Measurement range expansion of continuous wave ultrasonic anemometer

Han, Dongwoo; Park, Sekwang

doi:10.1016/j.measurement.2011.08.030

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…If the airflow/temperature-induced phase difference is less than half a cycle (180°), the TOF difference is simply the difference between the current phase and preceding phase (∆ , −1 ) multiplied by . This is used by the most prevalent algorithm in the literature [11], which limits the phase difference to 0.5 (the current phase must be within a half cycle of the initial calibration phase ( 0 )). The maximum airflow/temperature range measurable by this method is calculated from (1).…”

Section: Fundamentalsmentioning

confidence: 99%

“…These methods typically assume that airflow-and temperature-induced phase changes remain within a half-wave cycle, thus limiting the measurable velocity and temperature range of the anemometer [7]- [10]. Decreasing the ultrasound frequency decreases the airflow-induced phase difference and increases the half-cycle phase detection range [11], though at some cost in sensitivity. However, even for lower frequencies, the phase differences are prone to exceed half a cycle in typical air flows, especially during significant temperature changes.…”

Section: Introductionmentioning

confidence: 99%

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Measuring Air Speed With a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking

et al. 2019

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Indoor air movement affects many functions of buildings, including ventilation and air quality, comfort and health of occupants, fire safety, and building energy use. Accurately measuring air movement has been difficult and expensive over extended periods of time, especially for velocities below 1 m/s. A new type of high frequency ultrasonic transceiver provides high sensitivity measurements and low cost through microelectromechanical systems (MEMS) manufacturing. However, at high frequencies, conventional ultrasonic signal processing algorithms function only over small ranges of ambient temperature and velocity. In this paper, we describe three algorithms that use the complex phase angle of an ultrasonic pulse to measure velocity and temperature over extended ranges of temperature and velocity. They employ heuristics to track the vibration cycle of the measured phase angle. These methods are applied in a pulse-based anemometer whose 176kHz MEMS transceivers both transmit and receive. In wind tunnel tests between 0-4 m/s, the tracking algorithm with a low-pass filter measured air speed with high sensitivity and accuracy (0.026 m/s mean absolute error). The ability to monitor to this accuracy with such low power draw and low cost is currently unprecedented in the industry.

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Section: Fundamentalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Measuring Air Speed With a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking

et al. 2019

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“…The maximum allowable symmetric phase difference is ±180°, which equates to ±12.5 µs time delay for a transducer frequency of 40 kHz. If a phase difference beyond this range is encountered the velocity reading will wraparound and, for example, a positive reading will then become negative [26]. To avoid this, a margin of around 50% above the maximum typical air velocity was used as the maximum measurable air velocity.…”

Section: Designmentioning

confidence: 99%

Development of an Ultrasonic Airflow Measurement Device for Ducted Air

Raine

Aslam

Underwood

et al. 2015

Sensors

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In this study, an in-duct ultrasonic airflow measurement device has been designed, developed and tested. The airflow measurement results for a small range of airflow velocities and temperatures show that the accuracy was better than 3.5% root mean square (RMS) when it was tested within a round or square duct compared to the in-line Venturi tube airflow meter used for reference. This proof of concept device has provided evidence that with further development it could be a low-cost alternative to pressure differential devices such as the orifice plate airflow meter for monitoring energy efficiency performance and reliability of ventilation systems. The design uses a number of techniques and design choices to provide solutions to lower the implementation cost of the device compared to traditional airflow meters. The design choices that were found to work well are the single sided transducer arrangement for a “V” shaped reflective path and the use of square wave transmitter pulses ending with the necessary 180° phase changed pulse train to suppress transducer ringing. The device is also designed so that it does not have to rely on high-speed analogue to digital converters (ADC) and intensive digital signal processing, so could be implemented using voltage comparators and low-cost microcontrollers.

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“…Ultrasound anemometers are also widely used in agriculture with nonmoving parts on sensor detectors [ 15 , 16 ]. The mechanical motion mechanism is nonexistent within system parts, so ultrasonic transducers have the ability to receive a high-pass signal with a high sampling rate from airflow or a low-pass signal after the calculation of data [ 17 , 18 ]. However, the use of a precise structure and expensive sensors will inevitably result in higher expenditure and maintenance costs, and the initial cost generally exceeds EUR 2 k [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Wind Speed Based on Schlieren Machine Vision System Inspired by Greenhouse Top Vent

Huang

Zhang

et al. 2023

Sensors

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Greenhouse ventilation has always been an important concern for agricultural workers. This paper aims to introduce a low-cost wind speed estimating method based on SURF (Speeded Up Robust Feature) feature matching and the schlieren technique for airflow mixing with large temperature differences and density differences like conditions on the vent of the greenhouse. The fluid motion is directly described by the pixel displacement through the fluid kinematics analysis. Combining the algorithm with the corresponding image morphology analysis and SURF feature matching algorithm, the schlieren image with feature points is used to match the changes in air flow images in adjacent frames to estimate the velocity from pixel change. Through experiments, this method is suitable for the speed estimation of turbulent or disturbed fluid images. When the supply air speed remains constant, the method in this article obtains 760 sets of effective feature matching point groups from 150 frames of video, and approximately 500 sets of effective feature matching point groups are within 0.1 difference of the theoretical dimensionless speed. Under the supply conditions of high-frequency wind speed changes and compared with the digital signal of fan speed and data from wind speed sensors, the trend of wind speed changes is basically in line with the actual changes. The estimation error of wind speed is basically within 10%, except when the wind speed supply suddenly stops or the wind speed is 0 m/s. This method involves the ability to estimate the wind speed of air mixing with different densities, but further research is still needed in terms of statistical methods and experimental equipment.

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Measurement range expansion of continuous wave ultrasonic anemometer

Cited by 11 publications

References 9 publications

Measuring Air Speed With a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking

Measuring Air Speed With a Low-Power MEMS Ultrasonic Anemometer via Adaptive Phase Tracking

Development of an Ultrasonic Airflow Measurement Device for Ducted Air

Estimation of Wind Speed Based on Schlieren Machine Vision System Inspired by Greenhouse Top Vent

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