Sensor Signal Quality Improvement with Decoupled Noise Sensing
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Solution Overview
Problem
Existing sensor data for low-voltage motors in industrial environments are adversely affected by environmental noise, leading to inaccurate measurements and false alarms due to high background noise levels, which current noise reduction methods either fail to address effectively or introduce additional complexity and costs.
Innovation Solution
A computer-implemented method using environmentally coupled and decoupled sensing means to estimate background noise, allowing direct measurement and reduction of noise through a correlation function, utilizing a processor to process data from both types of sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are used to eliminate ambient interference, then measurement accuracy is improved, but system complexity and configuration requirements increase
Solution Approach 1:
The sensor system is segmented into two functional groups: sensors environmentally coupled to the technical device (first group) and sensors environmentally decoupled from the technical device (second group). This segmentation allows independent processing of device-specific signals and ambient noise, resolving the contradiction by organizing multiple sensors into distinct functional segments that can be processed separately.
Solution Approach 2:
The invention extracts ambient noise characteristics from the second group of sensors that are environmentally decoupled from the technical device. By taking out the ambient interference component separately, the system can remove it from the first group's measurements without requiring complex inter-sensor coordination, thus reducing system complexity while maintaining measurement accuracy.
2Object-affected harmful factors
If statistical methods are used to eliminate noise in cloud applications, then background noise is reduced, but measurement accuracy is lost due to false alarms and suppressed anomalies
Solution Approach 1:
The second group of sensors acts as an intermediary that measures ambient noise independently without being directly coupled to the technical device. This intermediary measurement allows the system to subtract ambient noise from the first group's measurements while preserving true device anomalies, avoiding the false alarms and suppressed anomalies caused by direct statistical processing of combined signals.
Solution Approach 2:
The system performs preliminary measurement of ambient noise characteristics using the second group of sensors before processing the device measurements. By anticipating and characterizing the ambient interference in advance, the system can apply targeted noise reduction that preserves measurement accuracy rather than applying blanket statistical methods that cause false alarms.
3Productivity
If low-voltage motors operate in industrial environments, then production functionality is maintained, but sensor measurements are degraded by vibration, temperature and magnetic field interference
Solution Approach 1:
The invention applies local quality by placing sensors in different environmental contexts: the first group of sensors is locally coupled to the technical device to capture device-specific signals, while the second group is locally decoupled to capture only ambient noise. This local differentiation allows each sensor group to optimize for its specific measurement target, maintaining productivity while improving measurement precision.
Solution Approach 2:
The second group of sensors creates a copy of the ambient noise environment without the device-specific signals. This noise copy can then be subtracted from the first group's measurements to eliminate vibration, temperature, and magnetic field interference while preserving the actual device operation data, thus maintaining productivity with improved measurement quality.
Data Source
AI summary
Computer-implemented method for improving the signal quality of a first sensor data (SD1), wherein the first sensor data (SD1) is captured by a first sensing means (SM1), which is environmentally coupled to a first technical device (D1), and at least one second sensor data (SD2-SD5) is captured by at least one second sensing means (SM2-SM5), wherein the at least one second sensing means (SM2-SM5) is environmentally decoupled from the first technical device (D1), and a correlation function is calculated by a processor (CPU) with a memory, which is connected with the first and the at least one second sensing means (SM1-SMS), using the first and the at least one second sensor data (SD1-SDS) to estimate the background noise (BN), to which background noise (BN) the first and the at least one second sensing means (SM1-SMS) are exposed simultaneously, and the correlation function is used to reduce the background noise (BN) of the first sensor data (SD1).