Research on the Technology of Middleware of Distributed Spectrum Monitoring System

2014 ◽  
Vol 599-601 ◽  
pp. 1057-1063
Author(s):  
Mei Lei Jiang ◽  
Jian Feng Feng ◽  
Kai Li

Currently, the electromagnetic environment has become more and more complicated. So, the research of real-time monitoring and analysis of regional radio signals and real-time display the electromagnetic situation of the region is more and more important. In this paper, the related technologies of the spectrum of existing monitoring systems is in-depth studied, and its own characteristics is analyzed, and on this basis, the reasons of using a distributed spectrum monitoring system is discussed. Secondly, for the demand of the issue, this paper put forward a design concept of distributed spectrum monitoring system which based on middleware, in other words, to apply the middleware technology to the distributed spectrum monitoring system, using the middleware to achieve the distribution of tasks and transmission of the results when coping with multiple testing tasks. Finally, designed and implemented the middleware, and the reliability and performance of middleware have been tested.

2021 ◽  
Author(s):  
Vadim Goryachikh ◽  
Fahad Alghamdi ◽  
Abdulrahman Takrouni

Abstract Background information Natural gas liquid (NGL) production facilities, typically, utilize turbo-expander-brake compressor (TE) to generate cold for C2+ separation from the natural gas by isentropic expansion of feed stream and use energy absorbed by expansion to compress residue gas. Experience shows that during operational phase TE can exposed to operation outside of design window that may lead to machine integrity loss and consequent impact on production. At the same time, there is a lack of performance indicators that help operator to monitor operating window of the machine and proactively identify performance deterioration. For instance, TE brake compressor side is always equipped with anti-surge protection system, including surge deviation alarms and trip. However, there is often gap in monitoring deviation from stonewall region. At the same time, in some of the designs (2×50% machines) likelihood of running brake compressor in stonewall is high during one machine trip or train start-up, turndown operating modes. Also, typical compressor performance monitoring systems does not have enough dynamic parameters that may indicate machine process process performance deterioration proactively (real-time calculation of actual polytrophic efficiency, absorbed power etc.) and help operator to take action before catastrophic failure occurs. In addition, typical compressor monitoring systems are based on assumed composition and fixed compressibility factor and do not reflect actual compositions variations that may affect machine performance monitoring. To overcome issues highlighted above, Hawiyah NGL (HNGL) team has developed computerized monitoring and advisory system to monitor the performance of turbo-expander-brake compressor, proactively, identify potentially unsafe conditions or performance deterioration and advice operators on taking necessary actions to avoid unscheduled deferment of production. Computerized performance monitoring system has been implemented in HNGL DCS (Yokogawa) and utilized by control room operators on day-to-day basis. Real-time calculation, analysis and outputs produced by performance monitoring system allow operator to understand how current operating condition are far from danger zone. Proactive deviation alarms and guide messages produce by the system in case of deviation help operators to control machine from entering unsafe region. Actual polytrophic efficiency, adsorbed power calculations provide machine condition status and allow identifying long-term performance deterioration trends.


Author(s):  
Scot McNeill ◽  
Paul Angehr ◽  
Dan Kluk ◽  
Tomokazu Saruhashi ◽  
Ikuo Sawada ◽  
...  

A method is described for determining quasi-static and dynamic riser angles using measured data typically found in a riser fatigue monitoring system, specifically acceleration and angular rate data. Quasi-static riser inclination and orientation of the inclination plane are determined from the low frequency triaxial accelerations, containing measurement of the gravitational body force. Components of the gravitational body force along the accelerometer axes vary slowly with the riser quasi-static response. The slowly varying Euler angles are determined from the components of gravity along the three axes. Dynamic riser inclination along and transverse to the quasi-static inclination plane are determined by integration of the angular rates, followed by transformation into a coordinate system aligned with the quasi-static inclination plane. The quasi-static and dynamic inclination angles are combined to arrive at the time trace of riser inclination angles. Following implementation of the method in Matlab®, the procedure was validated and the program verified using laboratory test data. A double-gimbaled platform was constructed, on which were mounted a triaxial accelerometer, biaxial angular rate and biaxial inclinometer (reference sensor). A battery of static and dynamic tests was carried out on the platform. Machinists’ levels and angle gauges were used to set the inclination in the various tests. The angles derived from the acceleration and angular rate data were compared to those of the reference inclinometer. Angle estimates were shown to match the reference angles with negligible error. The method was then implemented into the real-time Riser Fatigue Monitoring System (RFMS) aboard the Chikyu drillship. The algorithm was run using data from an emergency disconnect event that occurred in November, 2012. Quasi-static riser inclination angles were quite large due to high currents near the sea surface. Dynamic riser inclination angles proved to be significant due to Vortex Induced Vibration of the lower portion of the riser that immediately followed the disconnect event. It is important to note that the method uses data that is typically already included in real-time riser monitoring systems. Therefore only a software update is required to provide real-time riser angle information. If the method is built into data processing routines for real-time riser monitoring systems, the need for additional instrumentation, such as inclinometers near flex joints, may be circumvented. On the other hand, if inclinometers already exist, the method serves as an independent source of riser angle information at several locations on the riser. The method can also be used to calculate riser and Blow out Preventer (BOP) stack angles from data recorded using stand-alone, battery-powered loggers.


2011 ◽  
Vol 121-126 ◽  
pp. 3750-3754 ◽  
Author(s):  
Chung Chiang Hu ◽  
Shing Han Li ◽  
Tien Wei Tsai

The equipments in computer rooms are complicated in nature. Many factors may influence their normal operations, for example: voltage, temperature, humidity, and the normalcy of systems. It would be prudent to have a monitoring system to prevent from unpredictable problems. Most monitoring systems in the market can only issue alarms in abnormal situations and then analyze the aftermath. They are also expansive and lack the ability for distant instant control. To tackle this problem, after our successful and practical experiments, we utilize GSM text messaging ability (i.e. SMS, short message service) and make distant monitoring possible. The monitoring system is established with a reasonable price that is well below current market. With this system, the manager/administrator can monitor the real-time status of equipments in computer rooms, send control commands through SMS and then get them executed to solve the problems instantly and effectively.


2020 ◽  
Vol 61 (1) ◽  
pp. 11-20
Author(s):  
Pham Cong Khai ◽  
Nguyen Van Hai ◽  

This paper presents results of investigating, designing, and building a monitoring system in real-time based on GNSS CORS technology in order to monitor landslides at Xekaman 3 hydropower plant in the Lao people’s Democratic Republic. A system with 18 monitoring stations and a CORS station has been designed to ensure the operation of system 24/7. The connection diagram for data transmission from the monitoring stations to the data processing center, as well as the connection diagram of the devices at a monitoring station has been designed. A simulation experiment has shown that the designed system can be applied for real-time monitoring of landslide.


2014 ◽  
Vol 624 ◽  
pp. 647-650
Author(s):  
Hong Mei Cao

Large span bridges are very important infrastructure of the nations. The enormous investment and significance in state economy make them get more and more recognition. At present, the technology of the safety monitoring of bridges is becoming a hotspot in both academic and engineering field. Now, safety monitoring systems of the structures have been applied to many large bridges in the world. Among all these parameters which can indicate the safety status of bridges, the deflection is indispensable. Although there are lots of sensors now used to measure the degrees of the deflection, it is still very scarce that the sensors can be made for long-distance, real-time and automatic online completely. The photo-electricity and liquid level deflection sensors (PLLD) introduced here are cheaper and of better-automaticity and higher precision and can work online continuously without contact. This paper will show the structure, performance and theory of our new sensor based on ARM7 in detail. In the end, a concrete application instance in XiaoGou bridge of ShanXi province will be given.


Author(s):  
A Consilvio ◽  
M Iorani ◽  
V Iovane ◽  
M Sciutto ◽  
G Sciutto

Continuous welded rail maintenance plays a significant role in ensuring high levels of rail traffic and safety. Temperature variations, excessive alignment defects, decreased fastening system resistance and train braking (always in the same stretches and in the same direction) may result in rail buckling or rail breaks. The current traditional monitoring systems and procedures for continuous welded rail consist of programmed discontinuous diagnostic surveys that require personnel intervention on site. Moreover, these traditional systems often imply destructive and invasive operations on the track that may lead to interruption of railway operations. This paper proposes a Rail Strain Monitoring System (RSMS) that performs a real-time rail strain monitoring and allows rail inspection without personnel on site. Using strain gauges and temperature sensors, placed on the rail in specific measurement points, the proposed Rail Strain Monitoring System performs a multi-parameter check by measuring, at the same time, the temperature, the rail strain and the neutral temperature of the rail. The paper describes the mode of operation of the Rail Strain Monitoring System, the calibration procedure and the results from the field, and highlights the advantages of this system in comparison to other traditional monitoring systems. The safety improvement that can be achieved with the application of the Rail Strain Monitoring System is analysed. In particular, the reliability of the system is evaluated and compared to the human error probability in the traditional manual inspections. Finally, the reduction of derailment risk and related economic damages is estimated.


2021 ◽  
Vol 20 (3) ◽  
pp. 7-14
Author(s):  
Muhammad Ilias Rosli ◽  
Mohd Ridzuan Ahmad

The development of a cleanroom monitoring system needs more concentrated consideration consistently. There is a challenge to prove that the cleanroom operates following the specifications, in other words, users do not see the software error, they see failures in execution. This paper aims to design a smart monitoring system to monitor important parameters inside the cleanroom, i.e. temperature, humidity, and pressure to produce a good quality of work or experiment inside the cleanroom. The observing framework utilizes Arduino Mega as a microcontroller, ESP 8266 Wi-Fi module, DHT 11 as an integrated temperature and humidity sensor, HX710B as a pressure sensor, and Blynk application as a monitoring system to record and show information including provide fault notification. The project is tested on a modeled cleanroom to monitor important parameters via smartphone anytime and anywhere. From the experimental results, the Cleanroom IoT Monitoring System successfully read all parameters based on the system requirements and displays data of parameters in real-time and stored historical data. This system is also successful to provide failures notification of humidity, temperature, and pressure in real-time if any of the parameters are out of range from the system requirements. Lastly, users can monitor the condition of the cleanroom anytime and anywhere including receiving real-time failures notifications. This concept can avoid or reduce cleanroom working out of the criteria that can cause testing or experiment inside the cleanroom to be inaccurate. By observing and controlling the prerequisite development for IoT monitoring systems, great nature and better quality of performance of operational cleanrooms can be delivered.


2021 ◽  
Vol 11 (4) ◽  
pp. 1761
Author(s):  
Yoon-A Choi ◽  
Sejin Park ◽  
Jong-Arm Jun ◽  
Chee Meng Benjamin Ho ◽  
Cheol-Sig Pyo ◽  
...  

Stroke is the third highest cause of death worldwide after cancer and heart disease, and the number of stroke diseases due to aging is set to at least triple by 2030. As the top three causes of death worldwide are all related to chronic disease, the importance of healthcare is increasing even more. Models that can predict real-time health conditions and diseases using various healthcare services are attracting increasing attention. Most diagnosis and prediction methods of stroke for the elderly involve imaging techniques such as magnetic resonance imaging (MRI). It is difficult to rapidly and accurately diagnose and predict stroke diseases due to the long testing times and high costs associated with MRI. Thus, in this paper, we design and implement a health monitoring system that can predict the precursors of stroke diseases in the elderly in real time during daily walking. First, raw electroencephalography (EEG) data from six channels were preprocessed via Fast Fourier Transform (FFT). The raw EEG power values were then extracted from the raw spectra: alpha (α), beta (β), gamma (γ), delta (δ), and theta (θ) as well as the low β, high β, and θ to β ratio, respectively. The experiments in this paper confirm that the important features of EEG biometric signals alone during walking can accurately determine stroke precursors and occurrence in the elderly with more than 90% accuracy. Further, the Random Forest algorithm with quartiles and Z-score normalization validates the clinical significance and performance of the system proposed in this paper with a 92.51% stroke prediction accuracy. The proposed system can be implemented at a low cost, and it can be applied for early disease detection and prediction using the precursor symptoms of real-time stroke. Furthermore, it is expected that it will be able to detect other diseases such as cancer and heart disease in the future.


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