Pitch Sensors Research Articles

Examination of Heatsinking in Thermally Multiplexed TES Arrays With Buried Wiring

It is now possible to fabricate stacks of buried wires with extremely high density, perfect yield, and many layers using fine-line lithography and chemical mechanical polish. Such wiring in principle will enable large format arrays of fine pitch sensors. Buried wiring has the distinct advantage that additional metallization – such as metallic links in a thermal multiplexer (“hydra”) design and attachment points between absorbers and the substrate – are not limited in their placement. In close-packed arrays, thermal crosstalk occurs when a heat pulse in one device transmits through the dielectric connection and is absorbed in a neighbor. We seek to integrate Mo/Au transition edge sensors with such wiring but encounter limitations of fabrication options by the restriction of materials permitted to be used, including noble metals and certain dielectrics. In this paper we show measurement results of X-ray microcalorimeters with multi-stack buried wiring on a silicon nitride dielectric layer exploring new methods of integrating heat sinking. We attempt to mitigate thermal crosstalk channels by enhancing coupling of the emitted heat to a thick metallic heatsinking layer. We measure the thermal response in close packed hydra arrays in a variety of heatsinking configurations and show energy resolution and pulse response in these devices.

Fault Classification of a Blade Pitch System in a Floating Wind Turbine Based on a Recurrent Neural Network

This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training model with training data for decision-making. The ANN comprises an encoder and a decoder. The encoder uses a gated recurrent unit, which is a recurrent neural network, for dimensionality reduction of the input data. The decoder uses a multilayer perceptron (MLP) for diagnosis decision-making. To create data, we use a wind turbine simulator that enables fully coupled nonlinear time-domain numerical simulations of offshore wind turbines considering six fault types including biases and fixed outputs in pitch sensors and excessive friction, slit lock, incorrect voltage, and short circuits in actuators. The input data are time-series data collected by two sensors and two control inputs under the condition that of one fault of the six types occurs. A gated recurrent unit (GRU) that is one of the RNNs classifies the suggested faults of the blade pitch system. The performance of fault classification based on the gate recurrent unit is evaluated by a test procedure, and the results indicate that the proposed scheme works effectively. The proposed ANN shows a 1.4% improvement in its performance compared to an MLP-based approach.

Fault detection and diagnosis of a blade pitch system in a floating wind turbine based on Kalman filters and artificial neural networks

This paper describes the development of a fault detection and diagnosis method to automatically identify different fault conditions of a hydraulic blade pitch system in a spar-type floating wind turbine. For fault detection, a Kalman filter is employed to estimate the blade pitch angle and valve spool position of the blade pitch system. The fault diagnosis scheme is based on an artificial neural network method with supervised learning that is capable of diagnosing a predetermined fault type. The neural network algorithm produces a predictive model with training, validation and test procedures after the final performance evaluation. The validation and test procedures of the artificial neural network model are conducted with the training model to prove the model performance. The proposed method is demonstrated in case studies of a spar floating wind turbine with stochastic wind and wave conditions and with consideration of six different types of faults, such as biases and fixed outputs in pitch sensors and excessive friction, slit-lock, wrong voltage, and circuit shortage in actuators. The fault diagnosis results from the final performance evaluation show that the proposed methods work effectively with good performance.

Holistic approach to high-performance long-wave infrared system design

In past performance analyses and comparisons of midwave infrared (MWIR) and long-wave infrared (LWIR) systems, infrared systems scientists and engineers have not had the cumulative technologies that we will soon enjoy. Large format, small pitch, deep wells, and digital processing do not exist in a single focal plane, but they are a reality now individually and will exist collectively in the near future. How do we best use these technologies, and how do we compare sensors when we use these technologies? From a more fundamental aspect, how do you optimize a system given that practical limits are minimized and theoretical limits apply? Smaller pitch infrared detectors can provide longer range performance for a given aperture and higher photon collection duty cycles (deep wells and faster frame rates) can allow better modulation transfer function correction. Digital image processing allows for recovery of resolution by trading surplus signal-to-noise ratio. Nonuniformity correction becomes an important issue, but there are methods using higher duty cycles to address the problems. LWIR can compete with MWIR using the additional photons given an improved photon collection duty cycle. A holistic approach to system design can provide for an extremely high-performance system. It is also worth mentioning that infrared targeting sensor design in the future shall be quantified with more than just identification range. Since these technologies provide more than a human can consume, the sensors need to be designed to better utilize human consumption limits. An example is that small pitch high-density sensors (solid-state imaging) can provide faster target prosecution, which allows for faster target engagements. We show these possibilities using an LWIR targeting sensor to demonstrate the concept of optimizing pitch-well-processing.

Mobile C‐Arm with a CMOS detector: Technical assessment of fluoroscopy and Cone‐Beam CT imaging performance

Indirect-detection CMOS flat-panel detectors (FPDs) offer fine pixel pitch, fast readout, and low electronic noise in comparison to current a-Si:H FPDs. This work investigates the extent to which these potential advantages affect imaging performance in mobile C-arm fluoroscopy and cone-beam CT (CBCT). FPDs based on CMOS (Xineos 3030HS, 0.151mm pixel pitch) or a-Si:H (PaxScan 3030X, 0.194mm pixel pitch) sensors were outfitted on equivalent mobile C-arms for fluoroscopy and CBCT. Technical assessment of 2D and 3D imaging performance included measurement of electronic noise, gain, lag, modulation transfer function (MTF), noise-power spectrum (NPS), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ) in fluoroscopy (with entrance air kerma ranging 5-800nGy per frame) and cone-beam CT (with weighted CT dose index, CTDIw , ranging 0.08-1mGy). Image quality was evaluated by clinicians in vascular, orthopaedic, and neurological surgery in realistic interventional scenarios with cadaver subjects emulating a variety of 2D and 3D imaging tasks. The CMOS FPD exhibited ~2-3× lower electronic noise and ~7× lower image lag than the a-Si:H FPD. The 2D (projection) DQE was superior for CMOS at ≤50nGy per frame, especially at high spatial frequencies (~2% improvement at 0.5mm-1 and ≥50% improvement at 2.3mm-1 ) and was somewhat inferior at moderate-high doses (up to 18% lower DQE for CMOS at 0.5mm-1 ). For smooth CBCT reconstructions (low-frequency imaging tasks), CMOS exhibited ~10%-20% higher NEQ (at 0.1-0.5mm-1 ) at the lowest dose levels (CTDIw ≤0.1mGy), while the a-Si:H system yielded slightly (~5%) improved NEQ (at 0.1-0.5 lp/mm) at higher dose levels (CTDIw ≥0.6mGy). For sharp CBCT reconstructions (high-frequency imaging tasks), NEQ was ~32% higher above 1mm-1 for the CMOS system at mid-high-dose levels and ≥75% higher at the lowest dose levels (CTDIw ≤0.1 mGy). Observer assessment of 2D and 3D cadaver images corroborated the objective metrics with respect to a variety of pertinent interventional imaging tasks. Measurements of image noise, spatial resolution, DQE, and NEQ indicate improved low-dose performance for the CMOS-based system, particularly at lower doses and higher spatial frequencies. Assessment in realistic imaging scenarios confirmed improved visibility of fine details in low-dose fluoroscopy and CBCT. The results quantitate the extent to which CMOS detectors improve mobile C-arm imaging performance, especially in 2D and 3D imaging scenarios involving high-resolution tasks and low-dose conditions.

INDIRECT MEASUREMENT METHODOLOGY OF CARGO WEIGHT LIFTED BY THE EXCAVATOR IN THE CRANE MODE

Introduction.To solve the indirect measurement problem of the cargo weight lifted by the excavator in crane mode the authors propose the specific method and develop mathematical model according to the indications of hydraulic fluid pressure sensors in the piston and rod cavities of boom lifting cylinders. Moreover, the signals from the angle sensor of the boom and the handle relative to the gravity horizon are used, the roll and pitch sensors of the rotary column of the excavator relative to the gravity horizon are additionally applied.Materials and methods. As initial data of the indirect measurement method of cargo mass, constant design parameters, constant masses of moving links are used, such as booms with handle hydraulic cylinder, handles with bucket hydraulic cylinder and bucket turning mechanism, bucket weight. In addition, constant linear number and angular machine dimensions are included in the investigation. To obtain analytical formulas of the method, the method of homogeneous coordinates is applied, as well as the method of direct analytical inference.Results.The developed design scheme of the method is presented. As a result, the position of the excavator crane is described in the right-hand rectangular coordinate system. Moreover, the technique of indirect measurement of cargo mass according to the indications of hydraulic fluid pressure sensors in the form of formulae linear sequence is presented.Discussion and conclusion. The accuracy of the developed method was estimated by comparison with the results of the full-scale experiment. The relative reduced measurement error in the range of boom angles’ measurement and the crane-excavator handle was less than ten percent. Therefore, the technique merits are its simplicity, as well as record of the roll and pitch angles of the crane-excavator turntable element.

Autonomous Underwater Vehicle for Vision Based Tracking

This paper describes about the design, construction and control of an “Autonomous Underwater Vehicle for Vision Based Tracking”, built in Vignan’s Institute of Information Technology, Centre for Innovation Lab. The underwater vision robot is essentially an Autonomous Underwater Vehicle (AUV) for study of marine animals by automatically tracking and following them using computer vision. The AUV can also be used as a platform for Photo-mapping of the Seafloor using the onboard camera and light arrangement. The robot is proposed to have 5 thrusters configurations to achieve 4 degrees of freedom controlled by an Inertial Measurement Unit (IMU) interfaced with control unit and powered by commercial LiPo battery packs. The robot is equipped with roll, pitch, heading, and depth sensors which provide sufficient feedback signals to automatically control the vehicle to track a pre-planned trajectory. The centre of gravity and centre of buoyancy of the vehicle are positioned in such a way that it is self-stabilized. Along with this the combinations of sensors and speed control drivers provide more stability to the system using a closed loop control system, without the operator involvement.The AUV also captures videos during its mission using the camera. It is planned to have a multi-core umbilical cable for video signal, water leakage alarm, feedback signals and battery charging lines. This will be only used for development and test purposes and will be removed during autonomous missions. Various control schemes can be applied for the vehicle to track different paths. The AUV is designed to the dimension of 575×210×175mm.TheAUV uses O-rings for the hulls for good water sealing effect as well as for faster assembly and disassembly.We expect this AUV development to mature in to an advanced system can be used as a platform for study of the ocean by scientists, for environmental studies and for defense applications.

Model-based fault detection, fault isolation and fault-tolerant control of a blade pitch system in floating wind turbines

Abstract This paper presents model-based fault detection, fault isolation, and fault-tolerant control schemes focused on blade pitch systems in floating wind turbines. Fault detection, isolation, and accommodation techniques are required to achieve high power capture efficiency and structural reliability in floating wind turbines. Faults in blade pitch systems should be detected at an early stage to prevent catastrophic failures. To detect faults of the blade pitch systems, a Kalman filter is designed to estimate the blade pitch angle of the system. The fault isolation algorithm is based on inference methods and capable of determining the fault type, location, magnitude and time. The fault-tolerant controller based on a reconfiguration block with a virtual sensor and shutdown mode controls the floating wind turbine to avoid unexpected external loads. The proposed methods are demonstrated in case studies with stochastic wind and wave conditions that considering different types of faults, such as biases and fixed outputs in pitch sensors and stuck pitch actuators. The simulation results show that the proposed methods can detect and isolate multiple faults effectively at an early stage. Additionally, the effectiveness of the fault-tolerant control systems for different load cases for single and multiple fault conditions is verified by numerical simulations.

Model-based fault detection of blade pitch system in floating wind turbines

This paper presents a model-based scheme for fault detection of a blade pitch system in floating wind turbines. A blade pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be detected at the early stage to prevent failures. To detect faults of blade pitch actuators and sensors, an appropriate observer should be designed to estimate the states of the system. Residuals are generated by a Kalman filter and a threshold based on H optimization, and linear matrix inequality (LMI) is used for residual evaluation. The proposed method is demonstrated in a case study that bias and fixed output in pitch sensors and stuck in pitch actuators. The simulation results show that the proposed method detects different realistic fault scenarios of wind turbines under the stochastic external winds.

Evaluation of Aircraft Sensor Failures Effects Using the Artificial Immune System Paradigm

This paper presents the development of simple models for the assessment of flight envelope reduction under aircraft sensor failures within the artificial immune system paradigm. The proposed methodology is expected to facilitate the design of on-board augmentation systems increasing aircraft survivability and improving operation safety. It demonstrates and exploits the capability of the artificial immune system to not only detect and identify aircraft subsystem abnormal conditions but also evaluate their impact and consequences. An artificial immune system built through simulation for a fighter aircraft is used in conjunction with a hierarchical multi-self strategy for estimating ranges of flight envelope relevant variables at post-failure conditions affecting angular rate sensors that are needed within the control augmentation system. Failure-specific algorithms correlated with the characteristics and dimensionality of self projections are developed for roll, pitch, and yaw rate sensors affected by bias. Metrics for the performance evaluation of the proposed approach are defined and used for successful demonstration in a motion-based flight simulator.

Sensor Failure Detection, Identification, and Accommodation Using Fully Connected Cascade Neural Network

Modern control systems rely heavily on their sensors for reliable operation. Failure of a sensor could destabilize the system, which could have serious consequences to the system's operations. Therefore, there is a need to detect and accommodate such failures, particularly if the system in question is of a safety critical application. In this paper, a sensor failure detection, identification, and accommodation (SFDIA) scheme is presented. This scheme is based on the fully connected cascade (FCC) neural network (NN) architecture. The NN is trained using the neuron by neuron learning algorithm. This NN architecture is chosen because of its efficiency in terms of the number of neurons and the number of inputs required to solve a problem. The SFDIA scheme considers failures in pitch, roll, and yaw rate gyro sensors of an aircraft. A total of 105 experiments were conducted; out of which, only one went undetected. The SFDIA scheme presented here is efficient, compact, and computationally less expensive, in comparison to schemes using, for example, the popular multilayer perceptron NN. These benefits are inherited from the FCC NN architecture.

A Robust Estimation Method for Correcting Dynamic Draft Error in PPK GPS Elevation Using ADCP Tilt Data

Abstract Measuring temporal and spatial variations in water level with high resolution and accuracy can provide fundamental insights into the hydrodynamics of marine and riverine systems. Real-time kinematic global positioning systems (RTK GPS), and by extension postprocessed kinematic (PPK) positioning, have provided the opportunity to achieve this goal, by allowing fast and straightforward measurements with subdecimeter accuracy. However, boat-mounted GPS are subject to movements of the water surface (e.g., waves, long-period heaves) as well as to the effects of dynamic draft. The latter contaminate the records and need to be separated and removed from the data. A method is proposed to postcorrect the elevation data using tilt information measured by an attitude sensor—in this case, an acoustic Doppler current profiler (ADCP) equipped with internal pitch and roll sensors. The technique uses iteratively reweighted least squares (IRLS) regressions to determine the position of the center of rotation (COR) of the boat that leads to optimal corrections. The COR is also allowed to change in time by performing the IRLS analyses on data subsamples, thus accounting for changes in weight distribution, for example, due to personnel movements. An example of application is presented using data collected in the Saint Lawrence fluvial estuary. The corrections exhibit significant reductions associated with the boat motion while keeping subtle variations in water levels likely related to local hydrodynamics.

Hybrid Model–Based Fault Detection of Wind Turbine Sensors

AbstractIn order to improve reliability of wind turbines, it is important to detect faults in their very early occurrence, and to handle them in an optimal way. This paper focuses on the pitch sensors of the turbine blade system, as they are mainly used for wind turbine control, in order to maximise the power production, and the efficiency of the whole process. On the other hand, as the input-output behaviour of the system under diagnosis is nonlinear, this work suggests a modelling scheme relying on piecewise affine models, whose parameters are identified through the acquired input–output measurements affected by measurement uncertainty. Therefore, these hybrid prototypes are exploited for generating suitable residual signals, which allow the detection and the isolation of the considered sensor faults. This noise rejection scheme is used since the wind turbine measurements are not very reliable, due to the uncertainty of wind speed acting on the wind turbine, and to the turbulence around the rotor plane. A detailed benchmark model simulating the wind turbine where realistic fault conditions can be considered shows the effectiveness of both the identification and fault diagnosis techniques.

An automated sensor-based method of simple behavioural classification of sheep in extensive systems

Automated sensor-based behaviour classification systems are already developed and used for cattle in an agricultural context. To develop a similar tool for sheep we investigated the use of pitch and roll tilt sensors to provide information about sheep behaviour. The aim was to determine if different behaviour types associated with grazing can be accurately identified using tilt sensor data. We collected data from two adjacent enclosures at two contrasting sites, one in the Southern Uplands grazed by Cheviot ewes and one in the Western Highlands of Scotland grazed by Scottish Blackface ewes. In addition to our observations of ewes on hill pasture we also observed collared ewes in flat and gently sloped fields and in a shed to evaluate the tilt data. The data was analysed using three classification methods, a linear discriminant analysis, a classification tree method, and a manually developed decision tree consisting of four “if then” loops. We found that we can distinguish between the two behaviour categories “active” and “inactive”, even if only pitch tilt data is used. All three methods provide very good classification predictions with more than 90% correct results. However, the classification tree method was less robust than the other methods. Using the manually developed decision tree, we produced results of activity that were robust and credible. By using the behaviour classification we are able to collect data on different genotypes, systems or management options in sheep farming, and in combination with GPS we will be able to improve management strategies and gain information about grazing ecology. It can also be seen as a first step to support farmers with a viable system to comply with welfare regulations in the light of European Union Common Agricultural Policy and as an integral part for future developments regarding virtual fencing technology for sheep.

DESIGN, DEVELOPMENT AND LOCOMOTION CONTROL OF BIO-FISH ROBOT WITH UNDULATING ANAL FINS

This paper describes the design of the propulsion system and depth control of a robot fish. The design is inspired from the knifefish. The propulsion system is based on the undulating fins. A simplified model of the fins is constructed by using oscillating servomotors to which are attached cranks holding flexible membranes that can slide permitting the variation of the length of the fins. The depth control was inspired from the gas bladder of fish which changes volume to control the depth based on the buoyancy forces. A buoyancy tank, equipped with two pistons, is used to change the submerged volume. Proximity sensors are used to monitor and limit the piston movement. The robot fish was controlled using microprocessors which takes readings from proximity, depth and pitch sensors, and implements a control scheme. Bluetooth technology was used to interface the robot fish to a laptop to allow the operator to control the robot fish. The propulsion speed was measured as a function of phase angle and a frequency of the servomotors. Testing has also been conducted in an outdoor diving pool to demonstrate the capability of the knifefish robot in various swimming courses and also the depth control of the bio-fish 4 m under the water. The design structures and mechanisms can be scaled down for micro-bio-fish models. The micro-fin model driven by a smart actuator is being tested. The bio-mechatronics implementation can be applied in defence and medical applications as the model is modular, scalable, and re-configurable.

磁気センサを用いたドリル先端位置検知精度の改善

Precise measurement of drill head position is required to avoid the collision between the drill head and underground facilities, when a horizontal drilling machine is used for constructing underground gas pipes in the city. A positioning technique without special devices on the ground surface has been expected especially beneath the waterway or heavy traffic road, because it is difficult to conduct the measurement for locating the drill head position on the ground surface.The authors have studied both magnetic and pitch sensors installed inside the drilling tool for locating drill head position, and we have found that alignment of two sets of magnetic sensors is effective to reduce noise in the city which disturbs the natural magnetic field. We have confirmed that the sensors can keep the drill head position with a precision less than 10 cm, when the drill head progresses 12 m along the drill hole. Engineers and workers do not have to walk around just above the underground drilling site to locate the drill head position by using the sensors.

Probe configurations for hot-dome anemometry

Measurements were obtained in the Rensselaer transonic windtunnel with front and side sensors on block and domed configurations of hot-dome probes in the uniform freestream over the range Mach 0.42 to 0.82 and for pitch and yaw angles of up to 60 deg. Results are presented with two hot-dome probe configurations, a block probe and a domed probe, and quantify effects of probe geometry, angle sensitivity, and velocity up to transonic Mach numbers. Block probe showed turbulence generation in the vicinity of the hot-film sensors, probably associated with recirculating flow downstream of its sharp corners. The domed probe was designed with rounded front and side surfaces to realize benefits from aerodynamic contouring and effect reductions in blockage, probe interference, separation, and compressibility. The curved front sensor of the domed probe responded primarily to the normal component of cooling velocity, and this implies that the front sensor of domed probes can be used to obtain the magnitude of flow velocity. Responses of pitch and yaw sensors on the domed probe suggest angle calibrations similar to those for five-hole impact probes may be suitable for hot-dome probes.

GPS MARINE KINEMATIC POSITIONING ACCURACY AND RELIABILITY

Positioning accuracy and reliability are two parameters of major concern to GPS marine users. GPS limitations and error sources are analyzed from a user’s point of view. The coverage limitations inherent to the (18 + 3) satellite constellation are discussed and related outages inherent to specific geographical areas are described. Receiver and antenna characteristics are described in relation to their effect on positioning accuracy and reliability. Antenna requirements for shipborne applications are discussed. The effect of the troposphere and ionosphere on GPS measurements is quantified for various cases. Multipath and imaging effects on both P and CIA code and carrier phase measurements are discussed. A variety of user accuracy and reliability enhancements are described. These include the use of seven-channel receivers and that of height and time constraints to increase redundancy and limit poor geometry effects, the use of differential methods to reduce satellite and propagation medium errors, the integration of code and carrier phase measurements to increase positioning accuracy, and the use of external sensors such as pitch and roll sensors, and inertial navigation systems. It is concluded that GPS is capable of achieving the one metre accuracy level for marine applications provided that error sources specific to shipborne applications can be effectively controlled.

STABILITY OF SINGLE AXIS GYROS IN A CIRCULAR ORBIT

The stability of single axis gyros mounted on a vehicle in circular motion about a central force field is examined for several orientations of the spin vector and output axis. When the orientation of the output axis is in the radial or tangential direction of the orbit, as in the case of pitch or roll sensors, the stability is dependent on the ratio of the spin angular velocity to the vehicle angular velocity around the orbit and the ratio of the moments of inertia of the gyro wheel. When the orientation of the output axis is fixed in inertial space, as in an inertial platform, the equations of motion are of the Mathieu type. The stability in this case is independent of the spin angular velocity of the gyro wheel and is a function of the moment of inertia ratio of the wheel, the angular velocity of the vehicle around the orbit, and the desired orentation of the spin velocity vector.