scholarly journals Detection of drinking water contamination event with Mahalanobis distance method, using on-line monitoring sensors and manual measurement data

2018 ◽  
Vol 18 (6) ◽  
pp. 2133-2141 ◽  
Author(s):  
S. Dejus ◽  
A. Nescerecka ◽  
G. Kurcalts ◽  
T. Juhna
Keyword(s):  
Drinking Water ◽  
Real Time ◽  
Mahalanobis Distance ◽  
Measurement Data ◽  
Early Warning Systems ◽  
Operating Conditions ◽  
Distance Method ◽  
Biological Contamination ◽  
On Line ◽  
Contamination Events

Abstract Concerns about drinking water (DW) quality contamination during water distribution raise a need for real-time monitoring and rapid contamination detection. Early warning systems (EWS) are a potential solution. The EWS consist of multiple conventional sensors that provide the real-time measurements and algorithms that allow the recognizing of contamination events from normal operating conditions. In most cases, these algorithms have been established with artificial data, while data from real and biological contamination events are limited. The goal of the study was the event detection performance of the Mahalanobis distance method in combination with on-line DW quality monitoring sensors and manual measurements of grab samples for potential DW biological contamination scenarios. In this study three contamination scenarios were simulated in a pilot-scale DW distribution system: untreated river water, groundwater and wastewater intrusion, which represent realistic contamination scenarios and imply biological contamination. Temperature, electrical conductivity (EC), total organic carbon (TOC), chlorine ion (Cl-), oxidation–reduction potential (ORP), pH sensors and turbidity measurements were used as on-line sensors and for manual measurements. Novel adenosine-triphosphate and flow cytometric measurements were used for biological water quality evaluation. The results showed contamination detection probability from 56% to 89%, where the best performance was obtained with manual measurements. The probability of false alarm was 5–6% both for on-line and manual measurements. The Mahalanobis distance method with DW quality sensors has a good potential to be applied in EWS. However, the sustainability of the on-line measurement system and/or the detection algorithm should be improved.

scholarly journals Monitoring and diagnostics of special-purpose turbomachines

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Małgorzata Gizelska
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Magnetic Bearing ◽  
Operating Conditions ◽  
Active Magnetic Bearing ◽  
Diagnostic Tools ◽  
Compression Process ◽  
Rotating System ◽  
On Line ◽  
Monitoring And Diagnostics

Abstract In the operation of special-purpose turbomachines, diagnostic tools are necessary. They enable control of the machine technical state and its operation parameters in the on-line mode. The acquisition and processing of the measurement data in real time is crucial as they are indicators of the machine functioning under various operating conditions. The paper presents two types of computer designed diagnostic tools to monitor in real time the dynamic and thermodynamic parameters of special-purpose turbomachines. The first one monitors the dynamics of the rotating system with an active magnetic bearing, the second - monitors the instant value of polytropic efficiency of the compression process, which was designed for the industrial machine.

Artificial Intelligence and Data Analytics for Virtual Flow Metering

2021 ◽  
Author(s):  
Anton Gryzlov ◽  
Liliya Mironova ◽  
Sergey Safonov ◽  
Muhammad Arsalan
Keyword(s):  
Machine Learning ◽  
Multiphase Flow ◽  
Real Time ◽  
Production Control ◽  
Measurement Data ◽  
Sufficient Accuracy ◽  
Operating Conditions ◽  
Machine Learning Techniques ◽  
Flow Metering ◽  
Oil Gas

Abstract Modern challenges in reservoir management have recently faced new opportunities in production control and optimization strategies. These strategies in turn rely on the availability of monitoring equipment, which is used to obtain production rates in real-time with sufficient accuracy. In particular, a multiphase flow meter is a device for measuring the individual rates of oil, gas and water from a well in real-time without separating fluid phases. Currently, there are several technologies available on the market but multiphase flow meters generally incapable to handle all ranges of operating conditions with satisfactory accuracy in addition to being expensive to maintain. Virtual Flow Metering (VFM) is a mathematical technique for the indirect estimation of oil, gas and water flowrates produced from a well. This method uses more readily available data from conventional sensors, such as downhole pressure and temperature gauges, and calculates the multiphase rates by combining physical multiphase models, various measurement data and an optimization algorithm. In this work, a brief overview of the virtual metering methods is presented, which is followed by the application of several advanced machine-learning techniques for a specific case of multiphase production monitoring in a highly dynamic wellbore. The predictive capabilities of different types of machine learning instruments are explored using a model simulated production data. Also, the effect of measurement noise on the quality of estimates is considered. The presented results demonstrate that the data-driven methods are very capable to predict multiphase flow rates with sufficient accuracy and can be considered as a back-up solution for a conventional multiphase meter.

scholarly journals Accurate Real Time On-Line Estimation of State-of-Health and Remaining Useful Life of Li ion Batteries

2020 ◽  
Vol 10 (21) ◽  
pp. 7836
Author(s):  
Cher Ming Tan ◽  
Preetpal Singh ◽  
Che Chen
Keyword(s):  
Lithium Ion Batteries ◽  
Real Time ◽  
Estimation Method ◽  
Lithium Ion ◽  
Threshold Level ◽  
Remaining Useful Life ◽  
Operating Conditions ◽  
State Of Health ◽  
On Line ◽  
Useful Life

Inaccurate state-of-health (SoH) estimation of battery can lead to over-discharge as the actual depth of discharge will be deeper, or a more-than-necessary number of charges as the calculated SoC will be underestimated, depending on whether the inaccuracy in the maximum stored charge is over or under estimated. Both can lead to increased degradation of a battery. Inaccurate SoH can also lead to the continuous use of battery below 80% actual SoH that could lead to catastrophic failures. Therefore, an accurate and rapid on-line SoH estimation method for lithium ion batteries, under different operating conditions such as varying ambient temperatures and discharge rates, is important. This work develops a method for this purpose, and the method combines the electrochemistry-based electrical model and semi-empirical capacity fading model on a discharge curve of a lithium-ion battery for the estimation of its maximum stored charge capacity, and thus its state of health. The method developed produces a close form that relates SoH with the number of charge-discharge cycles as well as operating temperatures and currents, and its inverse application allows us to estimate the remaining useful life of lithium ion batteries (LiB) for a given SoH threshold level. The estimation time is less than 5 s as the combined model is a closed-form model, and hence it is suitable for real time and on-line applications.

The Development and Design of a Laser Detection System for Tire Thickness Measurement

2013 ◽  
Vol 418 ◽  
pp. 128-131
Author(s):  
King Sun Lee
Keyword(s):  
Standard Deviation ◽  
Real Time ◽  
Detection System ◽  
Measurement Data ◽  
Thickness Measurement ◽  
Inspection System ◽  
Laser Sensors ◽  
Repeatability Error ◽  
On Line ◽  
Measuring Machine

This system is a self-developed real-time thickness inspection system including high-precision laser sensors and a mobile platform for on-line detection of tire rubber skin. The measurement data is used to calculate the standard deviation and process capability indices, and to evaluate measurement capacity. The system is a real-time measurement system in which the obtained measuring data compare with the standard value and show any errors. A technician can adjust the process parameters precisely on-line to improve product quality. The standard deviation of repeatability of the system for height is within +/- 0.0081 mm. The repeatability error of the horizontal sliding rail is within 0.0145mm, while the measurement error between this system and a coordinated measuring machine is within 0.028mm.

scholarly journals Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6671
Author(s):  
Sharif Hossain ◽  
Christopher W.K. Chow ◽  
Guna A. Hewa ◽  
David Cook ◽  
Martin Harris
Keyword(s):  
Machine Learning ◽  
Drinking Water ◽  
Real Time ◽  
Learning Algorithm ◽  
Measurement Data ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Kernel Functions ◽  
Support Vector ◽  
Organic Nitrate

The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) can be better achieved by separating its spectra from the combined spectra. In this paper, two major focuses are (i) the separation of monochloramine spectra from the combined spectra and (ii) assessment of the application of the machine learning algorithm in real-time detection of monochloramine. The support vector regression (SVR) model was developed using multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectra and online amperometric monochloramine residual measurement data. The performance of the SVR model was evaluated by using four different kernel functions. Results show that (i) particles or turbidity in water have a significant effect on UV-Vis spectral measurement and improved modelling accuracy is achieved by using particle compensated spectra; (ii) modelling performance is further improved by compensating the spectra for natural organic matter (NOM) and nitrate (NO3) and (iii) the choice of kernel functions greatly affected the SVR performance, especially the radial basis function (RBF) appears to be the highest performing kernel function. The outcomes of this research suggest that disinfectant residual (monochloramine) can be measured in real time using the SVR algorithm with a precision level of ± 0.1 mg L−1.

On-Line Tracking and Monitoring of Rolling Element Bearing Faults

2014 ◽  
Author(s):  
S. Chatterton ◽  
P. Borghesani ◽  
P. Pennacchi ◽  
A. Vania
Keyword(s):  
Real Time ◽  
Damage Index ◽  
Vibration Signal ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Simple Task ◽  
Alarm Signaling ◽  
Rolling Element ◽  
On Line ◽  
Element Bearing

Diagnostics of rolling element bearings is usually performed by the analysis of vibration signal using suitable signal analysis tools, such as the most used and simplest method, Envelope Analysis. This method is based on the identification of bearing damage frequency components in the so-called Square Envelope Spectrum. If the assessment of the bearing health is quite a simple task, the on-line monitoring and the real-time evaluation of the trend of a suitable damage index is a complex task to be performed in an automatic way. The damage index must be robust against variations of system operating conditions and external vibration sources to avoid misleading results. The damage index should be also simple to be evaluated in the case of real-time applications. In the paper, the case of a rolling element bearing in which the defect develops until a permanent failure is described as well as the algorithm implemented for alarm signaling.

scholarly journals Analisa Perbandingan GPS Google Maps Dan GPS Google Earth Dalam Penentuan Titik Koordinat Breeding Place

Respati ◽  
2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Andhy Sulistyo ◽  
Anton Yudhana ◽  
Sunardi Sunardi ◽  
Resmi Aini
Keyword(s):  
Real Time ◽  
Global Positioning System ◽  
Measurement Data ◽  
Google Earth ◽  
Positioning System ◽  
Individual Data ◽  
Google Maps ◽  
Distance Method ◽  
Global Positioning ◽  
Breeding Place

INTISARINyamuk  Aedes  Aegypti menularkan penyakit DBD (Demam Berdarah Dengue) ke manusia dengan gigitannya. Breeding Place  merupakan berkembangbiaknya  jentik nyamuk di tempat penampungan air yang tidak beralaskan tanah  kurang  menjadi pantauan oleh masyarakat. GPS (Global Positioning System) adalah sistem satelit navigasi dan pemantauan posisi koordiinat bumi. Proses pengambilan lokasi Breeding Place tersebut akan diperoleh koordinat yang disebut waypoint (garis lintang dan bujur pada peta). Google Maps dan GoogleEarth saat ini telah tersedia untuk Android dan menawarkan keseluruhan layanan yang dimiliki Google. Salah satu fitur yang bermanfaat bagi banyak orang adalah informasi titik koordinat  GPS lintang dan bujurnya.Google Maps dirancang untuk memenuhi kebutuhan dari penggunanya. Seperti mencari bisnis lokal, melihat peta, mendapatkan petunjuk, informasi lalu lintas real-time, melihat jadwal keberangkatan masih banyak lagi.Sementara Google Earth dapat membawa  pada  virtual tempat-tempat indah yang berbeda di belahan bumi. Google Earth dapat diasumsikan sebagai bagian dari Google Maps. Tapi, lebih mengutamakan pengalaman daripada utilitas.Penelitian ini bertujuan membandingkan tingkat akurasi antara Gooogle Maps dan Google Earth dengan metoda linier jarak(phytagoras) untuk mengetahui titik koordinat Breeding Place di lingkungan penduduk. Hasil uji linier jarak data diolah menggunakan  standar deviasi untuk mengindikasikan ketelitian atau kedekatan setiap individual data terhadap data lainnya, pada suatu pengamatan terhadap objek tertentu. Dengan semakin besarnya nilai standar deviasi, maka tingkat ketelitian data hasil pengukuran dapat dikatakan burukKata kunci —GPS,Breeding Place,Gooogle Maps,Google Earth. ABSTRACTAedes Aegypti mosquitoes transmit DHF (Dengue Hemorrhagic Fever) to humans with bites. Breeding Place is the breeding of mosquito larvae in water shelters that are not grounded and are not monitored by the community. GPS (Global Positioning System) is a navigation satellite system and monitoring the Earth's coordinating position. The process of taking the location of the Breeding Place will be obtained by the coordinates called waypoint (latitude and longitude on the map). Google Maps and Google Earth are now available for Android and offer all of Google's services. One feature that is useful for many people is information on the latitude and longitude GPS coordinates. Google Maps is designed to meet the needs of its users. Like looking for a local business, looking at maps, getting instructions, real-time traffic information, see more departure schedules. While Google Earth can bring to virtual different beautiful places in the hemisphere. Google Earth can be assumed as part of Google Maps. But, prioritizing experience rather than utility.This study aims to compare the level of accuracy between Gooogle Maps and Google Earth with the linear distance method(phytagoras) to find out the coordinates of Breeding Place in a population environment. The linear test distance of the data is processed using standard deviations to indicate the accuracy or proximity of each individual data to other data, in an observation of a particular object. With the increasing standard deviation value, the level of accuracy of the measurement data can be said to be badKeywords— GPS,Breeding Place,Gooogle Maps,Google Earth.INTISARINyamuk  Aedes  Aegypti menularkan penyakit DBD (Demam Berdarah Dengue) ke manusia dengan gigitannya. Breeding Place  merupakan berkembangbiaknya  jentik nyamuk di tempat penampungan air yang tidak beralaskan tanah  kurang  menjadi pantauan oleh masyarakat. GPS (Global Positioning System) adalah sistem satelit navigasi dan pemantauan posisi koordiinat bumi. Proses pengambilan lokasi Breeding Place tersebut akan diperoleh koordinat yang disebut waypoint (garis lintang dan bujur pada peta). Google Maps dan GoogleEarth saat ini telah tersedia untuk Android dan menawarkan keseluruhan layanan yang dimiliki Google. Salah satu fitur yang bermanfaat bagi banyak orang adalah informasi titik koordinat  GPS lintang dan bujurnya.Google Maps dirancang untuk memenuhi kebutuhan dari penggunanya. Seperti mencari bisnis lokal, melihat peta, mendapatkan petunjuk, informasi lalu lintas real-time, melihat jadwal keberangkatan masih banyak lagi.Sementara Google Earth dapat membawa  pada  virtual tempat-tempat indah yang berbeda di belahan bumi. Google Earth dapat diasumsikan sebagai bagian dari Google Maps. Tapi, lebih mengutamakan pengalaman daripada utilitas.Penelitian ini bertujuan membandingkan tingkat akurasi antara Gooogle Maps dan Google Earth dengan metoda linier jarak(phytagoras) untuk mengetahui titik koordinat Breeding Place di lingkungan penduduk. Hasil uji linier jarak data diolah menggunakan  standar deviasi untuk mengindikasikan ketelitian atau kedekatan setiap individual data terhadap data lainnya, pada suatu pengamatan terhadap objek tertentu. Dengan semakin besarnya nilai standar deviasi, maka tingkat ketelitian data hasil pengukuran dapat dikatakan burukKata kunci —GPS,Breeding Place,Gooogle Maps,Google Earth. ABSTRACTAedes Aegypti mosquitoes transmit DHF (Dengue Hemorrhagic Fever) to humans with bites. Breeding Place is the breeding of mosquito larvae in water shelters that are not grounded and are not monitored by the community. GPS (Global Positioning System) is a navigation satellite system and monitoring the Earth's coordinating position. The process of taking the location of the Breeding Place will be obtained by the coordinates called waypoint (latitude and longitude on the map). Google Maps and Google Earth are now available for Android and offer all of Google's services. One feature that is useful for many people is information on the latitude and longitude GPS coordinates. Google Maps is designed to meet the needs of its users. Like looking for a local business, looking at maps, getting instructions, real-time traffic information, see more departure schedules. While Google Earth can bring to virtual different beautiful places in the hemisphere. Google Earth can be assumed as part of Google Maps. But, prioritizing experience rather than utility.This study aims to compare the level of accuracy between Gooogle Maps and Google Earth with the linear distance method(phytagoras) to find out the coordinates of Breeding Place in a population environment. The linear test distance of the data is processed using standard deviations to indicate the accuracy or proximity of each individual data to other data, in an observation of a particular object. With the increasing standard deviation value, the level of accuracy of the measurement data can be said to be badKeywords— GPS,Breeding Place,Gooogle Maps,Google Earth.

scholarly journals Technical note: Efficient online source identification algorithm for integration within a contamination event management system

2017 ◽  
Vol 10 (2) ◽  
pp. 53-59
Author(s):  
Jochen Deuerlein ◽  
Lea Meyer-Harries ◽  
Nicolai Guth
Keyword(s):  
Drinking Water ◽  
Real Time ◽  
Early Warning ◽  
Source Identification ◽  
Management System ◽  
Distribution Networks ◽  
Early Warning Systems ◽  
Optimal Placement ◽  
Identification Algorithm ◽  
Event Management

Abstract. Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

How Bulk Modulus Errors Can Affect Leak Detection

1996 ◽  
Author(s):  
Henry H. Rachford ◽  
Andrew Wike
Keyword(s):  
Bulk Modulus ◽  
Measurement Data ◽  
Leak Detection ◽  
Operating Conditions ◽  
Time Data ◽  
Transient Model ◽  
Property Data ◽  
Wide Range ◽  
Fluid Properties ◽  
On Line

Liquid pipeline operators look to leak detection systems to provide continuous surveillance of their pipelines across a wide range of operating conditions; this is particularly the case for batch pipelines. Operators frequently anticipate that on-line transient modeling systems can satisfy this requirement, which they can, but have little exposure to the on-line measurement data requirements of such systems. There can be a mistaken focus on improving the quality of the real-time data normally available to facilitate pipeline operations, without due regard to providing the measurement data that the model needs. Pipeline operators are normally not concerned with a detailed characterization of fluid properties, other than in the most general sense regarding the susceptibility of adjacent fluids to mix at their interface. This paper illustrates how the lack of reliable fluid property data (specifically, bulk modulus data) can substantially impede the effectiveness of a transient model charged with the task of leak detection.

Management of sensible water uses with real-time measurements

2002 ◽  
Vol 46 (3) ◽  
pp. 33-40 ◽  
Author(s):  
N. Fleischmann ◽  
K. Staubmann ◽  
G. Langergraber
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Warning System ◽  
Monitoring Network ◽  
The Internet ◽  
Grab Sampling ◽  
Validation Data ◽  
Monitoring Network Design ◽  
Control Centre ◽  
On Line

For the protection of bankside wells and a groundwater recharge an early warning system had to be developed. The monitoring network design is based on sensor measurements only. For this purpose a new submersible spectrometer has been successfully tested for multi-parameter measurements directly in the medium. The developed system can easily be upgraded with other new sensors. Only calibration and validation data are supplied by conventional grab sampling and laboratory analysis.. A conventional testfilter improved by on-line monitoring at 5 sampling sites serves as a reference system. The whole system is equipped with remote control and the internet serves as the control centre of the network. All measurement data from all 9 sites are available in real time on the internet.

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