On-line Monitoring Applications Research Articles

Fe3O4 Magnetic Nanoparticles as Peroxidase Mimetics Used in Colorimetric Determination of 2,4-Dinitrotoluene

Fe3O4 magnetic nanoparticles (Fe3O4 MNPs) were prepared by co-precipitation method, which possessed intrinsic peroxidase-like activity. It was found that the as-prepared Fe3O4 MNPs could not only catalyze the oxidation of peroxidase substrate, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate acid) (ABTS) by H2O2 to produce the colored product with maximum absorbance at 417 nm, but also catalyze the oxidation of 2,4-dinitrotoluene (DNT) by H2O2 and thus consume H2O2 in the reaction system. On the basis of the reaction mechanism described above, a novel colorimetric reaction system of Fe3O4 MNPs-ABTS-H2O2-DNT was established for the determination of trace amount of DNT. Some key influencing factors of the proposed Fe3O4 MNPs-ABTS-H2O2-DNT system were systematically discussed and optimized. Under the optimal conditions, the absorbance of the system at 417 nm displayed a good linear relationship with DNT concentration in the range from 5.0 × 10−7 M to 2.0 × 10−5 M with a detection limit of 1.5 × 10−7 M (S/N = 3). These results demonstrated that the constructed colorimetric method was simple, rapid and sensitive enough for the detection of DNT, which would have a great potential in the application of on-line monitoring of DNT in environmental water samples

Novel detection method for DC series arc faults by using morphological filtering

It has been known that DC arc faults pose a hazard in power electronics systems. Due to the fault current is lower than normal current load, series arc is more difficult to be discovered than parallel arc. The traditional methods of DC series arc faults detection have some disadvantages, such as large computation, long delay and easier influence by interferences. In this paper, a novel method with multi-scale morphological filtering was utilized for the fault detection of DC series arc. Compared to the tradition method, the proposed method is more simple and efficient. It was verified that it was convenient for field application of on-line monitoring and diagnosis with a good ability to prevent misjudgments from the environment interference.

Optically heated ultra-fast-cycling gas chromatography module for separation of direct sampling and online monitoring applications.

This work describes an ultrafast-cycling gas chromatography module (fast-GC module) for direct-sampling gas chromatography/mass spectrometry (GC-MS). The sample can be introduced into the fast-GC module using a common GC injector or any GC × GC modulator. The new fast-GC module offers the possibility to conduct a complete temperature cycle within 30 s. Its thermal mass is minimized by using a specially developed home-built fused silica capillary column stack and a halogen lamp for heat generation, both placed inside a gold-coated quartz glass cylinder. A high airflow blower enables rapid cooling. The new device is highly flexible concerning the used separation column, the applied temperature program, and the integration into existing systems. An application of the fast-GC module is shown in this work by thermal analysis coupled to gas chromatography-mass spectrometry (TA-GC-MS). The continuously evolving gases of the TA are modulated by a liquid CO2 modulator. Because of the rapid cycling of the fast-GC module, it is possible to obtain the best separation while maintaining the online character of the TA. Restrictions in separation and retention time shifting, known from isothermal and normal ramped fast-GC systems, are overcome.

Gas-sensing array application for on-line monitoring in a heat-responsive bioprocess of Streptomyces griseus HUT 6037

The stress-responsive bioprocess concept has been developed into an environmentally friendly biosensor with low energy consumption and high recovery yield. To improve chitosanase production during Streptomyces griseus cultivation, heat-stress was applied to the bioprocess with monitoring using an on-line gas sensing system. When exposed to heat-stress with liposomes, the chitosanase productivity was 2.6 times greater than for conventional cultivation. The mixed gas components could be distinguished using a principal component analysis during chitosanase production. The online-monitoring system reflected basic changes in growth conditions and metabolite formation in cells. The array type gas-sensing system was capable of detecting bacterial infection faster than conventional sensor systems. The gas sensor system can play a key role in monitoring and controlling stress levels in a stress-responsive bioprocess.

A review of recent application of near infrared spectroscopy to wood science and technology

This review article introduces recent scientific and technical reports due to near infrared spectroscopy (NIRS) at wood science and technology, most of which was published between 2006 and 2013. Many researchers reported that NIR technique was useful to detect multi traits of chemical, physical, mechanical and anatomical properties of wood materials although it was widely used in a state where characteristic cellular structure was retained. However, we should be sensitive and careful for application of NIRS, when spectra coupled with chemometrics presents unexpected good results (especially, for mechanical physical and anatomical properties). The real application for on-line or at-line monitoring in wood industry is desired as next step. Basic spectroscopic research for wooden material is also progressed. It should be a powerful and meaningful analytical spectroscopic tool.

Reservoir computing compensates slow response of chemosensor arrays exposed to fast varying gas concentrations in continuous monitoring

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively controlled instrument configurations where the sensor array is placed within a closed measurement chamber. Usually, the experimental protocol is defined beforehand and it includes three stages: the array is first exposed to a gas reference, then to the gas sample, and finally to the reference again to recover the initial state. Such sampling procedure requires signal acquisition during the complete experimental protocol and usually delays the output prediction until the predefined measurement duration is complete. Due to the slow time response of chemical sensors, the completion of the measurement typically requires minutes. In this paper we propose the use of reservoir computing (RC) algorithms to overcome the slow temporal dynamics of chemical sensor arrays, allowing identification and quantification of chemicals of interest continuously and reducing measurement delays. We generated two datasets to test the ability of RC algorithms to provide accurate and continuous prediction to fast varying gas concentrations in real time. Both datasets – one generated with synthetic data and the other acquired from actual gas sensors – provide time series of MOX sensors exposed to binary gas mixtures where concentration levels change randomly over time. Our results show that our approach improves the time response of the sensory system and provides accurate predictions in real time, making the system specifically suitable for online monitoring applications. Finally, the collected dataset and developed code are made publicly available to the research community for further studies.

Facile solvothermal synthesis of Ag/Fe3O4 nanocomposites and their SERS applications in on-line monitoring of pesticide contaminated water

The dual-functional substrates of Ag/Fe3O4 exhibit excellent SERS performance, and have been successfully applied in real-time on-line monitoring of wastewater.

Development and Application of On-Line Monitor for the ZLW-1 Axis Cracks

This article mainly introduces a method that uses acoustic emission techniques to achieve on-line monitor for the shaft cracks and crack growth.According to this method,axis crack monitor is produced by acoustic emission techniques.This instrument can apply to all the pressure vessels,pipelines and rotor machines that can bear buckling load.It has the online real-time monitoring,automatic recording,printing,sound and light alarm,collecting crack information function.After a series of tests in both laboratory and field,it shows that this instrument is very versatile and possesses broad prospects of development and application.

Development of distinct load signatures for higher efficiency of NILM algorithms

A simple and novel methodology for the configuration of robust and distinct load signatures is presented in this paper. A technique based on a spectral analysis of the current waveform of each load is proposed, leading to load signatures consisting of three distinct spectral coefficients. Data required for each load signature come from only one period of the current waveform, under a sampling frequency at the order of kHz. A simple identification algorithm has also been developed in order to estimate the signatures adequacy. Each appliance has been measured and classified as an individual load, using a simple identification procedure. Data obtained from two different measurement sets show that the proposed technique provides unique data formations for each appliance tested by developing an efficient recognition procedure with high levels of identification rate. Due to the simplicity of both the database configuration and the identification procedure, the proposed methodology could be considered appropriate for online monitoring and real time smart grid applications.

Compendium of Sensors and Monitors and Their Use in the Global Water Industry

Online monitoring of water quality is an powerful enabler in the water industry. It is a crucial component in the pro-active management of processes and assets, and helps improve performance and cost efficiency. Instrumentation for the monitoring of most water quality parameters is commercially available. Implementation of such equipment, however, remains largely limited to a small number of basic parameters and is still confined to key nodes in collection, treatment and distribution systems. A primary hurdle to further realization of the potential of online monitoring is the lack of publicly available information on system performance, key drivers and barriers (technical, economic and social) to successful implementation. A study was performed to identify and document information on commercially available instrument types, associated costs (capital and operating), and real-world experiences with the use of sensors in the global water / wastewater industry. This information was compiled in an online compendium, to facilitate sharing of information and learning from experience.The study has shown that the current generation of technology is suitable for routine operation. However, there is no one-size-fits-all solution to monitoring questions. Furthermore, successful application of on-line water quality monitoring requires commitment of considerable resources, which need to be accompanied by a solid QA/QC plan. Furthermore, the understanding and appreciation of monitoring and the efforts required to make it a success need to be embedded and supported at all levels within an organization.Deciding whether on-line monitoring is the best solution to a need for information has to be done in careful process. Defining needs and requirements, building a business case around this and then carefully working out the specifications and all organizational aspects of the monitoring program are prerequisites for effective implementation and to prevent surprises and disappointmentThis title belongs to WERF Research Report Series.ISBN: 9781780406695 (eBook)

Towards a portable Raman spectrometer using a concave grating and a time-gated CMOS SPAD.

A low-cost, compact Raman spectrometer suitable for the on-line water monitoring applications is explored. A custom-designed concave grating for wavelength selection was fabricated and tested. The detection of the Raman signal is accomplished with a time-gated single photon avalanche diode (TG-SPAD). A fixed gate window of 3.5ns is designed and applied to the TG-SPAD. The temporal resolution of the SPAD was ~60ps when tested with a 7ps, 532nm solid-state laser. To test the efficiency of the gating in fluorescence signal suppression, different detection windows (3ns-0.25ns) within the 3.5ns gate window are used to measure the Raman spectra of Rhodamine B. Strong Raman peaks are resolved with this low-cost system.

Highly sensitive and selective detection of Pb2+ ions using a novel and simple DNAzyme-based quartz crystal microbalance with dissipation biosensor.

A novel, label-free DNAzyme-based quartz crystal microbalance with dissipation monitoring (QCM-D) biosensor was developed for the highly sensitive and specific detection of Pb(2+) ions. To enhance the performance of the sensor, oligonucleotide-functionalized gold nanoparticles were used for both frequency and dissipation amplification. This sensor was developed by immobilizing Pb(2+)-specific DNAzymes onto the QCM-D sensor surface and allowing them to hybridize with substrate-functionalized AuNPs. The DNAzyme catalyzed the cleavage of the substrate in the presence of Pb(2+) ions, causing the cleaved substrate-functionalized AuNPs to be removed from the sensor surface. Thus, Pb(2+) ions can be determined on-line by monitoring the change in frequency and dissipation signals. The results revealed that the sensor showed a sensitive response to Pb(2+) ions with detection limits of 14 nM and 20 nM for frequency and dissipation, respectively. This QCM-D biosensor also exhibited excellent selectivity toward Pb(2+) ions in the presence of other divalent metal ions. In addition, the approach was able to detect Pb(2+) in tap water, demonstrating its great potential for monitoring drinking water quality. The proposed sensor system described here represents a new class of lead ion sensor. Its simple detection strategy makes it feasible for 'pollution-free' detection; thus, the approach could have applications in on-line water quality monitoring.

Determination of moisture content of polyamide 66 directly from combination region near‐infrared spectra

ABSTRACTThe hygroscopic nature of polyamide (PA) polymers motivates the development of analysis tools for use in assessing their moisture content. Among possible analysis techniques, near‐infrared (near‐IR) spectroscopy is non‐destructive, requires little or no sample preparation, and is compatible with sample thicknesses on the order of mm. The work reported here makes use of transmission near‐IR spectroscopy in the combination region (5000–4000 cm−1) to develop a protocol for assessing the moisture content of PA 66 samples directly from their spectral intensities after preprocessing with the standard normal variate transform and partial least‐squares. The method is compatible with online or continuous monitoring applications and can be calibrated without the use of destructive reference measurements such as thermogravimetric analysis. The long‐term calibration performance of the technique is evaluated, and on a scale of 0–100% moisture uptake, the standard error of prediction is found to average 1.4% over 6 months. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40645.

Data Compression of Structural Seismic Responses via Principled Independent Component Analysis

This paper proposes a novel lossy data compression scheme for structural seismic responses based on principled (truncated) independent component analysis (PICA). It is first shown that independent component analysis (ICA) is able to transform a multivariate data set into a sparse representation space where is optimal for coding and compression, such that both the intradependencies and interdependencies (i.e., redundant information) between the multichannel data are removed for efficient data compression. Two examples are presented to demonstrate the compression performance of PICA, using the real-measured structural seismic responses from the 1994 Northridge earthquake, of the Fire Command Control (FCC) building and the USC hospital building, respectively. It is compared with the popular wavelet transform coding technique, which is only able to handle single-channel data separately. Results show that PICA achieves dramatically higher compression ratio (CR) than the wavelet method while retaining excellent reconstruction accuracy. It is also shown that PICA slightly outperforms the (principled) principal component analysis (PCA) method—which used to be considered optimal multivariate data compression scheme—with respect to both CR and reconstruction accuracy. Equipped with the FastICA algorithm that enjoys a cubic convergence rate, PICA has potential for rapid and reliable data transfer, communication (e.g., multihop wireless sensor network), storage, and retrieval in online or post-disaster (e.g., earthquake) monitoring and assessment applications of civil infrastructures.

Boiling detection in a LMFBR using autoregressive models and SVM

This paper deals with acoustic detection of sodium boiling in a Liquid Metal Fast Breeder Reactor (LMFBR) cooled by liquid sodium. As sodium boiling induces acoustic emission, the method consists in real time analysis of acoustic signals measured through wave guides. Auto Regressive (AR) models are estimated on sliding windows and are classified in boiling or non-boiling models using Support Vector Machines (SVM). One of the difficulties to cope with is disturbances due to the influence of some environment noises like the liquid coolant cavitation, vortex flow, shaft vibration and mechanical pump noise. These disturbances can generate false alarms or mask the boiling. The proposed method is designed to be robust toward these disturbances. Furthermore, the SVM are designed to be robust toward the operating mode changing. The application for online monitoring is made on data obtained from French nuclear power plant Phenix and boiling sound signals generated from laboratory experiments. Different acoustic boiling sound levels are used and the effectiveness of the method is shown by the good detection rate and its low false alarm rate even for low acoustic boiling sound level.

Continuous Prediction in Chemoresistive Gas Sensors Using Reservoir Computing

Abstract Chemoresistive gas sensors, and Metal Oxide (MOX) sensors in particular, are predominant choices to perform funda- mental tasks of chemical detection due to their sensitivity, ease of use, low-cost, and fast response time compared to other technologies. Yet, their use has been mainly limited to relatively controlled scenarios where a gas sensor array is first exposed to a reference, then to the gas sample, and finally to the reference again to recover the initial state. In this paper we propose the use of MOX sensors along with Reservoir Computing algorithms to identify chemicals of interest. Our approach allows continuous gas monitoring in simple experimental setups without the requirement of acquiring recovery transient of the sensors, thereby making the system specifically suitable for online monitoring applications.

Online monitoring of flue gas emissions in power plants having multiple fuels

This paper introduces an online monitoring application for flue gas emission measurements. The monitoring is conducted by analytical redundancy by estimating the monitored measurement variables. The estimated variables are CO2, H2O, flue gas flow and combustion air flow. Additionally, SO2 content in the flue gas can be estimated with certain limitations. The monitoring method is based on physical combustion modeling and is therefore boiler structure and fuel independent. The model is valid for multiple fuels as long as the fuel flow measurements, fuel properties and flue gas O2 measurement are available. The estimates can further be improved by flue gas CO measurement. The monitoring method was successfully tested in an industrial wood, peat, bark and slurry fired power plant. The results verify that the method is able to automatically separate sensor faults and process disturbances.

Progress and trend of sensor technology for on-line oil monitoring

Oil monitoring constitutes an important and essential component of condition monitoring technologies and has distinguished advantages in revealing wear, lubrication and friction conditions of tribo-pairs. Newly developed on-line/in-line oil monitoring technologies extend the merits into real-time applications and demonstrate significant benefits in maintenance and management of equipment. This paper comprehensively reviews the progress of on-line/in-line oil monitoring techniques including sensor technologies, their scopes and industrial applications. Based on the existing developments and applications of the sensors for oil quality and wear debris measurements, the trends for future sensor developments are discussed with focuses on accurate, integrated and intelligent features along with exploring a fundamental issue, that is, acquiring the knowledge on degradation mechanisms which has not received sufficient attention until now. Current status of applications of on-line oil monitoring is also reviewed. Although limited reports have been found on this topic, increasing awareness and encouraging progress in on-line monitoring techniques are recognized in applications such as aircraft, shipping, railway, mining, etc. Key fundamental issues for further extending the on-line oil monitoring techniques in industries are proposed and they include long-term reliability of sensors in harsh conditions, and agreement with fault or maintenance determination.

Identification of sit-to-stand and stand-to-sit transitions using a single inertial sensor.

In order to enhance the quality of life of people with mobility problems like Parkinson's disease or stroke patients, it is crucial to monitor and assess their daily life activities by characterizing basic movements like postural transitions, which is the main goal of this work. This paper presents a novel postural transition detection algorithm which is able to detect and identify Sit to Stand and Stand to Sit transitions with a Sensitivity of 88.2% and specificity of 98.6% by using a single sensor located at the user's waist. The algorithm has been tested with 31 healthy volunteers and an overall amount of 545 transitions. The proposed algorithm can be easily implemented in real-time system for on-line monitoring applications.

Influence of temperature, moisture content and ageing on oil impregnated paper bushings insulation

Insulators or bushings are one of the most common cause of transformer failures especially those with fire and collateral damage. This can be prevented by application of off-line and on-line monitoring, especially by measuring of capacitance C and dielectric dissipation factor tanδ, but current physical understanding of these parameters should be improved. A complex research of temperature dependence of C and tanδ, which is based on measurements on a specially designed oil impregnated paper bushing models with different moisture contents in the insulation and during artificial ageing, is presented in the paper. Useful relationships, which enable calculation of tanδ as a function of observed influencing parameters, are also presented.