The Experts below are selected from a list of 102 Experts worldwide ranked by ideXlab platform

Seung-bok Choi - One of the best experts on this subject based on the ideXlab platform.

  • Vibration control of a Camera Mount system for an unmanned aerial vehicle using piezostack actuators
    Smart Materials and Structures, 2011
    Co-Authors: Young-min Han, Seung-bok Choi
    Abstract:

    This work proposes an active Mount for the Camera systems of unmanned aerial vehicles (UAV) in order to control unwanted vibrations. An active actuator of the proposed Mount is devised as an inertial type, in which a piezostack actuator is directly connected to the inertial mass. After evaluating the actuating force of the actuator, it is combined with the rubber element of the Mount, whose natural frequency is determined based on the measured vibration characteristics of UAV. Based on the governing equations of motion of the active Camera Mount, a robust sliding mode controller (SMC) is then formulated with consideration of parameter uncertainties and hysteresis behavior of the actuator. Subsequently, vibration control performances of the proposed active Mount are experimentally evaluated in the time and frequency domains. In addition, a full Camera Mount system of UAVs that is supported by four active Mounts is considered and its vibration control performance is evaluated in the frequency domain using a hardware-in-the-loop simulation (HILS) method.

  • performance evaluation on an active Camera Mount system for uav via hardware in the loop simulation
    Transactions of The Korean Society for Noise and Vibration Engineering, 2010
    Co-Authors: Seung-bok Choi, Hanjun Cho, Chulhee Lee, Myeongwoo Cho
    Abstract:

    In the present work, vibration control performance of piezoactuator-based active Mount system for unmanned aero vehicle(UAV) equipment is evaluated via hardware in the loop simulation(HILS). At first, the vibration level of UAV is measured and from this vibration data, the proper piezostack actuator is selected. Then, the dynamic model of active Mount system including four active Mounts and UAV Camera equipment is derived. In order to evaluate vibration control performance, the HILS system is constructed. The proposed Mount is prepared as hardware part and the other Mounts are considered in software part. A sliding mode controller is designed and implemented to the HILS system. Effective vibration control results are presented in both time and frequency domains.

Lewis, Quinn W. - One of the best experts on this subject based on the ideXlab platform.

  • Measuring flow and mixing at stream confluences using large-scale particle image velocimetry, in-stream techniques, and small unmanned aerial systems
    2020
    Co-Authors: Lewis, Quinn W.
    Abstract:

    Confluences, locations where two rivers flow into one another, are characterized by the mixing of water, dissolved nutrients, chemicals, pollutants, and sediment. The process of mixing at confluences is inherently related to patterns of confluent flows, yet the complex nature of confluence hydrodynamics has limited efforts to generalize how mixing occurs at these locations in river systems. Although traditional in-stream measurements of three-dimensional velocities using hydroacoustic instruments provide valuable information on confluence hydrodynamics, such measurements are relatively limited in spatial resolution. State-of-the-art high-resolution velocity-measurement techniques based on analysis of low-level imagery obtained by Cameras positioned above the water surface have the potential to document in detail complex patterns of at confluences. Thus far, however, no studies have applied these emerging image-based methods to characterize flow at confluences, or have examined how imagery-based velocity measurement techniques might be enhanced by the acquisition of imagery using small unmanned aerial systems (sUAS). The objectives of this dissertation are to: 1) investigate the accuracy of LSPIV for characterizing two-dimensional patterns of surface flow at stream confluences and 2) to use in-stream measurements of three-dimensional velocity, temperature, and turbidity to characterize mixing patterns and rates at confluences and to examine how mixing at confluences varies with changes in controlling factors. The dissertation research is organized into four distinct investigations focusing on flow and mixing at river confluences. The first study investigates the potential for using large-scale particle image velocimetry (LSPIV), an imagery-based velocity measurement technique typically employed in laboratory settings or in simple, uniform flows in the field, for improving understanding of complex two-dimensional flow at a river confluence. This study develops a stationary, river channel-spanning Camera Mount onto which a small action Camera is anchored. The Camera records the movement of inexpensive, recycled landscape mulch on the surface of the water, and compares the resultant LSPIV-derived velocity with near-surface acoustic velocity measurements. The accuracy of the LSPIV compares favorably to the acoustic measurements, yet LSPIV can be used to obtain velocity over a large spatial extent. The chapter then focuses on applying the strengths inherent in the high spatial and temporal resolution afforded by LSPIV to characterize complex two-dimensional flow structures at a river confluence. The results of this chapter confirm that LSPIV can be a cost efficient and effective supplement to traditional studies in regions of complex flow, and on its own can be used to better understand aspects of flow at confluences such as wake-like flow and shear-layer dominated flow along the confluence shear layer. The second study extends the analysis of LSPIV methodology at confluences by exploring the potential benefits or disadvantages of using sUAS to obtain LSPIV imagery. This chapter specifically focuses on the potential capability of sUAS to measure complex mean flow and quasi-instantaneous snapshots of flow structure in river confluences with strong two-dimensional velocity gradients. In this study, LSPIV results from a mobile tripod, a channel-spanning stationary Camera Mount, and sUAS are compared. The accuracy of each method is compared to near-surface acoustic velocity measurements, and all methods are found to be accurate in comparison to the in-stream measurements. Although the sUAS is not fixed and moves slightly in three dimensions when hovering over the water surface, movement rapidly converges to a net of zero within tens of seconds even in relatively windy conditions. The results of this study indicate that mean velocities obtained with sUAS-derived LSPIV are just as accurate as with fixed methods, but can be a substantial improvement because of increased locational flexibility of the field of view. In addition, this study explores the effect of total sUAS image distortion, and confirms that image distortion is not meaningful when flying within about 20 m of the water surface and thus extensive image rectification is not required. Finally, this study investigates the conditions under which quasi-instantaneous snapshots of flow structures can be recorded with sUAS-derived LSPIV. Results reveal that, while more challenging than recording mean velocities, snapshots of flow structure can be obtained using sUAS when the flow structure is many times larger than the LSPIV interrogation area, and if the velocity signal that defines the flow structure is substantially larger than any apparent velocity signal caused by LSPIV error (such as spare seeding or Camera movement). The dissertation’s third chapter builds upon the first two be applying the developed LSPIV and sUAS methodology to produce a study of highly-detailed hydrodynamic mapping at two river confluences. Flow at two river confluences under high and low momentum ratios are investigated in unprecedented spatial detail. Results of this investigation reveal similarities between flow at each confluence and the standard conceptual model of flow at confluences, yet also finds important differences between the field cases and expectations derived from the standard conceptual model. This investigation exposes details about how the presence and location of the expected hydrodynamic zones changes with changing momentum ratio and confluence morphology and confirms that both variables have strong controls on confluence hydrodynamics. Results of this research unequivocally confirm the presence of wake-like flow at confluences at low momentum ratio and shear-layer flow at high momentum ratio, but also show that flow within the stagnation zone and shear layer at one confluence was not strongly controlled by momentum ratio. Detailed hydrodynamic maps for each confluence under each flow condition are produced, which can be directly compared to conceptual, computational, or laboratory models of confluent flow. The dense array of velocity measurements afforded by sUAS-derived LSPIV are combined with in-stream measurements to demonstrate the advancement of knowledge of flow at confluences driven by the application of these new techniques. The fourth and final investigation assess mixing dynamics at three confluences with distinct external (i.e. geometrical and morphological) characteristics. This study uses detailed measurements of three-dimensional velocity and spatially coincident measurements of temperature and turbidity to determine how patterns of mixing respond to velocity patterns. This research builds upon the growing body of work on mixing at confluences by obtaining these detailed measurements over a suite of flow conditions at each confluence. This study also assesses mixing rates with a formula based on tracer variance that can be compared among different sites and flow conditions. The results of this study indicate that channel-scale secondary flow drives momentum transfer along the mixing interface between flows, and therefore is the dominant control on mixing. The dominant form of secondary flow is coherent helical cells driven by flow streamline curvature and the associated pressure gradient, although this study also shows that in cases without extensive helical flow cells substantial mixing (up to 40%) can occur at one of the confluences. This investigation also confirms that mixing appears to be positively correlated with momentum ratio, negatively correlated with flow scale (e.g. depth), and might be affected by density differences in some cases. This study provides the groundwork for future detailed studies of mixing at these sites supported by thorough analytical and computational investigation. In conclusion, the results of the research presented in this dissertation improve understanding of flow and mixing at river confluences under a suite of external (geometrical and morphological) and internal (hydrodynamic) controls, while simultaneously advancing LSPIV and sUAS methodologies. This dissertation also provides a foundation for ongoing and future computational modeling of flow at confluences, and offers the potential for future comparisons among field, laboratory, and computational work using mixed methodology approaches that yield high-resolution data in the field.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

  • Measuring flow and mixing at stream confluences using large-scale particle image velocimetry, in-stream techniques, and small unmanned aerial systems
    2018
    Co-Authors: Lewis, Quinn W.
    Abstract:

    Confluences, locations where two rivers flow into one another, are characterized by the mixing of water, dissolved nutrients, chemicals, pollutants, and sediment. The process of mixing at confluences is inherently related to patterns of confluent flows, yet the complex nature of confluence hydrodynamics has limited efforts to generalize how mixing occurs at these locations in river systems. Although traditional in-stream measurements of three-dimensional velocities using hydroacoustic instruments provide valuable information on confluence hydrodynamics, such measurements are relatively limited in spatial resolution. State-of-the-art high-resolution velocity-measurement techniques based on analysis of low-level imagery obtained by Cameras positioned above the water surface have the potential to document in detail complex patterns of at confluences. Thus far, however, no studies have applied these emerging image-based methods to characterize flow at confluences, or have examined how imagery-based velocity measurement techniques might be enhanced by the acquisition of imagery using small unmanned aerial systems (sUAS). The objectives of this dissertation are to: 1) investigate the accuracy of LSPIV for characterizing two-dimensional patterns of surface flow at stream confluences and 2) to use in-stream measurements of three-dimensional velocity, temperature, and turbidity to characterize mixing patterns and rates at confluences and to examine how mixing at confluences varies with changes in controlling factors. The dissertation research is organized into four distinct investigations focusing on flow and mixing at river confluences. The first study investigates the potential for using large-scale particle image velocimetry (LSPIV), an imagery-based velocity measurement technique typically employed in laboratory settings or in simple, uniform flows in the field, for improving understanding of complex two-dimensional flow at a river confluence. This study develops a stationary, river channel-spanning Camera Mount onto which a small action Camera is anchored. The Camera records the movement of inexpensive, recycled landscape mulch on the surface of the water, and compares the resultant LSPIV-derived velocity with near-surface acoustic velocity measurements. The accuracy of the LSPIV compares favorably to the acoustic measurements, yet LSPIV can be used to obtain velocity over a large spatial extent. The chapter then focuses on applying the strengths inherent in the high spatial and temporal resolution afforded by LSPIV to characterize complex two-dimensional flow structures at a river confluence. The results of this chapter confirm that LSPIV can be a cost efficient and effective supplement to traditional studies in regions of complex flow, and on its own can be used to better understand aspects of flow at confluences such as wake-like flow and shear-layer dominated flow along the confluence shear layer. The second study extends the analysis of LSPIV methodology at confluences by exploring the potential benefits or disadvantages of using sUAS to obtain LSPIV imagery. This chapter specifically focuses on the potential capability of sUAS to measure complex mean flow and quasi-instantaneous snapshots of flow structure in river confluences with strong two-dimensional velocity gradients. In this study, LSPIV results from a mobile tripod, a channel-spanning stationary Camera Mount, and sUAS are compared. The accuracy of each method is compared to near-surface acoustic velocity measurements, and all methods are found to be accurate in comparison to the in-stream measurements. Although the sUAS is not fixed and moves slightly in three dimensions when hovering over the water surface, movement rapidly converges to a net of zero within tens of seconds even in relatively windy conditions. The results of this study indicate that mean velocities obtained with sUAS-derived LSPIV are just as accurate as with fixed methods, but can be a substantial improvement because of increased locational flexibility of the field of view. In addition, this study explores the effect of total sUAS image distortion, and confirms that image distortion is not meaningful when flying within about 20 m of the water surface and thus extensive image rectification is not required. Finally, this study investigates the conditions under which quasi-instantaneous snapshots of flow structures can be recorded with sUAS-derived LSPIV. Results reveal that, while more challenging than recording mean velocities, snapshots of flow structure can be obtained using sUAS when the flow structure is many times larger than the LSPIV interrogation area, and if the velocity signal that defines the flow structure is substantially larger than any apparent velocity signal caused by LSPIV error (such as spare seeding or Camera movement). The dissertation’s third chapter builds upon the first two be applying the developed LSPIV and sUAS methodology to produce a study of highly-detailed hydrodynamic mapping at two river confluences. Flow at two river confluences under high and low momentum ratios are investigated in unprecedented spatial detail. Results of this investigation reveal similarities between flow at each confluence and the standard conceptual model of flow at confluences, yet also finds important differences between the field cases and expectations derived from the standard conceptual model. This investigation exposes details about how the presence and location of the expected hydrodynamic zones changes with changing momentum ratio and confluence morphology and confirms that both variables have strong controls on confluence hydrodynamics. Results of this research unequivocally confirm the presence of wake-like flow at confluences at low momentum ratio and shear-layer flow at high momentum ratio, but also show that flow within the stagnation zone and shear layer at one confluence was not strongly controlled by momentum ratio. Detailed hydrodynamic maps for each confluence under each flow condition are produced, which can be directly compared to conceptual, computational, or laboratory models of confluent flow. The dense array of velocity measurements afforded by sUAS-derived LSPIV are combined with in-stream measurements to demonstrate the advancement of knowledge of flow at confluences driven by the application of these new techniques. The fourth and final investigation assess mixing dynamics at three confluences with distinct external (i.e. geometrical and morphological) characteristics. This study uses detailed measurements of three-dimensional velocity and spatially coincident measurements of temperature and turbidity to determine how patterns of mixing respond to velocity patterns. This research builds upon the growing body of work on mixing at confluences by obtaining these detailed measurements over a suite of flow conditions at each confluence. This study also assesses mixing rates with a formula based on tracer variance that can be compared among different sites and flow conditions. The results of this study indicate that channel-scale secondary flow drives momentum transfer along the mixing interface between flows, and therefore is the dominant control on mixing. The dominant form of secondary flow is coherent helical cells driven by flow streamline curvature and the associated pressure gradient, although this study also shows that in cases without extensive helical flow cells substantial mixing (up to 40%) can occur at one of the confluences. This investigation also confirms that mixing appears to be positively correlated with momentum ratio, negatively correlated with flow scale (e.g. depth), and might be affected by density differences in some cases. This study provides the groundwork for future detailed studies of mixing at these sites supported by thorough analytical and computational investigation. In conclusion, the results of the research presented in this dissertation improve understanding of flow and mixing at river confluences under a suite of external (geometrical and morphological) and internal (hydrodynamic) controls, while simultaneously advancing LSPIV and sUAS methodologies. This dissertation also provides a foundation for ongoing and future computational modeling of flow at confluences, and offers the potential for future comparisons among field, laboratory, and computational work using mixed methodology approaches that yield high-resolution data in the field

Ville V. Lehtola - One of the best experts on this subject based on the ideXlab platform.

  • MOTORIZED PANORAMIC Camera Mount – CALIBRATION AND IMAGE CAPTURE
    ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, 2016
    Co-Authors: Heikki Kauhanen, Petri Rönnholm, Ville V. Lehtola
    Abstract:

    Abstract. interesting applications. Among the large variation of panoramic Camera systems, we have focused on concentric panoramic imaging with a frame Camera. In order to establish the concentric image acquisition, the Camera Mount must be calibrated so that the projection centre of the Camera is located at the rotation centre of the Mount. For this purpose, we developed a novel Mount calibration method, which allows an accurate recovery of the rotation centre in two image acquisition steps. In addition, we have built a motorized Camera Mount that can self-calibrate the Camera position within the Mount, given the previously solved rotation centre, and then be used to automatically capture panoramic images. Hence, we have streamlined the previously laborious manual phase of iterative position calibration, but also automated the capturing of panoramic images. For validation purposes, reference results from a conventional manual Mount are provided. In the case of non-motorized Mount, the average distance between the projection centre of the Camera and the rotation centre of the Mount was 0.253 mm and the standard deviation was 0.161 mm. For the motorized Mount, the corresponding average distance and standard deviation were 0.549 mm and 0.404 mm, respectively.

  • MOTORIZED PANORAMIC Camera Mount – CALIBRATION AND IMAGE CAPTURE
    ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, 2016
    Co-Authors: Heikki Kauhanen, Petri Rönnholm, Ville V. Lehtola
    Abstract:

    interesting applications. Among the large variation of panoramic Camera systems, we have focused on concentric panoramic imaging with a frame Camera. In order to establish the concentric image acquisition, the Camera Mount must be calibrated so that the projection centre of the Camera is located at the rotation centre of the Mount. For this purpose, we developed a novel Mount calibration method, which allows an accurate recovery of the rotation centre in two image acquisition steps. In addition, we have built a motorized Camera Mount that can self-calibrate the Camera position within the Mount, given the previously solved rotation centre, and then be used to automatically capture panoramic images. Hence, we have streamlined the previously laborious manual phase of iterative position calibration, but also automated the capturing of panoramic images. For validation purposes, reference results from a conventional manual Mount are provided. In the case of non-motorized Mount, the average distance between the projection centre of the Camera and the rotation centre of the Mount was 0.253 mm and the standard deviation was 0.161 mm. For the motorized Mount, the corresponding average distance and standard deviation were 0.549 mm and 0.404 mm, respectively.

Young-min Han - One of the best experts on this subject based on the ideXlab platform.

  • Vibration control of a Camera Mount system for an unmanned aerial vehicle using piezostack actuators
    Smart Materials and Structures, 2011
    Co-Authors: Young-min Han, Seung-bok Choi
    Abstract:

    This work proposes an active Mount for the Camera systems of unmanned aerial vehicles (UAV) in order to control unwanted vibrations. An active actuator of the proposed Mount is devised as an inertial type, in which a piezostack actuator is directly connected to the inertial mass. After evaluating the actuating force of the actuator, it is combined with the rubber element of the Mount, whose natural frequency is determined based on the measured vibration characteristics of UAV. Based on the governing equations of motion of the active Camera Mount, a robust sliding mode controller (SMC) is then formulated with consideration of parameter uncertainties and hysteresis behavior of the actuator. Subsequently, vibration control performances of the proposed active Mount are experimentally evaluated in the time and frequency domains. In addition, a full Camera Mount system of UAVs that is supported by four active Mounts is considered and its vibration control performance is evaluated in the frequency domain using a hardware-in-the-loop simulation (HILS) method.

Heikki Kauhanen - One of the best experts on this subject based on the ideXlab platform.

  • MOTORIZED PANORAMIC Camera Mount – CALIBRATION AND IMAGE CAPTURE
    ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, 2016
    Co-Authors: Heikki Kauhanen, Petri Rönnholm, Ville V. Lehtola
    Abstract:

    Abstract. interesting applications. Among the large variation of panoramic Camera systems, we have focused on concentric panoramic imaging with a frame Camera. In order to establish the concentric image acquisition, the Camera Mount must be calibrated so that the projection centre of the Camera is located at the rotation centre of the Mount. For this purpose, we developed a novel Mount calibration method, which allows an accurate recovery of the rotation centre in two image acquisition steps. In addition, we have built a motorized Camera Mount that can self-calibrate the Camera position within the Mount, given the previously solved rotation centre, and then be used to automatically capture panoramic images. Hence, we have streamlined the previously laborious manual phase of iterative position calibration, but also automated the capturing of panoramic images. For validation purposes, reference results from a conventional manual Mount are provided. In the case of non-motorized Mount, the average distance between the projection centre of the Camera and the rotation centre of the Mount was 0.253 mm and the standard deviation was 0.161 mm. For the motorized Mount, the corresponding average distance and standard deviation were 0.549 mm and 0.404 mm, respectively.

  • MOTORIZED PANORAMIC Camera Mount – CALIBRATION AND IMAGE CAPTURE
    ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, 2016
    Co-Authors: Heikki Kauhanen, Petri Rönnholm, Ville V. Lehtola
    Abstract:

    interesting applications. Among the large variation of panoramic Camera systems, we have focused on concentric panoramic imaging with a frame Camera. In order to establish the concentric image acquisition, the Camera Mount must be calibrated so that the projection centre of the Camera is located at the rotation centre of the Mount. For this purpose, we developed a novel Mount calibration method, which allows an accurate recovery of the rotation centre in two image acquisition steps. In addition, we have built a motorized Camera Mount that can self-calibrate the Camera position within the Mount, given the previously solved rotation centre, and then be used to automatically capture panoramic images. Hence, we have streamlined the previously laborious manual phase of iterative position calibration, but also automated the capturing of panoramic images. For validation purposes, reference results from a conventional manual Mount are provided. In the case of non-motorized Mount, the average distance between the projection centre of the Camera and the rotation centre of the Mount was 0.253 mm and the standard deviation was 0.161 mm. For the motorized Mount, the corresponding average distance and standard deviation were 0.549 mm and 0.404 mm, respectively.