Time of flight measurement system for an ultrasonic anemometer

Chandran, Pooja; Bhakthavatchalu, Ramesh; Kumar, P. Pradeep

doi:10.1109/iccicct.2016.7988049

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…Furthermore, ultrasonic anemometers have high sensitivity and can perform well in harsh environments [29]. Finally, the high precision and wide measuring range of ultrasonic anemometers make them the first choice for wind measurement [30].The main wind measurement methods used in ultrasonic sensors are the vortex [31,32] and the time-of-flight (TOF) [29,33,34]. The vortex method determines wind speed by measuring the frequency of the vortex, based on the proportional relationship between the average flow velocity and the eddy current frequency.…”

mentioning

confidence: 99%

“…The vortex method determines wind speed by measuring the frequency of the vortex, based on the proportional relationship between the average flow velocity and the eddy current frequency. However, measuring the wind direction using the vortex method is complex [33,34]. The TOF method is easier to implement, and can obtain both the wind speed and direction simultaneously.…”

mentioning

confidence: 99%

“…The main wind measurement methods used in ultrasonic sensors are the vortex [31,32] and the time-of-flight (TOF) [29,33,34]. The vortex method determines wind speed by measuring the frequency of the vortex, based on the proportional relationship between the average flow velocity and the eddy current frequency.…”

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confidence: 99%

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Three-Dimensional Wind Measurement Based on Ultrasonic Sensor Array and Multiple Signal Classification

Teng

Zhu

et al. 2020

Sensors

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The wind power industry continues to experience rapid growth worldwide. However, the fluctuations in wind speed and direction complicate the wind turbine control process and hinder the integration of wind power into the electrical grid. To maximize wind utilization, we propose to precisely measure the wind in a three-dimensional (3D) space, thus facilitating the process of wind turbine control. Natural wind is regarded as a 3D vector, whose direction and magnitude correspond to the wind's direction and speed. A semi-conical ultrasonic sensor array is proposed to simultaneously measure the wind speed and direction in a 3D space. As the ultrasonic signal transmitted between the sensors is influenced by the wind and environment noise, a Multiple Signal Classification algorithm is adopted to estimate the wind information from the received signal. The estimate's accuracy is evaluated in terms of root mean square error and mean absolute error. The robustness of the proposed method is evaluated by the type A evaluation of standard uncertainty under a varying signal-to-noise ratio. Simulation results validate the accuracy and anti-noise performance of the proposed method, whose estimated wind speed and direction errors converge to zero when the SNR is over 15 dB.Sensors 2020, 20, 523 2 of 16 turbines, which further maximizes wind utilization efficiency [10]. In addition, wind measurement can be used to estimate the corresponding power generation, thus contributing to the system scheduling and energy dispatching, and, ultimately, the integration of wind power in the grid [11]. In summation, precise wind speed and direction measurements in a 3D space are of vital importance to wind energy utilization and the wind power industry.Light detection and ranging (LIDAR) technology is one of the most popular wind measurements [12]. However, LIDAR can only measure the wind speed component along the line of sight, a disadvantage known as "the Cyclops dilemma" [13,14]. Therefore, the wind distribution measurement in a 3D space would require the very costly installment and deployment of several LIDARs in the wind farm. In contrast, wind measurement sensors are much cheaper and could be deployed around the wind field in distances of miles to provide information for previewing wind measurement. Several types of wind measurement sensors have been employed by researchers, including cup anemometers [15][16][17], thermal anemometers [18][19][20], and ultrasonic anemometers [21][22][23]. However, measurements from cup anemometers often suffer from errors caused by wear and tear on the internal rotating bearings, and frequent inspection or calibration is required to ensure measurement accuracy [24,25]. The performance of cup anemometers can also be affected by the measuring environment. For example, cup anemometers are prone to jamming in humid environments, since water vapor can penetrate their bearings [26]. Thermal anemometers also have difficulties coping with harsh environments. In addition, their sensitivity to changes in the velocity f...

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Three-Dimensional Wind Measurement Based on Ultrasonic Sensor Array and Multiple Signal Classification

Teng

Zhu

et al. 2020

Sensors

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“…However, because the width of the scintillation pulse ranges from a few tens of nanoseconds to microseconds, directly measuring time information using an Arduino counter is insufficient to accurately measure the ToT signal. Hence, we combined the ToT circuit with a low-cost and low-power time-to-digital converter (TDC, TDC7200, Texas Instruments, TX, U.S.A.) [16][17][18].…”

Section: Low-cost Time-based Signal Readoutmentioning

confidence: 99%

Comparison of Arduino Nano and Due processors for time-based data acquisition for low-cost mobile radiation detection system

Lee¹,

Lee²,

Jang³

et al. 2022

J. Inst.

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Arduino is an open-source hardware and software platform that consists of a single-board microcontroller (MCU). Arduino offers low-cost and low-power operation, which allows the design of a mobile battery-operated device and offers easy programming with a wide range of compatible sensors. Hence, Arduino has recently been widely used as an inexpensive solution to build educational and evaluation tools. Here, we combined Arduino processors with custom-developed time-based signal readout electronics for a low-cost mobile radiation detection system; the system utilizes a time-over-threshold technique that provides compact electronics. Arduino processors were used for chip configuration, serial communication, and real-time data acquisition. In this study, we tested two commercial Arduino processors, Nano and Due, in various signal environments and compared their performances. The developed Arduino-based data acquisition system was combined with a 48 × 48 × 20 mm3 GAGG:Ce (Gd3Al2Ga3O12:Ce) scintillation crystal and an 8 × 8 array of 6 × 6 mm2 SiPM. The developed low-cost mobile gamma detection system achieved 9.35% energy resolution at 662 keV and was able to acquire events up to 600 Hz using an Arduino Nano.

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“…Analog signals are easily affected by noise so they can affect the measurement results. This causes the measurement results to have a small standard deviation [2,6]. Noise measurement results can be eliminated by using filters neither analog filters nor digital filters.…”

Section: Introductionmentioning

confidence: 99%

Development of Ultrasonic Anemometer Using HC-SR04 with Kalman Filter Based on Microcontroller Integrated IoT

et al. 2020

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Measurement of wind speed using an anemometer is very important in various fields. The most effective and efficient type of anemometer is the ultrasonic anemometer. This research develops an Arduino-based ultrasonic anemometer using the HC-SR04 sensor with a Kalman filter to reduce noise and integrated IoT with the Blynk application on a smartphone. The advantage of ultrasonic anemometer is not having analog signal conditioning and analog filters, thereby reducing the possibility of having noise, low cost, and can be monitored remotely. The ultrasonic anemometer has been calibrated on the wind tunnel and has a measurement resolution of 0.10 m/s and a measurement error of 0.14 m/s.

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Time of flight measurement system for an ultrasonic anemometer

Cited by 9 publications

References 11 publications

Three-Dimensional Wind Measurement Based on Ultrasonic Sensor Array and Multiple Signal Classification

Three-Dimensional Wind Measurement Based on Ultrasonic Sensor Array and Multiple Signal Classification

Comparison of Arduino Nano and Due processors for time-based data acquisition for low-cost mobile radiation detection system

Development of Ultrasonic Anemometer Using HC-SR04 with Kalman Filter Based on Microcontroller Integrated IoT

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