A Comparison of Beat Frequency Estimation Methods for Large Ring Laser

Autoregressive (AR2) technique has always been used to estimate frequency of the output signal from Large ring laser. However, the acquisition rate is not at near real time which is the requirement and noise level still challenge the process resulting to errors in the final estimation. A research was done to compare the Autoregressive (AR2) with the counterparts such as Pisarenko, Quinn, Hilbert and Phase looking for a better technique that will estimate the frequency at near real time to minimize errors. Secondary data from G and C – II ring laser were used during the comparison between the techniques and Autoregressive (AR2). Results shows that, the output characteristics from the counterpart does not depict the oscillations of the Earth rotation as expected contrast to that of Autoregressive (AR2) which does. Moreover, there were much deviation from the expected true value for the techniques contrast to that of AR2 which is very minimum. On the other hand, when the C – II data were used, it was observed that both techniques resemble on their output characteristics though AR2 was still better in the acquisition rate expect for Hilbert transform which does not resemble with others. Following the scope of this paper, Autoregressive (AR2) technique still emerge as a favorite frequency estimation technique contrast to the four counterparts due to its robustness, high acquisition rate as well as low noise level.

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Performance Comparison of Two Real-Time Power System Frequency Estimation Methods

Advances in Power Systems and Energy Management - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-10-4394-9_42 ◽

2017 ◽

pp. 421-429

Author(s):

R. B. Sharma ◽

G. M. Dhole ◽

M. B. Tasare

Keyword(s):

Power System ◽

Real Time ◽

Frequency Estimation ◽

Performance Comparison ◽

Estimation Methods ◽

System Frequency

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Real-time measurement of optical fiber length with chaotic ring laser

Mechanical, Information and Industrial Engineering ◽

10.2495/icmiie140831 ◽

2015 ◽

Author(s):

Nian Fang ◽

Wei Ji ◽

Lutang Wang ◽

Zhaoming Huang

Keyword(s):

Optical Fiber ◽

Real Time ◽

Ring Laser ◽

Fiber Length ◽

Time Measurement ◽

Real Time Measurement

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PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v12i3.861 ◽

2013 ◽

Vol 12 (3) ◽

Author(s):

Rusmadi Suyuti

Keyword(s):

Information System ◽

Real Time ◽

Travel Demand ◽

Urban Traffic ◽

Road User ◽

Traffic Information ◽

Estimation Methods ◽

Traffic Counts ◽

Real Time Traffic ◽

Demand Models

Traffic information condition is a very useful information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.

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Real-Time Single Image Depth Perception in the Wild with Handheld Devices

Sensors ◽

10.3390/s21010015 ◽

2020 ◽

Vol 21 (1) ◽

pp. 15

Author(s):

Filippo Aleotti ◽

Giulio Zaccaroni ◽

Luca Bartolomei ◽

Matteo Poggi ◽

Fabio Tosi ◽

...

Keyword(s):

Real Time ◽

Depth Perception ◽

Depth Estimation ◽

Autonomous Driving ◽

Estimation Methods ◽

Handheld Devices ◽

Single Image ◽

Handheld Device ◽

Time Performance ◽

In The Wild

Depth perception is paramount for tackling real-world problems, ranging from autonomous driving to consumer applications. For the latter, depth estimation from a single image would represent the most versatile solution since a standard camera is available on almost any handheld device. Nonetheless, two main issues limit the practical deployment of monocular depth estimation methods on such devices: (i) the low reliability when deployed in the wild and (ii) the resources needed to achieve real-time performance, often not compatible with low-power embedded systems. Therefore, in this paper, we deeply investigate all these issues, showing how they are both addressable by adopting appropriate network design and training strategies. Moreover, we also outline how to map the resulting networks on handheld devices to achieve real-time performance. Our thorough evaluation highlights the ability of such fast networks to generalize well to new environments, a crucial feature required to tackle the extremely varied contexts faced in real applications. Indeed, to further support this evidence, we report experimental results concerning real-time, depth-aware augmented reality and image blurring with smartphones in the wild.

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Assessing local noise level estimation methods: Application to noise robust ASR

Speech Communication ◽

10.1016/s0167-6393(00)00051-0 ◽

2001 ◽

Vol 34 (1-2) ◽

pp. 141-158 ◽

Cited By ~ 40

Author(s):

Christophe Ris ◽

Stéphane Dupont

Keyword(s):

Noise Level ◽

Estimation Methods ◽

Noise Level Estimation ◽

Noise Robust

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LOW-NOISE SILICON-ON-INSULATOR HALL DEVICES

Fluctuation and Noise Letters ◽

10.1142/s021947750400194x ◽

2004 ◽

Vol 04 (02) ◽

pp. L345-L354 ◽

Cited By ~ 3

Author(s):

Y. HADDAB ◽

V. MOSSER ◽

M. LYSOWEC ◽

J. SUSKI ◽

L. DEMEUS ◽

...

Keyword(s):

Noise Level ◽

Low Voltage ◽

Silicon Layer ◽

Electrical Current ◽

Low Noise ◽

Silicon On Insulator ◽

Technological Parameters ◽

Wide Range ◽

Hall Sensors ◽

Soi Technology

Hall sensors are used in a very wide range of applications. A very demanding one is electrical current measurement for metering purposes. In addition to high precision and stability, a sufficiently low noise level is required. Cost reduction through sensor integration with low-voltage/low-power electronics is also desirable. The purpose of this work is to investigate the possible use of SOI (Silicon On Insulator) technology for this integration. We have fabricated SOI Hall devices exploring the useful range of silicon layer thickness and doping level. We show that noise is influenced by the presence of LOCOS and p-n depletion zones near the edges of the active zones of the devices. A proper choice of SOI technological parameters and process flow leads to up to 18 dB reduction in Hall sensor noise level. This result can be extended to many categories of devices fabricated using SOI technology.

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Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine

Applied Sciences ◽

10.3390/app11156701 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6701

Author(s):

Yuta Sueki ◽

Yoshiyuki Noda

Keyword(s):

Real Time ◽

Molten Metal ◽

Flow Rate ◽

Kalman Filters ◽

Estimation Method ◽

Estimation Methods ◽

Liquid Volume ◽

Model Parameters ◽

Rate Estimation ◽

Time Flow

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.

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Comparison of Noise Reduction Performance Evaluation Methods for Low-Noise Pavement in Korea- Part

INTER-NOISE and NOISE-CON Congress and Conference Proceedings ◽

10.3397/in-2021-2260 ◽

2021 ◽

Vol 263 (4) ◽

pp. 2930-2939

Author(s):

Byungchae Kim ◽

Hyunjin Kim ◽

Wonuk Kang

Keyword(s):

Noise Reduction ◽

Noise Level ◽

Measurement Method ◽

Road Traffic ◽

Low Noise ◽

Management Standards ◽

Close Proximity ◽

Porous Pavement ◽

Reduction Effect ◽

Measurement Location

In Korea, road noise is assessed as a measurement method of exterior noise emitted by road vehicle for management standards by the National Institute of Environmental Sciences. In this method, the noise felt at the actual pickup point is measured as LAeq (the roadside equivalent noise level). Recently, to clarify the standard for measuring noise on low-noise pavements, the CPX (ISO11819-2; Close-proximity method) was first introduced in the Porous Pavement Guidelines of the Ministry of Land, Infrastructure and Transport. According to ISO, the CPX adopts the side microphone as a mandatory measurement location, and the rear optional. The side location has been a mandatory due to its high correlation with SPB (ISO 11819-1, Statistical Pass-by method). However, according to our previous study on the correlation evaluation between L and CPX rear microphone noise level, both noise reduction effect was about 9-12 dB(A) showed a high correlation in Korea where heavy road traffic is common. The following study aims to show the consistent correlation between the L and CPX rear noise level. Furthermore, it is intended to be helpful in selecting the location of the CPX microphone that can most effectively represent the actual noise on the low-noise pavement in Korea.

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