A low-cost GPS/INS Integrated System for an Auto Guided Tractor

2015 ◽  
Keyword(s):  
Low Cost ◽  
Integrated System

A Critical Review of the Biological Processes in the Chemical Absorption-biological Reduction Integrated System for NO Removal

2021 ◽  
Vol 07 ◽  
Author(s):  
Wei Li
Keyword(s):  
Catalytic Reduction ◽  
Low Cost ◽  
Reduction Process ◽  
Integrated System ◽  
Future Research ◽  
Small Scale ◽  
Biological Processes ◽  
Chemical Absorption ◽  
Biological Reduction ◽  
Biological Reaction

: Exploring low-cost, green and safe technologies to provide an alternative to the conventional selective catalytic reduction process is key to the control of NOx emitted from small-scale boilers and other industrial processes. To meet the demand, the chemical absorption-biological reduction integrated system has been developing recently. chemical absorption-biological reduction integrated system applies Fe(II)EDTA for NO absorption and iron-reducing and denitrifying bacteria for absorbent regeneration. Many studies have focused on the enhancements of mass transfer and biological reaction, among which the biological processes were the rate-limiting steps. This review summarizes the current researches on the biological processes in the CABR system, which focuses on the mechanism and enhancement of biochemical reactions, and provides the possible directions of future research.

Non-invasive intelligent monitoring system for fault detection in induction motor based on bio piezoelectric sensor using ANN

2022 ◽  
Author(s):  
Massine GANA ◽  
Hakim ACHOUR ◽  
Kamel BELAID ◽  
Zakia CHELLI ◽  
Mourad LAGHROUCHE ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Motor ◽  
Vibration Analysis ◽  
Low Cost ◽  
Piezoelectric Sensor ◽  
Integrated System ◽  
Easy Access ◽  
Non Invasive ◽  
Artificial Neural

Abstract This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements have been collected then monitored in real time and transmitted via an ESP32 board. A new bio-flexible piezoelectric sensor developed previously in our laboratory, was used for vibration analysis. Moreover an infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network algorithm implemented on the microcontroller. Besides, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of vibration analysis, thermal signature analysis and artificial neural network provides a better diagnosis. It ensures efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

scholarly journals Testing of the Possibilities of Using IMUs with Different Types of Movements

2014 ◽  
Vol 12 ◽  
pp. 61-66 ◽  
Author(s):  
Pavol Kajánek
Keyword(s):  
Inertial Navigation System ◽  
Low Cost ◽  
Indoor Navigation ◽  
Integrated System ◽  
Test Results ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Improve Accuracy ◽  
Different Types ◽  
Measurement Units

Inertial navigation system (INS) is a self-contained navigation technique. Its main purpose is to determinate the position and the trajectory of the object´s movement in space. This technique is well represented not only as a supplementary method (GPS/INS integrated system) but as an autonomous system for navigation of vehicles and pedestrians, also. The aim of this paper is to design a test for low-cost inertial measurement units. The test results give us information about accuracy, which determine the possible use in indoor navigation or other applications. There are described some methods for processing the data obtained by inertial measurement units, which remove noise and improve accuracy of position and orientation.

scholarly journals The Dark Side of Microalgae Biotechnology: A Heterotrophic Biorefinery Platform Directed to ω-3 Rich Lipid Production

2019 ◽  
Vol 7 (12) ◽  
pp. 670 ◽  
Author(s):  
Teresa Lopes da Silva ◽  
Patrícia Moniz ◽  
Carla Silva ◽  
Alberto Reis
Keyword(s):  
Low Cost ◽  
Lipid Production ◽  
Arable Land ◽  
Integrated System ◽  
Dark Side ◽  
Omega 3 ◽  
Niche Markets ◽  
Microalgal Biomass ◽  
Oleaginous Microalgae ◽  
Heterotrophic Microalgae

Microbial oils have been considered a renewable feedstock for bioenergy not competing with food crops for arable land, freshwater and biodiverse natural landscapes. Microalgal oils may also have other purposes (niche markets) besides biofuels production such as pharmaceutical, nutraceutical, cosmetic and food industries. The polyunsaturated fatty acids (PUFAs) obtained from oleaginous microalgae show benefits over other PUFAs sources such as fish oils, being odorless, and non-dependent on fish stocks. Heterotrophic microalgae can use low-cost substrates such as organic wastes/residues containing carbon, simultaneously producing PUFAs together with other lipids that can be further converted into bioenergy, for combined heat and power (CHP), or liquid biofuels, to be integrated in the transportation system. This review analyses the different strategies that have been recently used to cultivate and further process heterotrophic microalgae for lipids, with emphasis on omega-3 rich compounds. It also highlights the importance of studying an integrated process approach based on the use of low-cost substrates associated to the microalgal biomass biorefinery, identifying the best sustainability methodology to be applied to the whole integrated system.

scholarly journals Robust INS/SFPPP-BDS tightly coupled navigation algorithm with adaptive cycle slip compensation model

2019 ◽  
Vol 13 ◽  
pp. 174830181983304
Author(s):  
Hangshuai Ma ◽  
Rong Wang ◽  
Zhi Xiong ◽  
Jianye Liu ◽  
Chuanyi Li
Keyword(s):  
Navigation System ◽  
Carrier Phase ◽  
Low Cost ◽  
Integrated System ◽  
Single Frequency ◽  
Cycle Slip ◽  
Phase Measurements ◽  
Satellite Navigation System ◽  
Tightly Coupled ◽  
Robust Adaptive

The application of Beidou Satellite Navigation System (BDS) is developing rapidly. To satisfy the increasing demand for positioning performance, single-frequency precise point positioning (SFPPP) has been a focus in recent years. By introducing the SFPPP technique into the INS/BDS integrated system, higher navigation accuracy can be obtained. Cycle slip, which is caused by signal blockage during the measurement of the carrier phase, is a challenge for SFPPP application. In the INS/SFPPP-BDS integrated system, cycle slip can cause serious bias in BDS carrier phase measurements. In this paper, a new INS/SFBDS-PPP tightly coupled navigation system and a robust adaptive filtering method are proposed. Using a low-cost single-frequency receiver integrated with INS, an observation model was built based on the pseudo range and carrier phase by PPP preprocessing. The cycle slip was introduced into the state vector to improve the estimation precision. The test statistics, comprising the innovation and its covariance, were used to estimate the time at which cycle slip occurred and its amplitude to compensate for its effect on the observation. Finally, the proposed system model and algorithm are validated by simulation.

Directly Georeferenced Ground Feature Points with UAV Borne Photogrammetric Platform without Ground Control

2013 ◽  
Vol 284-287 ◽  
pp. 1523-1527
Author(s):  
Meng Lun Tsai ◽  
Kai Wei Chiang ◽  
Cheng Fang Lo ◽  
Jiann Yeou Rau
Keyword(s):  
Real Time ◽  
Spatial Information ◽  
Disaster Relief ◽  
Low Cost ◽  
Control Point ◽  
Integrated System ◽  
Single Frequency ◽  
Ground Control ◽  
Differential Gps ◽  
Positioning Accuracy

In order to facilitate applications such as environment detection or disaster monitoring, developing a quickly and low cost system to collect near real time spatial information is very important. Such a rapid spatial information collection capability has become an emerging trend in the technology of remote sensing and mapping application. In this study, a fixed-wing UAV based spatial information acquisition platform is developed and evaluated. The proposed UAV based platform has a direct georeferencing module including an low cost INS/GPS integrated system, low cost digital camera as well as other general UAV modules including immediately video monitoring communication system. This direct georeferencing module is able to provide differential GPS processing with single frequency carrier phase measurements to obtain sufficient positioning accuracy. All those necessary calibration procedures including interior orientation parameters, the lever arm and boresight angle are implemented. In addition, a flight test is performed to verify the positioning accuracy in direct georeferencing mode without using any ground control point that is required for most of current UAV based photogrammetric platforms. In other word, this is one of the pilot studies concerning direct georeferenced based UAV photogrammetric platform. The preliminary results in term of positioning accuracy in direct georeferenced mode without using any GCP illustrate horizontal positioning accuracies in x and y axes are both less than 20 meters, respectively. On the contrary, the positioning accuracy of z axis is less than 50 meters with 600 meters flight height above ground. Such accuracy is good for near real time disaster relief. Therefore, it is a relatively safe and cheap platform to collect critical spatial information for urgent response such as disaster relief and assessment applications where ground control points are not available.

GPS-INS Integration Algorithm for Autonomous Vehicle Using Loosely Coupled Integration Architecture

2013 ◽  
Vol 390 ◽  
pp. 506-511
Author(s):  
Rashid Iqbal ◽  
Zhong Jian Li ◽  
Khan Badshah
Keyword(s):  
Autonomous Vehicles ◽  
Low Cost ◽  
Autonomous Vehicle ◽  
Integrated System ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Initial Alignment ◽  
Integration Algorithm ◽  
Loosely Coupled ◽  
Integration Architecture

Inertial measurement unit (IMU) has been widely used for autonomous vehicles navigation. The accuracy of IMU specifies the performance of the inertial navigation system (INS).The errors in the INS are mainly due to the IMU inaccuracies, initial alignment, computational errors and approximations in the system equations. These errors are further integrated over time due to the dead-reckoning nature of the INS, which leads to unacceptable results. These errors need an accurate estimation for high precision navigation. INS is integrated with Global Positioning System (GPS) to estimate the errors and enhance the navigation capability of the INS. Linearized Kalman Filter (LKF) is proposed for estimating the errors in the low cost INS using Loosely Coupled integration approach, which is opted for its simplicity and robustness. Prediction part of the LKF is used during the GPS lag for errors estimation, which is found very effective for low cost sensors. The resulting GPS-INS integration algorithm is evaluated on simulated Autonomous vehicle trajectory, generated from 6-DOF model. The integrated system limits the attitude errors less than 0.1 deg and velocity errors of the order of 0.003 meter per second. Furthermore, it provides an optimal navigation solution than can be achieved from individual systems.

MEMS IMU and GPS/Beidou Integration Navigation System Using Interval Kalman Filter

2014 ◽  
Vol 568-570 ◽  
pp. 970-975 ◽  
Author(s):  
Yang Le ◽  
Xiu Feng He ◽  
Ru Ya Xiao
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Low Cost ◽  
Integrated System ◽  
Integrated Navigation ◽  
Dynamics Modeling ◽  
Integrated Navigation System ◽  
Uncertain Dynamics ◽  
Integration Navigation ◽  
Mems Imu

This paper describes an integrated MEMS IMU and GNSS system for vehicles. The GNSS system is developed to accurately estimate the vehicle azimuth, and the integrated GNSS/IMU provides attitude, position and velocity. This research is aimed at producing a low-cost integrated navigation system for vehicles. Thus, an inexpensive solid-state MEMS IMU is used to smooth the noise and to provide a high bandwidth response. The integration system with uncertain dynamics modeling and uncertain measurement noise is also studied. An interval adaptive Kalman filter is developed for such an uncertain integrated system, since the standard extended Kalman filter (SKF) is no longer applicable, and a method of adaptive factor construction with uncertain parameter is proposed for the nonlinear integrated GNSS/IMU system. The results from the actual GNSS/IMU integrated system indicate that the filtering method proposed is effective.

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