si structures, even prepared by the same technique, often show different electrical properties depending on subtle differences in process conditions (hidden variables). Monitoring of physical dimensions and chemical compositions of dielectrics often miss unexpected variations in electrical properties. Non-contact electrical property characterization techniques lack lateral resolution and often results in impairment of the dielectrics/Si interface due to strong external electric fields from the measurement process. Alternative dielectrics/Si interface characterization techniques, which can provide insights into electrical properties without external electric field, would be very useful as a complimentary process and material quality monitoring technique. In this study, we have investigated the effect of SiN film deposition techniques on the interface quality of the resulting SiN/SiO2/Si using spectroscopic room temperature photoluminescence (RTPL) under multiwavelength excitation. The sample preparation procedures are as follows. First, ultra thin (~2.2 nm thick), gate oxide quality, thermal oxide films were grown on 300 mm Si(100) wafers. Nominally 5.0 nm thick SiN films were grown on ~2.0 nm thick SiO2/Si wafers using conventional low pressure chemical vapor deposition (LPCVD) and atomic layer deposition (ALD) under various nitrogen source flow conditions. The film thickness was measured (after SiO2 film deposition) before and after SiN deposition using ellipsometry. Figure 1 (a) and (b) show RTPL spectra measured at the center of seven different SiN/SiO2/Si wafers under 650 nm excitation and showing maximum RTPL intensity under 650 nm and 827 nm excitation. Significantly large RTPL intensity variations were measured among the seven SiN/SiO2/Si wafers. The SiN film deposition conditions have modified the underlying SiO2/Si interface characteristics. Non-contact RTPL measurements are very sensitive to the thin film deposition techniques and conditions. It is effective as a complimentary dielectrics/Si process and interface characterization and monitoring technique. Figure 1

Use of multivariate calibration models based on UV-Vis spectra for seawater quality monitoring in Tianjin Bohai Bay, China.

A series of ultraviolet-visible (UV-Vis) spectra from seawater samples collected from sites along the coastline of Tianjin Bohai Bay in China were subjected to multivariate partial least squares (PLS) regression analysis. Calibration models were developed for monitoring chemical oxygen demand (COD) and concentrations of total organic carbon (TOC). Three different PLS models were developed using the spectra from raw samples (Model-1), diluted samples (Model-2), and diluted and raw samples combined (Model-3). Experimental results showed that: (i) possible nonlinearities in the signal concentration relationships were well accounted for by the multivariate PLS model; (ii) the predicted values of COD and TOC fit the analytical values well; the high correlation coefficients and small root mean squared error of cross-validation (RMSECV) showed that this method can be used for seawater quality monitoring; and (iii) compared with Model-1 and Model-2, Model-3 had the highest coefficient of determination (R2) and the lowest number of latent variables. This latter finding suggests that only large data sets that include data representing different combinations of conditions (i.e., various seawater matrices) will produce stable site-specific regressions. The results of this study illustrate the effectiveness of the proposed method and its potential for use as a seawater quality monitoring technique.

Research on a power quality monitoring technique for individual wind turbines

The extensive deployment of megawatt-scale wind turbines is bringing more challenges to the safety and stability of electric grid than ever before. This is not only because of the unstable wind over time but the increased risk of power quality pollution by defective wind turbines particularly when the turbines today are still experiencing various reliability issues. To prevent the power quality pollution by defective turbines, a new power quality monitoring technique dedicated for individual wind turbines is developed in this paper, so that the quality of the power generated by an individual turbine can be monitored by the wind turbine condition monitoring system. Through simulated and physical experiments on a specially designed test rig, some encouraging results have been achieved. It has been shown that the proposed technique is not only valid for monitoring the power quality of an individual wind turbine, but helpful in detecting the mechanical and electrical faults occurring in the wind turbines.

Evidence for extraintestinal growth of bacteroidales originating from poultry litter.

Water quality monitoring techniques that target microorganisms in the order Bacteroidales are potential alternatives to conventional methods for detection of fecal indicator bacteria. Bacteroidales and members of the genus Bacteroides have been the focus of microbial source tracking (MST) investigations for discriminating sources of fecal pollution (e.g., human or cattle feces) in environmental waters. For accurate source apportionment to occur, one needs to understand both the abundance of Bacteroides in host feces and the survival of these host-associated microbial markers after deposition in the environment. Studies were undertaken to evaluate the abundance, persistence, and potential for growth of Bacteroidales originating from poultry litter under oxic and anoxic environmental conditions. Bacteroidales abundance, as determined by quantitative PCR (qPCR) with GenBac primers and probe, increased 2 to 5 log gene copies ml(-1) and 2 log gene copies g litter(-1) under most conditions during incubation of poultry litter in a variety of laboratory microcosm and field mesocosm studies. DNA sequencing of the Bacteroidales organisms in the litter identified taxa with sequences corresponding exactly to the GenBac primer and probe sequences and that were closely related to Bacteroides uniformis, B. ovatus, and B. vulgatus. These results suggest that MST studies using qPCR methods targeting Bacteroidales in watersheds that are affected by poultry litter should be interpreted cautiously. Growth of Bacteroidales originating from poultry litter in environmental waters may occur while Bacteroidales growth from other fecal sources declines, thus confounding the interpretation of MST results.

Laser-induced breakdown spectroscopy application in environmental monitoring of water quality: a review.

Water quality monitoring is a critical part of environmental management and protection, and to be able to qualitatively and quantitatively determine contamination and impurity levels in water is especially important. Compared to the currently available water quality monitoring methods and techniques, laser-induced breakdown spectroscopy (LIBS) has several advantages, including no need for sample pre-preparation, fast and easy operation, and chemical free during the process. Therefore, it is of great importance to understand the fundamentals of aqueous LIBS analysis and effectively apply this technique to environmental monitoring. This article reviews the research conducted on LIBS analysis for liquid samples, and the article content includes LIBS theory, history and applications, quantitative analysis of metallic species in liquids, LIBS signal enhancement methods and data processing, characteristics of plasma generated by laser in water, and the factors affecting accuracy of analysis results. Although there have been many research works focusing on aqueous LIBS analysis, detection limit and stability of this technique still need to be improved to satisfy the requirements of environmental monitoring standard. In addition, determination of nonmetallic species in liquid by LIBS is equally important and needs immediate attention from the community. This comprehensive review will assist the readers to better understand the aqueous LIBS technique and help to identify current research needs for environmental monitoring of water quality.

Quality monitoring service for distributed manufacturing systems

This paper proposes a novel service approach to quality monitoring (QM) in a distributed manufacturing system by implementing a network of autonomous work systems (AWSs). A quality monitoring service (QMS) is provided via a web application that offers a data interface unique to each manufacturing system, representing a service beneficiary. The solution preserves the data-related autonomy of the service beneficiary, is scalable, can be distributed, expanded by additional services and can be relatively easily integrated into each manufacturing system. The solution is based on a QMS system architecture and QMS ontology that facilitates the integration of QMS with AWS. Through a use case, it is demonstrated how an older QM technique (control charts) can be offered as a service using state-of-the-art information-communication technologies. In this way, new benefits for the manufacturer as well as the customer can be obtained. From the manufacturer’s perspective, the solution improves the manufacturing system’s competitiveness by maintaining manufacturing process quality. Furthermore, there are also benefits for customers, which are realised mainly by enhancing customers’ confidence in the manufacturing process, thus adding new value to the product.

Deploying a LEACH Data Aggregation Technique for Air Quality Monitoring in Wireless Sensor Network

The aim of this paper is to develop an effective aggregation technique for wireless sensor networks that is mainly designed to suit air quality monitoring application. The solution is based on LEACH by Heinzelman et al.; a well known data aggregation technique for wireless sensor networks. Experimental results show the effectiveness of our solution in extending the network lifetime, while efficiently monitoring air quality.

Technika elipsometrii spektroskopowej jako metoda monitorowania jakości powierzchni materiałów grupy SrxBa1-xNb2O6

The article presents the capabilities of spectroscopic ellipsometry as a fast and nondestructive tool for monitoring of surface quality of photorefractive SrxBa1-xNb2O6 crystals. Optical model with surface roughness layer is shown which allows to determine precisly the values of surface roughness in the fitting procedure of modeled and experimental optical functions. The obtained surface roughness quantities by spectroscopic ellipsometry and atomic force microscopy are in good agreement. (Spectroscopic ellipsometry as a technique for surface quality monitoring of SrxBa1-xNb2O6 materials).

Spectral Signatures Identifying Instrument on Spectroscopic Measurement Technique for Water Quality Monitoring

Spectral measurement is an important technology for measuring algal-chlorophyll in surface water. This paper provides a possibility of spectral signatures in the visible and near infrared, associated with experiments could be conduct to use proposed devise for outdoors in water environments. The overall objective of this study was to use development of micro controller based Spectrometer for finding possible spectral regions in which chlorophyll-a (Chl-a) could be identified so as to assist the assessment and monitoring of water quality spectrometric method. The main target is to develop very low cost effective with mobility and to get current data by accessing remotely. This study based on the application of linear regression analysis between the mean reflectance values (proposed Micro controlled visible Spectrometer-MVSM-C10988MA-01) across the spectrum and the concentrations of chlorophyll-a (μg/L) acquired simultaneously in situ measurement on the same day and time in the Ibaraki University Test Pond in Japan.

Wind Turbine Condition and Power Quality Monitoring by the Approach of Fast Individual Harmonic Extraction

Increasing deployment of wind turbines requires efficient condition monitoring to ensure the safety and availability of these machines. Grid code also requests the operator to enhance the monitoring of the quality of the power generated by the wind turbine. Most commercially available wind turbine condition monitoring systems are supported by a number of vibration transducers. They consequently are complex in hardware, expensive in price, but inefficient in computation and particularly lack of power quality monitoring ability. In view of this, an innovative electrical signal analysis-based wind turbine condition and power quality monitoring technique is developed in this paper by the approach of individual harmonic extraction. The proposed technique has been verified in the lab by applying to detecting both the mechanical and electrical faults emulated on a specially designed wind turbine condition monitoring test rig. Experiments show that the proposed technique is not only sensitive to the faults, but alert to the degradation of power quality.

Characterization of interface quality between various low-temperature oxides and Si using room-temperature-photoluminescence and Raman spectroscopy

Abstract

Simultaneous Dense Differential Phase-Shift Keying Wavelength Division Multiplexing Signal Quality Observation Based on Sequential Ultrafast Field Sampling

This paper describes a signal quality monitoring technique for wavelength division multiplexing (WDM) signals that uses an ultrafast field sampling approach, where the observed signal is parallelly sampled with N channel coherent mixers that include a delay of nT , where n is the channel number and T is the unit delay. Previously, we demonstrated that the technique was able to monitor ON-OFF Keying WDM signals with the aid of a digital finite impulse response filter. In this paper we apply the technique to a dual-channel sampling configuration to monitor differential phase-shift keying (DPSK) WDM signals. We show that the dual 16-branch serial sampling of the total field allows us to observe an 8-ch 25 Gb/s DPSK signal with a total data rate of 200 Gb/s. In addition, the measurement result is comparable to the result obtained by using an optical filter. We also confirm that the technique is capable of monitoring the optical signal to noise ratio (OSNR) up to over 20 dB. Moreover, by adaptively changing the filter profile, we simulate the dependence of the OSNR on the filter profile. In this paper, the technique uses an equivalent sampling approach with a sampling pulse that has a repetition frequency (sampling rate) as low as 10 MHz, so the use of the technology is limited to monitoring the signal. The technique can be used to receive an actual data transmission if the sampling rate is 1/NT, where N is the number of channels.