- Acoustic virtual temperature
- Arithmetic mean value
- Damping coefficient
- Damping ratio
- Delay distance
- Detection limit
- Gliding mean value
- Gray-code
- Orthogonal wind velocity vector
- Microturbulence / Effect on Measurement Signal
- Scalar wind velocity
- Serial-synchron. output
- Spatial Path Averaging
- Starting value
- Stress
- Variation
- Vectorial mean value
- Vectorial mean value with standard vectors
- Wind direction
- Wind force
- Wind run
- Wind speed
- 8-bit wind direction Gray-code
Acoustic virtual temperature
The acoustic virtual temperature is the air temperature referred to dry air without any portion of water vapour.
It is acquired by propagation measurements of sonic pulses. After respective correction of the humidity influence the procedure exceeds the accuracy of the classic procedures of the temperature measurement in a weather and thermal radiation shield.
It is acquired by propagation measurements of sonic pulses. After respective correction of the humidity influence the procedure exceeds the accuracy of the classic procedures of the temperature measurement in a weather and thermal radiation shield.
Damping coefficient
The damping coefficient characterises the oscillations of the wind vane. It is an important characteristic quantity for the qualitative evaluation of the wind vane. The damping coefficient is determined from the amplitudes of two successive excursions and is calculated by means of an equation.
Gray-code
One-increment binary code, on the changeover of one value to the next one only one single data bit modifies each to the previous and the next value respectively. The Gray-code is used for the digital determination of distances, for ex. the wind direction of a wind vane.
The code can be set up by means of any number of digits, it depends only on the required accuracy of resolution.
The code can be set up by means of any number of digits, it depends only on the required accuracy of resolution.
Orthogonal wind velocity vector
A straight line standing vertically to another straight line. By arranging two measurement distances standing vertically on each others you achieve the amount and angle of the wind velocity vector in the form of rectangular components. After measurement of the rectangular wind velocity components the amount and angle of the wind velocity can be calculated.
Microturbulence / Effect on Measurement Signal
Microturbulence consists of small, rapid fluctuations in the airflow. It occurs primarily near obstacles, in the wake of wind turbines, near the ground, or in flow fields influenced by certain structures. Unlike large-scale wind changes, microturbulence is locally confined and can vary significantly over short distances and time periods. Wind measurement systems capable of precisely detecting and resolving such local fluctuations can produce highly variable signals in the presence of microturbulence.
Microturbulence also affects measurements taken by ultrasonic wind sensors. The extent of this effect depends on the length of the measurement path. The shorter the measurement path, the greater the impact of local flow changes on the output signal. In the nacelle control of wind turbines, microturbulence can lead to short-term directional fluctuations that do not always reflect the average flow direction. This can influence the control behavior.
Connection to the Spatial Path Averaging Method:
The effect of microturbulence can be reduced using the principle of spatial path averaging. In this method, multiple flow components along a defined measurement path are recorded and averaged.
Microturbulence also affects measurements taken by ultrasonic wind sensors. The extent of this effect depends on the length of the measurement path. The shorter the measurement path, the greater the impact of local flow changes on the output signal. In the nacelle control of wind turbines, microturbulence can lead to short-term directional fluctuations that do not always reflect the average flow direction. This can influence the control behavior.
Connection to the Spatial Path Averaging Method:
The effect of microturbulence can be reduced using the principle of spatial path averaging. In this method, multiple flow components along a defined measurement path are recorded and averaged.
Spatial Path Averaging
Spatial Path Averaging is a physical measurement principle used in ultrasonic wind measurement. Instead of measuring the flow at a single point, it integrates the flow along a defined measurement path. Instead of using just a single measurement point in the flow, the wind is measured along a spatial path. This results in an averaged measurement value that takes into account multiple local flow components. This is particularly important for large wind turbines, where the air is often highly turbulent. In this case, large-scale wind movements overlap with small-scale turbulence structures and wake effects.
Influence of the Measurement Path Length:
The effectiveness of spatial path averaging depends significantly on the length of the measurement path.
• Short measurement paths:
greater sensitivity to local microturbulence and short-term fluctuations
• Longer measurement paths:
greater spatial integration of multiple flow components → more stable output signal
Significance for wind measurement:
Spatial averaging can improve the representativeness of the measurement signal. This contributes to a more stable measurement of the average wind direction, particularly in applications such as the yaw control of wind turbines.
Application in ultrasonic wind sensors:
In ultrasonic wind sensors, spatial path averaging is achieved through the geometric design of the measurement path.
Influence of the Measurement Path Length:
The effectiveness of spatial path averaging depends significantly on the length of the measurement path.
• Short measurement paths:
greater sensitivity to local microturbulence and short-term fluctuations
• Longer measurement paths:
greater spatial integration of multiple flow components → more stable output signal
Significance for wind measurement:
Spatial averaging can improve the representativeness of the measurement signal. This contributes to a more stable measurement of the average wind direction, particularly in applications such as the yaw control of wind turbines.
Application in ultrasonic wind sensors:
In ultrasonic wind sensors, spatial path averaging is achieved through the geometric design of the measurement path.
8-bit wind direction Gray-code
The wind direction (0 … 360 °) is converted into an 8-bit Gray code (Thies special) and transmitted. The resolution is 2.5 °, 144 increments per revolution.
Increment 0 = 0 ° = North and corresponds to the sector 0 … 2.5 °
Increment 143 = 357.5 ° corresponds to the sector 357.5 … 0 °.
Increment 0 = 0 ° = North and corresponds to the sector 0 … 2.5 °
Increment 143 = 357.5 ° corresponds to the sector 357.5 … 0 °.
