Software Datum Design for Cross-Axis Motion Measurement of X-Stage Based on Least Uncertainty Criterion

2011 ◽  
Vol 5 (2) ◽  
pp. 97-101 ◽  
Author(s):  
Eiki Okuyama ◽  
◽  
Hiroshi Takahashi ◽  
Hiromi Ishikawa ◽  
Keyword(s):  
Machine Tool ◽  
Random Error ◽  
Translational Motion ◽  
Inverse Filtering ◽  
Motion Measurement ◽  
Pitch Motion ◽  
Multiple Sensors ◽  
Multiple Sensor ◽  
Standard Deviations ◽  
Cross Axis

Cross-axis translational motion of a table on a machine tool is important in ultraprecision processes. Currently, conventional software datums that separate the cross-axismotion fromthe straightness profile of the straightedge by using multiple sensors and/or multiple arrangements are well-known. However, in large sampling numbers, the multiple sensor method tends to propagate random error. In this paper, a novel software datum for cross-axis motion measurement that can reduce the uncertainty due to the datum profile, pitch motion and random error is proposed. The proposed method consists of a weighted addition and inverse filtering. The suitable weight for the weighted addition yielding the least uncertainty is derived by an equation using standard deviations of the datum profile, pitch motion and random error of the sensors.

scholarly journals Bridge Carrying Robot Using ZigBee Carrying Multiple Sensor

2014 ◽  
Vol 41 ◽  
pp. 1-14
Author(s):  
M. Dheeraj Reddy
Keyword(s):  
Low Cost ◽  
Heavy Vehicles ◽  
Star Network ◽  
Light Detector ◽  
Multiple Sensors ◽  
The First World War ◽  
Zigbee Network ◽  
Gas Detector ◽  
Multiple Sensor ◽  
Fire Detector

MULTI-UTILITY VEHICLE is a vehicle which carries a folding bridge and multiple sensors. This vehicle is mainly used in war-field, it helps the soldiers to cross The un-even areas with the help of the bridge. It also helps other heavy vehicles to cross the disturbed path using its bridge. It is also equipped with multiple sensors like the fire detector, gas detector, light detector. This helps the soldiers to identify the different types of threats bearing poisonous gases, increase in temperature etc. from a longer distance. Those threats can be recognized by the soldiers with the help of buzzers equipped in the detector. As it is a remote vehicle which works on the wireless transmission of ZigBee, the light detector in the vehicle is used to automatically switch on the main lights when the visibility level starts decreasing due to sunlight. This project is already implemented in European countries during the First World War. It is an upcoming technology in our country. For solving the problem of the cooperation between multi-robots, a communication system based on the ZigBee network was designed. In the hardware of the robots, the ZigBee nodes are introduced. The multi-robots form a star network by the ZigBee nodes, and they keep communication with each other by the central node. The ZigBee network has many characteristics such as low cost, low power consume, strong anti-jamming ability and real-time performance etc, it adapts to the application of intelligence. Experiments showed that the communication between the robots is reliable. This scheme is a good way for robots to complete complex task and improve working efficiency.

scholarly journals Tire–Pavement Contact-Aware Weight Estimation for Multi-Sensor WIM Systems

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2027 ◽  
Author(s):  
Zhixin Jia ◽  
Kaiya Fu ◽  
Mengxiang Lin
Keyword(s):  
Neural Network ◽  
Estimation Error ◽  
Backpropagation Neural Network ◽  
Moving Vehicle ◽  
Multiple Sensors ◽  
Public Road ◽  
Weigh In Motion ◽  
Normal Speed ◽  
Gross Vehicle Weight ◽  
Multiple Sensor

Accurately estimating the weight of a moving vehicle at normal speed remains a challenging problem due to the complex vehicle dynamics and vehicle–pavement interaction. The weighing technique based on multiple sensors has proven to be an effective approach to this task. To improve the accuracy of weigh-in-motion (WIM) systems, this paper proposes a neural network-based method integrating identification and predication. A backpropagation neural network for signal classification (BPNN-i) was designed to identify ideal samples acquired by load sensors closest to the tire-pavement contact area. After that, ideal samples were used to predict the gross vehicle weight by using another backpropagation neural network (BPNN-e). The dataset for training and evaluation was collected from a multiple-sensor WIM (MS-WIM) system deployed in a public road. In our experiments, 96.89% of samples in the test set had an estimation error of less than 5%.

scholarly journals A single baroreceptor unit consists of multiple sensors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jun Liu ◽  
Nana Song ◽  
Yufang Wang ◽  
Jerome Walker ◽  
Jerry Yu
Keyword(s):  
Unit Activity ◽  
Myelinated Axon ◽  
Vital Role ◽  
Activity Level ◽  
Physiological Data ◽  
Multiple Sensors ◽  
Bolus Intravenous Injection ◽  
Multiple Sensor ◽  
Sensory Structures ◽  
High Level

AbstractArterial baroreceptors (BRs) play a vital role in the regulation of the cardiopulmonary system. What is known about how these sensors operate at the subcellular level is limited, however. Until recently, one afferent axon was considered to be connected to a single baroreceptor (one-sensor theory). However, in the lung, a single airway mechanosensory unit is now known to house many sensors (multiple-sensor theory). Here we tested the hypothesis that multiple-sensor theory also operates in BR units, using both morphological and electrophysiological approaches in rabbit aortic arch (in whole mount) labeled with Na+/K+-ATPase, as well as myelin basic protein antibodies, and examined microscopically. Sensory structures presented in compact clusters, similar to bunches of grapes. Sensory terminals, like those in the airways, formed leaf-like or knob-like expansions. That is, a single myelinated axon connected with multiple sensors forming a network. We also recorded single-unit activities from aortic baroreceptors in the depressor nerve in anesthetized rabbits and examined the unit response to a bolus intravenous injection of phenylephrine. Unit activity increased progressively as blood pressure (BP) increased. Five of eleven units abruptly changed their discharge pattern to a lower activity level after BP attained a plateau for a minute or two (when BP was maintained at the high level). These findings clearly show that the high discharge baroreceptor deactivates after over-excitation and unit activity falls to a low discharge sensor. In conclusion, our morphological and physiological data support the hypothesis that multiple-sensory theory can be applied to BR units.

Surgical Robot With Variable Remote Center of Motion Mechanism Using Flexible Structure

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Sho Yoshida ◽  
Takahiro Kanno ◽  
Kenji Kawashima
Keyword(s):  
Degrees Of Freedom ◽  
Translational Motion ◽  
Three Dimensional ◽  
Flexible Structure ◽  
Control Law ◽  
Surgical Robots ◽  
Pitch Motion ◽  
Bending Radius ◽  
Phantom Tissue ◽  
Pneumatic Cylinders

Remote center of motion (RCM) mechanisms are often used in surgical robots for laparoscopic surgery. In this paper, a RCM mechanism for holding a robotic forceps that facilitates adjustment using a flexible structure is proposed. The flexible structure is designed and manufactured with polypropylene-like resin material using a three-dimensional (3D) printer. Super elastic NI-Ti rods are inserted in the structure to have elasticity for bending and have rigidity for twisting. The structure achieves pitch motion around the remote center with two pneumatic cylinders. One cylinder drives the position and the other cylinder controls the bending radius of the structure. Therefore, the location of the remote center can be variable. This allows easier adjustment of the remote center before or during operation. The holder robot including the mechanism has four degrees-of-freedom (DOFs) in total, consisting of the pitch, a rotation around yaw axis, a translation in the direction of forceps insertion and a rotation of the forceps. Pneumatic rotary actuators are used for rotations and a cylinder is used for the translational motion. The model of the flexible structure is derived experimentally to design a controller for the pitch motion. A pneumatically driven robotic forceps is mounted on the holder to construct a master–slave control system. Experimental results show that the proposed control law achieves the desired rotational pitch motion. We compare the holder with a rigid link RCM holder and confirm the robustness of the proposed holder for variable remote center. Finally, the effectiveness of the system is confirmed with suturing tasks using a phantom tissue.

Generalized Two-Point Method Using Inverse Filtering for Surface Profile Measurement – Theoretical Analysis and Experimental Results for Error Propagation –

2014 ◽  
Vol 8 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Eiki Okuyama ◽  
◽  
Hiromi Ishikawa
Keyword(s):  
Theoretical Analysis ◽  
Error Propagation ◽  
Surface Profile ◽  
Sampling Interval ◽  
Experimental Results ◽  
Profile Measurement ◽  
Inverse Filtering ◽  
Multiple Sensors ◽  
The Difference ◽  
The Relationship

Error separation techniques of the surface profile from parasitic motions have been developed for the straightness profile measurement of a mechanical workpiece. These are known as software datums, which separate the surface profile from the parasitic motions by using multiple sensors and/or multiple orientations. The authors proposed a generalized twopoint method that used the difference with either integration or inverse filtering. This method can take any sampling interval. In this article, the relationship between the ratio of the sensor distance to the sampling interval and the error propagation at the lowest spatial frequency is clarified. Furthermore, experimental results are described to support the theoretical analysis of the error propagation.

scholarly journals Estimation of Translational Motion Parameters in Terahertz Interferometric Inverse Synthetic Aperture Radar (InISAR) Imaging Based on a Strong Scattering Centers Fusion Technique

2019 ◽  
Vol 11 (10) ◽  
pp. 1221 ◽  
Author(s):  
Ye Zhang ◽  
Qi Yang ◽  
Bin Deng ◽  
Yuliang Qin ◽  
Hongqiang Wang
Keyword(s):  
Synthetic Aperture Radar ◽  
Translational Motion ◽  
System Structure ◽  
Synthetic Aperture ◽  
Inverse Synthetic Aperture Radar ◽  
Motion Measurement ◽  
Scattering Centers ◽  
Motion Parameters ◽  
Strong Scattering ◽  
Aperture Radar

Translational motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate translational motion parameters of a maneuvering target. Compared to past InISAR image registration methods, the SSCF technique is advantageous in its high computing efficiency, excellent antinoise performance, high registration precision, and simple system structure. With a one-input three-output terahertz InISAR system, translational motion parameters in both the azimuth and height direction are precisely estimated. Firstly, the motion measurement curves are extracted from the spatial spectrums of mutually independent strong scattering centers, which avoids the unfavorable influences of noise and the “angle scintillation” phenomenon. Then, the translational motion parameters are obtained by fitting the motion measurement curves with phase unwrapping and intensity-weighted fusion processing. Finally, ISAR images are registered precisely by compensating the estimated translational motion parameters, and high-quality InISAR imaging results are achieved. Both simulation and experimental results are used to verify the validity of the proposed method.

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