<i>Signal Processing for Intelligent Sensor Systems</i>

Swanson, David C.; Havelock, David I.

doi:10.1121/1.1365422

Cited by 25 publications

(39 citation statements)

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“…This happens when either a conductor moves in a constant magnetic field or there is a changing magnetic field near a conductor. There are many physical ways in which electromagnetic noise can be reduced, including using shielded wires, twisting the wires into pairs, or placing the circuit in a Faraday cage [64]. Electromagnetic interference can also be filtered out of the circuit, as long as the frequency of the interference is not the same as the signal of interest.…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

“…Contact noise occurs across joints in electrical circuits, like solder joints. The magnitude of the noise is proportional to the DC current across any contact [64].…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

“…Thermal/Johnson noise comes from a resister and can be minimized by using smaller resistances in a signal conditioning circuit [9,31,64]. Shot noise is typically much smaller than Johnson noise.…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

“…It originates from small variations in electric current across vacuum tubes and transistors. Shot noise is minimized by minimizing the number of these voltage potential barriers [64].…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

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Investigation into use of piezoelectric sensors in a wheeled robot tire for surface characterization

Armstrong

Sandu

Taheri

2015

Journal of Terramechanics

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A differential steered, 13.6 kg robot was developed as an intelligent tire testing system and was used to investigate the potential of using piezoelectric film sensors in small tube-type pneumatic tires to characterize tire-ground interaction.One focus of recent research in the tire industry has been on instrumenting tires with sensors to monitor the tire, vehicle, or external environment. On small robots, tire sensors that measure the forces and deflections in the contact patch could be used to improve energy efficiency and/or mobility during a mission.The robot was assembled from a SuperDroid Robots kit and instrumented with low-cost piezoelectric film sensors from Measurement Specialties between the inner tube and the tire. An unlaminated and a laminated sensor were placed circumferentially along the tread and an unlaminated sensor was placed along the sidewall. A slip ring transferred the signals from the tire to the robot. There, the signal conditioning circuit extended the time constant of the sensors and filtered electromagnetic interference. The robot was tested with a controlled power sequence carried out on polished cement, ice, and sand at three power levels, two payload levels, and with two tire sizes.The results suggest that the sensors were capable of detecting normal pressure, deflection, and/or longitudinal strain. Added payload increased the amplitude of the signals for all sensors. On the smaller tires, sensors generally recorded a smaller, wider signal on sand compared to cement, indicating the potential to detect contact patch pressure and length. The signals recorded by the unlaminated sensor along the tread of the smaller tire were lower on ice compared to cement, indicating possible sensitivity to tractive force. Results were less consistent for the larger tires, possibly due to the large tread pattern.

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Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

“…Contact noise occurs across joints in electrical circuits, like solder joints. The magnitude of the noise is proportional to the DC current across any contact [64].…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

“…It originates from small variations in electric current across vacuum tubes and transistors. Shot noise is minimized by minimizing the number of these voltage potential barriers [64].…”

Section: Types Of Electromagnetic Interferencementioning

confidence: 99%

See 2 more Smart Citations

Investigation into use of piezoelectric sensors in a wheeled robot tire for surface characterization

Armstrong

Sandu

Taheri

2015

Journal of Terramechanics

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“…Especially, analyzing data, which changes their properties over time, is very difficult because they include a lot of inconsistent and uncertain information. In case of handling these data, a method using the useful parts of the data can be effective but requires various analysis techniques, generally principal components analysis (PCA), Fisher's linear discriminant analysis (LDA), feature subset selection (FSS), C-means clustering, radial basis function classification, K-nearest neighbor classification and so on [1][2][3][4][5]. To apply the above techniques, in addition, complex or various numerical analyses are accompanied independently [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Effective Gas Identification Model based on Fuzzy Logic and Hybrid Genetic Algorithms

Bang¹,

Byun

Lee³

2012

Journal of Sensor Science and Technology

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This paper presents an effective design method for a gas identification system. The design method adopted the sequential combination between the hybrid genetic algorithms and the TSK fuzzy logic system. First, the sensor grouping method by hybrid genetic algorithms led the effective dimensional reduction as well as effective pattern analysis from a large volume of pattern dimensions. Second, the fuzzy identification sub-models allowed handling the uncertainty of the sensor data extensively. By these advantages, the proposed identification model demonstrated high accuracy rates for identifying the five different types of gases; it was confirmed throughout the experimental trials.

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Process-based analysis of climate model ENSO simulations: Intermodel consistency and compensating errors

Linz

Tziperman

MacMartin

2014

J. Geophys. Res. Atmos.

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Citation:Linz, M., E. Tziperman, and D. G. MacMartin (2014) The input and output of these processes are identified and analyzed, some of which are motivated by the recharge oscillator theory. Several errors and compensating errors are identified. The east-west slope of the equatorial thermocline is found to respond to the central equatorial Pacific zonal wind stress as a damped driven harmonic oscillator in all models. This result is shown to be inconsistent with two different formulations of the recharge oscillator. East Pacific sea surface temperature (SST) responds consistently to changes in the thermocline depth in the eastern Pacific in the five CMIP models examined here. However, at time scales greater than 2 years, this consistent model response disagrees with observations, showing that the SST leads thermocline depth at long time scales. Compensating errors are present in the response of meridional transport of water away from the equator to SST: two different models show different response of the transport to off-equatorial wind curl and wind curl response to East Pacific SST. However, these two models show the same response of meridional transport to East Pacific SST. Identification of errors in specific physical processes can hopefully lead to model improvement by focusing model development efforts on these processes.

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Signal Processing for Intelligent Sensor Systems

Cited by 25 publications

References 0 publications

Investigation into use of piezoelectric sensors in a wheeled robot tire for surface characterization

Investigation into use of piezoelectric sensors in a wheeled robot tire for surface characterization

Effective Gas Identification Model based on Fuzzy Logic and Hybrid Genetic Algorithms

Process-based analysis of climate model ENSO simulations: Intermodel consistency and compensating errors

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