Research of Multi-Sensor Integration System for Train Speed and Position Measurement

2011 ◽  
Vol 105-107 ◽  
pp. 1920-1925 ◽  
Author(s):  
Yu Wei Zhou
Keyword(s):  
Sensor Fusion ◽  
Simulation Experiment ◽  
Doppler Radar ◽  
Sensor Integration ◽  
Position Measurement ◽  
Integration System ◽  
Train Control ◽  
Federated Kalman Filter ◽  
Train Speed ◽  
Single Sensor

The speed and position measurement is an important part of the train control system. Accurate measurement of train speed and position ensures safety of train running and improves transportation efficiency. Traditional methods to measure speed and position usually rely on single sensor, which has less accuracy and reliability. A method of measuring train speed and position based on multi-sensor fusion is proposed in this paper. Since trains are running on fixed rail tracks, the position of train can be determined by the traveled distance and speed monitoring is essentially to measure the magnitude of train velocity. According to this characteristic, this measurement system consists of axle odometer, Doppler radar, accelerometer and intermittent inquiry balise. The federated Kalman filter is used to implement multi-sensor fusion. Simulation experiment results prove that this method can improve the accuracy and reliability of train speed and position measurement.

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals A Robust Cooperative Modulation Classification Scheme with Intra sensor Fusion for the Time correlated Flat Fading Channels

2020 ◽  
Vol 70 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Goran Marković ◽  
Vlada Sokolović
Keyword(s):  
Fading Channels ◽  
Sensor Fusion ◽  
Large Scale ◽  
Negative Influence ◽  
Modulation Classification ◽  
Distributed Sensors ◽  
Performance Improvements ◽  
Flat Fading ◽  
Significant Performance ◽  
Single Sensor

Networks with distributed sensors, e.g. cognitive radio networks or wireless sensor networks enable large-scale deployments of cooperative automatic modulation classification (AMC). Existing cooperative AMC schemes with centralised fusion offer considerable performance increase in comparison to single sensor reception. Previous studies were generally focused on AMC scenarios in which multipath channel is assumed to be static during a signal reception. However, in practical mobile environments, time-correlated multipath channels occur, which induce large negative influence on the existing cooperative AMC solutions. In this paper, we propose two novel cooperative AMC schemes with the additional intra-sensor fusion, and show that these offer significant performance improvements over the existing ones under given conditions.

Sensor Fusion of Odometer, Compass and Beacon Distance for Mobile Robots

2020 ◽  
Vol 10 (1) ◽  
pp. 1-17
Author(s):  
Rufus Fraanje ◽  
René Beltman ◽  
Fidelis Theinert ◽  
Michiel van Osch ◽  
Teade Punter ◽  
...  
Keyword(s):  
State Estimation ◽  
Sensor Fusion ◽  
Simulation Experiment ◽  
Estimation Problem ◽  
Unknown Input ◽  
Fusion Algorithm ◽  
Process Noise ◽  
Distance Measurements ◽  
Differential Drive ◽  
Filter Solution

The estimation of the pose of a differential drive mobile robot from noisy odometer, compass, and beacon distance measurements is studied. The estimation problem, which is a state estimation problem with unknown input, is reformulated into a state estimation problem with known input and a process noise term. A heuristic sensor fusion algorithm solving this state-estimation problem is proposed and compared with the extended Kalman filter solution and the Particle Filter solution in a simulation experiment.

Sensor Integration and Data Fusion Theory

2010 ◽  
pp. 160-188
Author(s):  
Zude Zhou ◽  
Huaiqing Wang ◽  
Ping Lou
Keyword(s):  
Data Fusion ◽  
Error Compensation ◽  
Intelligent Manufacturing ◽  
Sensor Integration ◽  
Sensor Data ◽  
Sensor Technology ◽  
Fusion Technology ◽  
Knowledge Based ◽  
Manufacturing Intelligence ◽  
Single Sensor

In previous chapters, the engineering scientific foundations of manufacturing intelligence (such as the knowledge-based system, Multi-Agent system, data mining and knowledge discovery, and computing intelligence) have been discussed in detail. Sensor integration and data fusion is another important theory of manufacturing intelligence. With the development of integrated systems, there is an urgent requirement for improving system automaticity and intelligence. Without improvement, the complexity and scale of systems are increased. Such systems need to be more sensitive to their work environment and independent state, and obviously, single sensor technology hardly meets these requirements. Multi-sensor and data fusion technology are therefore employed in automatic and intelligent manufacturing as it is more comprehensive and accurate than traditional single sensor technology if the information redundancy and complementarity are used reasonably. In theory, the outputs of multi-sensors are mutually validated. Multi-sensor integration is a brand new concept for intelligent manufacturing, and without doubt, sensor integration-based intelligent manufacturing is the development orientation of manufacturing in the future. With reference to the information fusion problem of the multi-sensor integration system, the development state, technical background, application scope and basic meaning of the multi-sensor integration and the data fusion are first reviewed in this chapter. Secondly the classification, level, system structure and function model of the data fusion system is discussed. The theoretical method of the data fusion is then introduced, and finally, attention is paid to cutting tool condition detection, machine thermal error compensation and online detection and error compensation because those are the main applications of multi-sensor data fusion technology in intelligent manufacturing.

Micro Doppler Radar and Depth Sensor Fusion for Human Activity Monitoring in AAL

2019 ◽  
pp. 519-528
Author(s):  
Susanna Spinsante ◽  
Matteo Pepa ◽  
Stefano Pirani ◽  
Ennio Gambi ◽  
Francesco Fioranelli
Keyword(s):  
Sensor Fusion ◽  
Human Activity ◽  
Doppler Radar ◽  
Activity Monitoring ◽  
Depth Sensor

scholarly journals Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Mohammad Jalil Piran ◽  
Amjad Ali ◽  
Doug Young Suh
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Sensor Fusion ◽  
Ad Hoc ◽  
Fuzzy Theory ◽  
Wireless Sensor ◽  
Mobile Nodes ◽  
Level Information ◽  
Single Sensor ◽  
High Level

In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unified interpretation. The best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and definitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET). In the proposed technique, we considered four input sensor readings (antecedents) and one output (consequent). The employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, The Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash_Severity is considered as the consequent variable. The processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes.

Sensor Fusion Strategy in the Monitoring of Cutting Tool Wear

2006 ◽  
Vol 306-308 ◽  
pp. 727-732 ◽  
Author(s):  
Muslim Mahardika ◽  
Zahari Taha ◽  
Djoko Suharto ◽  
Kimiyuki Mitsui ◽  
Hideki Aoyama
Keyword(s):  
Tool Wear ◽  
Sensor Fusion ◽  
Cutting Tool ◽  
Fusion Technology ◽  
Machining Processes ◽  
Fusion Strategy ◽  
Cutting Tool Wear ◽  
Single Sensor ◽  
Paper Sensor

Cutting tool wear is a major problem in machining processes. It has a great effect on the quality of a workpiece. Thus, monitoring cutting tool wear is very important in order to maintain the workpiece quality as well to reduce production rate and production time. The use of a single sensor in a monitoring system may not be accurate to detect cutting tool wear. In this paper, sensor fusion technology is introduced for monitoring cutting tool wear.

scholarly journals ViSIAr – A virtual sensor integration architecture

Robotica ◽  
1999 ◽  
Vol 17 (6) ◽  
pp. 635-647 ◽  
Author(s):  
Nigel Hardy ◽  
Aftab Ahmad Maroof
Keyword(s):  
Software Engineering ◽  
Sensor Integration ◽  
Virtual Sensor ◽  
Integration System ◽  
Virtual Sensors ◽  
Integration Architecture ◽  
Design Requirements ◽  
Support Programming ◽  
Important Design

Virtual sensors (software abstractions to support programming of sensor use) have been shown to have software-engineering benefits. A sensor integration system is required to support them. We examine the general requirements of such systems and consider the important design requirements. An idealised architecture, ViSIAr, is proposed to serve as a framework for designing and constructing them. Illustrative examples are provided.

Sign in / Sign up

Export Citation Format

Share Document