To determine whether the measurement accuracy of a noise sensor has decreased, the core is to verify whether the deviation between its output data and the true noise level exceeds the allowable range through three methods: standard signal calibration, comparative testing, and data consistency analysis.
1、 Core judgment method: from calibration to actual measurement verification
1.standardRegular calibration using standard sound sources
This is the fundamental method for determining the decrease in accuracy, which verifies the response accuracy of the sensor through a standard signal with known sound pressure levels.
Operation steps: Place the sensor in an anechoic or semi anechoic chamber and use a sound level calibrator (such as a 1kHz, 94dB, or 114dB standard sound source) to closely adhere to the sensor pickup head.
Judgment criteria: If the deviation between the sensor display value and the calibrator standard value exceeds ± 0.5dB (usually allowed range for industrial grade sensors), it indicates that the accuracy may have decreased; When the deviation exceeds ± 1dB, immediate maintenance or replacement is required.
Attention: The calibration cycle should follow the equipment requirements, generally once every 6-12 months in industrial scenarios, and shortened to 3-6 months in harsh environments such as high temperature, high humidity, and high dust.
2. Most direct: comparative testing with high-precision sensors of the same model
By using "same platform comparison" to eliminate environmental interference, data deviations can be intuitively discovered.
Operation steps: Place the sensor to be tested side by side with a standard calibrated "reference sensor" (with a distance of no more than 1 meter), and continuously collect data for 10-30 minutes in the same noise environment (such as stable equipment operation noise, constant environmental noise).
Judgment criteria: If the real-time sound pressure level difference between the two (such as Leq equivalent continuous sound level) continues to exceed ± 1dB, or the peak sound pressure level difference exceeds ± 2dB, it indicates that the accuracy of the sensor to be tested may decrease.
Applicable scenario: When there is no standard calibrator on site, it can quickly and preliminarily determine accuracy issues.
3. Daily routine: Analyze the stability and rationality of long-term data
By analyzing the trends and logic of historical data, hidden precision biases can be identified.
Data stability check: Collect data continuously for 24 hours in the same stable environment (such as an empty factory without equipment start stop). If the irregular fluctuation amplitude of the data exceeds ± 0.8dB (excluding interference from airflow, vibration, etc.), it may be due to sensor sensitivity drift.
Logical rationality judgment: Verify data based on actual scenarios, for example, if the noise level of the device is known to be 85dB during operation, and the sensor displays 78dB or 92dB (excluding equipment faults and changes in measurement distance), it indicates abnormal accuracy; The environmental noise should be lower at night than during the day. If the data is reversed or there is no difference, it may also be due to a decrease in accuracy.
2、 Auxiliary judgment: Investigate potential problems from hardware status
Hardware damage or aging of sensors is a common cause of decreased accuracy, which can be assisted by visual and functional inspections.
Appearance inspection: Check if the pickup head (microphone) is clogged with dust, damaged, shows signs of water ingress, or if the connecting wires are loose or the insulation layer is aging. These issues can lead to a decrease in pickup sensitivity, directly affecting measurement accuracy.
Function button test: Check if the sensor's functions such as "reset" and "mode switching" (such as A weighting and C weighting) are normal. If the function fails, it may be accompanied by internal circuit faults, indirectly leading to inaccurate data.
Environmental adaptability verification: If the sensor is labeled with a working temperature of "-20 ℃~60 ℃", it needs to be recalibrated after use in environments beyond this range; If exposed to high humidity (RH>85%) for a long time, accuracy drift may occur due to moisture in internal components.
3、 Key precautions
To avoid misjudgment: If the decrease in measurement accuracy ≠ data fluctuation, external interference (such as airflow impact, vibration transmission, electromagnetic interference near the sensor) needs to be eliminated before making accuracy judgments.
Priority treatment: If used for compliance monitoring (such as factory noise emissions, environmental noise compliance testing), sensors with decreased accuracy should be immediately stopped to avoid compliance risks caused by data errors.