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Engineering Terms (Chinese-English Bilingual Version)
Sensor sensitivity refers to how much a sensor's output changes in response to a change in the measured quantity. It is often represented as a ratio, such as volts per degree Celsius for temperature sensors.
Higher sensitivity means the sensor can detect smaller changes in the measured quantity. For example, a highly sensitive pressure sensor will produce a significant output shift even with minor pressure changes.
Example: In a pressure transducer, the sensitivity might be expressed as the change in output (in volts or mA) per unit of pressure (psi or bar). If a pressure sensor has a sensitivity of 0.1 V/psi, each psi change in pressure would alter the output by 0.1 volts.
2. Accuracy
The accuracy of a sensor measures how close a sensor’s output is to the true value of the quantity being measured.
It is typically expressed as a percentage of the sensor's full-scale range or as an absolute error. High accuracy is crucial in applications where precise measurements are necessary, like in medical devices or scientific research.
Example: A temperature sensor with an accuracy of ±1°C can provide readings that deviate by up to 1°C from the actual temperature, within its specified range.
3. Precision
Precision, also called repeatability, is the sensor's ability to produce the same reading when measuring a constant input multiple time.
Unlike accuracy, precision does not indicate closeness to the true value but rather the consistency of repeated measurements. Precision is critical when consistent readings are more important than perfectly accurate readings, such as in relative humidity sensors for trend analysis.
Example: A pressure sensor with a precision of ±0.2% will provide readings that vary by no more than 0.2% each time it measures the same pressure level.
4. Resolution
Resolution is the smallest change in the measured quantity that the sensor can detect. This metric is typically determined by the sensor’s design and the limitations of its signal processing circuitry.
Higher resolution enables the detection of fine changes in the measured quantity, which is crucial for applications like image processing or position sensing.
Example: A temperature sensor with a resolution of 0.01°C can detect temperature changes as small as 0.01°C.
5. Linearity
Linearity describes how closely the sensor’s output follows a straight line over its measurement range.
If a sensor is perfectly linear, any change in the input should result in a proportional change in output. Non-linearity can lead to measurement errors, especially when measurements are taken near the sensor's upper or lower range.
Example: If a sensor measuring force outputs a 1V change for every 10N applied, its response is linear if this relationship holds across the sensor's range.
6. Range
Range, or full-scale range, indicates the maximum and minimum values the sensor can measure.
The range is essential to ensure the sensor can handle the anticipated measurement extremes. Selecting a sensor with an appropriate range prevents overloading, saturation, or inadequate resolution in the expected measurement environment.
Example: A strain gauge with a range of 0 to 500 psi can accurately measure pressure up to 500 psi without distortion or loss of accuracy.
7. Offset
Offset is a baseline shift in the sensor output when the measured quantity is zero. Ideally, a sensor should output zero when the input is zero, but manufacturing imperfections may cause a slight offset.
Understanding offset is necessary for calibrating the sensor accurately and for compensating in applications where precise zero-point measurements are required.
Example: A load cell may have an offset of 0.05 volts, meaning that even with no load, the output signal starts at 0.05 volts.
8. Hysteresis
Hysteresis is the sensor’s tendency to provide different outputs for the same input depending on the input's prior values.
This means the sensor may exhibit "memory" of past measurements. Hysteresis can lead to inconsistent readings, especially in applications where the input fluctuates around a specific value. It is vital in temperature sensors used in HVAC systems.
Example: A pressure sensor with a hysteresis error may show different readings if the pressure increased to a set point versus if it decreased to that same set point.
9. Response Time
Response time is the time it takes for a sensor to respond to a change in the measured quantity and reach a stable output.
Fast response time is essential in applications that require real-time monitoring, like gas detection or dynamic force measurement.
Example: A temperature sensor in a climate control system may have a response time of 2 seconds, meaning it takes this long to reflect temperature changes accurately.
10. Drift
Drift is the gradual change in a sensor's output when the input remains constant. It often results from factors like temperature changes or component aging.
Drift is crucial in long-term applications such as environmental monitoring, where accurate measurements over time are required without frequent recalibration.
Example: A humidity sensor might show a 1% increase in output each year due to drift, which would need correction for accurate long-term use.
11. Noise
Noise refers to random fluctuations in the sensor’s output that are not caused by changes in the measured quantity. It is typically caused by electrical interference or thermal fluctuations.
Low noise levels are essential for applications that require high accuracy and stability, such as laboratory measurements.
Example: A pressure transducer with 0.01V of noise may require additional filtering to ensure reliable readings.
12. Sensitivity Error
Sensitivity error occurs when a sensor’s sensitivity deviates from its specified value.
This means the output may be slightly higher or lower than expected based on the input change. Minimizing sensitivity error is crucial for applications that depend on precise scaling of measurements.
Example: If a sensor with a rated sensitivity of 1V/psi shows 1.02V/psi, it has a sensitivity error, which may need correction in post-processing.
13.NIST – National Institute of Standard and Technology:
A metrology laboratory and non-regulatory agency of the United States Department of Commerce. Sensors with “NIST Traceable” calibration have an unbroken chain of measurements leading back to standards maintained by NIST.
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