The Design of Real-Time Power Detection System in Communication Equipment

2012 ◽  
Vol 605-607 ◽  
pp. 1063-1067
Author(s):  
Xian Jun Yi ◽  
Jun Xia Jiang ◽  
De Wen Guo ◽  
Di Feng Zhang
Keyword(s):  
Real Time ◽  
Software Design ◽  
Communication Systems ◽  
Detection System ◽  
High Reliability ◽  
Complex Environment ◽  
Wide Range ◽  
Core Components ◽  
Wide Scale ◽  
Communication Equipment

Communications equipments' voltage, current fluctuations and power changes will bring uncertain hazards in communication systems, monitoring each functional unit's power is necessary. However, communication equipment's power supply has characteristics such as high transient and wide-scale fluctuations, which increases the difficulty of monitoring the power output. This paper introduces a design of an accurate real-time detection of each functional unit's power in communications equipment. The design uses dedicated power detection chip LTC4151 as the core components of the power collection, the LTC4151 which has wide range and high DC voltage input can measure output power, determine and make alarm processing under the management of the micro-controller. The hardware and software design of system are described in detail. The design has high reliability which solved the problem of monitoring communication equipment's power under the complex environment with simple circuit.

Application of CAN Bus in Modern Automobile Network System

2013 ◽  
Vol 655-657 ◽  
pp. 1141-1144
Author(s):  
Yi Wang ◽  
Li Ren He
Keyword(s):  
Real Time ◽  
Software Design ◽  
Network Architecture ◽  
High Performance ◽  
Can Bus ◽  
High Reliability ◽  
Network System ◽  
Interface Circuit ◽  
Automotive Electronic ◽  
Internal Network

As a field bus, CAN bus has been increasingly used in automotive electronic system.In this paper,a vehicle internal network architecture based on CAN bus system was introduced. Utilized the high-performance PIC18F258 MCU with CAN controller to design a CAN bus interface circuit, meanwhile shown the structure of major hardware and software design processes. The circuit has several advantages such as simple hardware design, high reliability,and powerful real-time.

scholarly journals Development of a high-throughput real-time PCR system for detection of enzootic pathogens in pigs

2019 ◽  
Vol 32 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Nicole B. Goecke ◽  
Charlotte K. Hjulsager ◽  
Jesper S. Krog ◽  
Kerstin Skovgaard ◽  
Lars E. Larsen
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Real Time Pcr ◽  
Pathogen Detection ◽  
Detection System ◽  
Working Hours ◽  
Negative Influence ◽  
Optimal Choice ◽  
National Veterinary Institute ◽  
Wide Range

Respiratory and intestinal diseases in pigs can have significant negative influence on productivity and animal welfare. A wide range of real-time PCR (rtPCR) assays are used in our laboratory (National Veterinary Institute, Technical University of Denmark) for pathogen detection, and PCR analyses are performed on traditional rtPCR platforms in which a limited number of samples can be analyzed per day given limitations in equipment and personnel. To mitigate these restrictions, rtPCR assays have been optimized for the high-throughput rtPCR BioMark platform (Fluidigm). Using this platform, we developed a high-throughput detection system that can be used for simultaneous examination of 48 samples with detection specificity for 18 selected respiratory and enteric viral and bacterial pathogens of high importance to Danish pig production. The rtPCR assays were validated and optimized to run under the same reaction conditions using a BioMark 48.48 dynamic array (DA) integrated fluidic circuit chip, and the sensitivity and specificity were assessed by testing known positive samples. Performance of the 48.48DA was similar to traditional rtPCR analysis, and the specificity of the 48.48DA was high. Application of the high-throughput platform has resulted in a significant reduction in cost and working hours and has provided production herds with a new innovative service with the potential to facilitate the optimal choice of disease control strategies such as vaccination and treatment.

The Application of CAN Bus Microcontroller MC9S08DZ60 in Automotive Electronic Control Unit

2013 ◽  
Vol 694-697 ◽  
pp. 2608-2611 ◽  
Author(s):  
Yi Wang ◽  
Li Ren He
Keyword(s):  
Real Time ◽  
Software Design ◽  
Can Bus ◽  
High Reliability ◽  
Electronic Control Unit ◽  
Low Cost ◽  
Control Unit ◽  
Scientific Basis ◽  
Electronic Control ◽  
Automotive Electronic

Take the microcontroller MC9S08DZ60 which integrated CAN controller for example, the design of automotive electronic control unit was introduced, meanwhile shown the hardware structure and software design processes. This circuit has characteristics of simple hardware, low cost, high reliability, real-time. It has provided a scientific basis for the development of the CAN communication electronic control unit based on MC9S08DZ60 microprocessor.

Pipeline Rupture Detection Using Real-Time Transient Modelling and Convolutional Neural Networks

2018 ◽  
Author(s):  
Joel Smith ◽  
Jaehee Chae ◽  
Shawn Learn ◽  
Ron Hugo ◽  
Simon Park
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Detection System ◽  
High Reliability ◽  
Leak Detection ◽  
Sudden Onset ◽  
False Alarms ◽  
Pipeline System ◽  
Transient Model ◽  
Social License

Demonstrating the ability to reliably detect pipeline ruptures is critical for pipeline operators as they seek to maintain the social license necessary to construct and upgrade their pipeline systems. Current leak detection systems range from very simple mass balances to highly complex models with real-time simulation and advanced statistical processing with the goal of detecting small leaks around 1% of the nominal flow rate. No matter how finely-tuned these systems are, however, they are invariably affected by noise and uncertainties in a pipeline system, resulting in false alarms that reduce system confidence. This study aims to develop a leak detection system that can detect leaks with high reliability by focusing on sudden-onset leaks of various sizes (ruptures), as opposed to slow leaks that develop over time. The expected outcome is that not only will pipeline operators avoid the costs associated with false-alarm shut downs, but more importantly, they will be able to respond faster and more confidently in the event of an actual rupture. To accomplish these goals, leaks of various sizes are simulated using a real-time transient model based on the method of characteristics. A novel leak detection model is presented that fuses together several different preprocessing techniques, including convolution neural networks. This leak detection system is expected to increase operator confidence in leak alarms, when they occur, and therefore decrease the amount of time between leak detection and pipeline shutdown.

scholarly journals Audio-Based Aircraft Detection System for Safe RPAS BVLOS Operations

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2076
Author(s):  
Jorge Mariscal-Harana ◽  
Víctor Alarcón ◽  
Fidel González ◽  
Juan José Calvente ◽  
Francisco Javier Pérez-Grau ◽  
...  
Keyword(s):  
Real Time ◽  
Data Augmentation ◽  
Detection System ◽  
Cost Effective ◽  
True Positive Rate ◽  
Training Dataset ◽  
Computational Performance ◽  
Combining Data ◽  
Wide Range ◽  
Aircraft Detection

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective ‘Detect and Avoid’ systems that enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based ‘Detect and Avoid’ system, composed of microphones and an embedded computer, which performs real-time inferences using a sound event detection (SED) deep learning model. Two state-of-the-art SED models, YAMNet and VGGish, are fine-tuned using our dataset of aircraft sounds and their performances are compared for a wide range of configurations. YAMNet, whose MobileNet architecture is designed for embedded applications, outperformed VGGish both in terms of aircraft detection and computational performance. YAMNet’s optimal configuration, with >70% true positive rate and precision, results from combining data augmentation and undersampling with the highest available inference frequency (i.e., 10 Hz). While our proposed ‘Detect and Avoid’ system already allows the detection of small aircraft from sound in real time, additional testing using multiple aircraft types is required. Finally, a larger training dataset, sensor fusion, or remote computations on cloud-based services could further improve system performance.

scholarly journals Audio-Based Aircraft Detection System for Safe RPAS BVLOS Operations

2020 ◽  
Author(s):  
Jorge Mariscal-Harana ◽  
Víctor Alarcón ◽  
Fidel González ◽  
Juan José Calvente ◽  
Francisco Javier Pérez-Grau ◽  
...  
Keyword(s):  
Real Time ◽  
Data Augmentation ◽  
Detection System ◽  
Cost Effective ◽  
True Positive Rate ◽  
Training Dataset ◽  
Computational Performance ◽  
Combining Data ◽  
Wide Range ◽  
Aircraft Detection

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective "Detect and Avoid" systems that enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based "Detect and Avoid" system, composed of microphones and an embedded computer, which performs real-time inferences using a sound event detection (SED) deep learning model. Two state-of-the-art SED models, YAMNet and VGGish, are fine-tuned using our dataset of aircraft sounds and their performances are compared for a wide range of configurations. YAMNet, whose MobileNet architecture is designed for embedded applications, outperformed VGGish both in terms of aircraft detection and computational performance. YAMNet's optimal configuration, with > 70% true positive rate and precision, results from combining data augmentation and undersampling with the highest available inference frequency (i.e. 10 Hz). While our proposed "Detect and Avoid" system already allows the detection of small aircraft from sound in real time, additional testing using multiple aircraft types is required. Finally, a larger training dataset, sensor fusion, or remote computations on cloud-based services could further improve system performance.

scholarly journals Performance analysis of security framework for software defined network architectures

2019 ◽  
Vol 8 (3) ◽  
pp. 232
Author(s):  
K. A. Varun Kumar ◽  
D. Arivudainambi
Keyword(s):  
Real Time ◽  
Bandwidth Allocation ◽  
Data Centers ◽  
Service Providers ◽  
Detection System ◽  
Network Function Virtualization ◽  
Cloud Infrastructure ◽  
Security Framework ◽  
Time Data ◽  
Wide Range

<p>Software defined data centers (SDDC) and software defined networking (SDN) are two emerging areas in the field of cloud data centers. SDN based centrally controlled services takes a global view of the entire cloud infrastructure between SDDC and SDN, whereas Network Function Virtualization (NFV) is widely used for providing virtual networking between host and Internet Service Providers (ISP’s). Some Application as a Service used in NFV data centers have a wide range in building security services like Virtual firewalls, Intrusion Detection System (IDS), load balancing, bandwidth allocation and management. In this paper, a novel security framework is proposed to combat SDDC and SDN based on NFV security features. The proposed framework consists of a Virtual firewall and an efficient bandwidth manager to handle multiple heterogeneous application requests from different ISPs. Real time data were taken from an experiment for a week and A new simulation based proof of concept is admitted in this paper for validation of the proposed framework which was deployed in real time SDNs using Mininet and POX controller.</p>

scholarly journals Image Processing Based Intelligent Traffic Controller

2012 ◽  
pp. 13-17
Author(s):  
Vikramaditya Dangi ◽  
Amol Parab ◽  
Kshitij Pawar ◽  
S.S Rathod
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Management ◽  
Detection System ◽  
Emergency Vehicle ◽  
Pollution Levels ◽  
Real Time Image ◽  
Wide Scale ◽  
Traffic Management System ◽  
Time Image

The frequent traffic jams at major junctions call for an efficient traffic management system in place. The resulting wastage of time and increase in pollution levels can be eliminated on a city-wide scale by these systems. The paper proposes to implement an intelligent traffic controller using real time image processing. The image sequences from a camera are analyzed using various edge detection and object counting methods to obtain the most efficient technique. Subsequently, the number of vehicles at the intersection is evaluated and traffic is efficiently managed. The paper also proposes to implement a real-time emergency vehicle detection system. In case an emergency vehicle is detected, the lane is given priority over all the others.

scholarly journals Audio-Based Aircraft Detection System for Safe RPAS BVLOS Operations

2020 ◽  
Author(s):  
Jorge Mariscal-Harana ◽  
Víctor Alarcón ◽  
Fidel González ◽  
Juan José Calvente ◽  
Francisco Javier Pérez-Grau ◽  
...  
Keyword(s):  
Real Time ◽  
Data Augmentation ◽  
Detection System ◽  
Cost Effective ◽  
True Positive Rate ◽  
Computational Performance ◽  
Combining Data ◽  
Wide Range ◽  
Positive Rate ◽  
Aircraft Detection

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective &quot;Detect and Avoid&quot; systems which enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based &quot;Detect and Avoid&quot; system, composed of microphones and an embedded computer, which performs real-time inferences using a sound event detection (SED) deep learning model. Two state-of-the-art SED models, YAMNet and VGGish, are fine-tuned using our aircraft sounds dataset and their performances are compared for a wide range of configurations. YAMNet, whose MobileNet architecture is designed for embedded applications, outperformed VGGish both in terms of aircraft detection and computational performance. YAMNet's optimal configuration, with &gt; 70% true positive rate and precision, results from combining data augmentation and undersampling with the highest available inference frequency (i.e. 10 Hz). While our proposed &quot;Detect and Avoid&quot; system already allows the detection of small aircraft from sound in real time, a larger dataset, sensor fusion, or the use of cloud-based services for remote computations could further improve its performance.

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