Virtual Sensor Array for Air Discharge Gas Detection
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Solution Overview
Problem
Current gas sensor arrays for detecting NO2, CO, and O3 from air discharge in power facilities face issues of high power consumption, large size, complex structure, and limited feature extraction, leading to inefficient identification and high costs.
Innovation Solution
A virtual sensor array using pulse heating voltage and nanometer gas-sensitive materials, combined with a convolutional neural network for data-driven identification, reduces power consumption, array size, and enhances feature extraction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sensor array with multiple sensors of different sensitivities is constructed to solve cross-sensitivity issue, then gas detection capability is improved, but array size and device complexity increase
Solution Approach 1:
The patent divides a single physical sensor into multiple virtual sensing units by applying pulse heating voltages at different amplitudes. Each pulse amplitude creates a distinct temperature condition, generating a virtual sensor response that corresponds to a specific temperature point. This segmentation approach enables the system to obtain responses from multiple virtual sensors without requiring multiple physical sensors, thereby improving gas detection capability while keeping the physical array size small.
Solution Approach 2:
The patent introduces a temporal dimension by applying pulse heating voltages at different amplitudes sequentially. Instead of using multiple physical sensors spatially arranged, the system creates virtual sensors along the temperature dimension achieved through pulsed heating. This transforms the problem from a spatial array to a temporal sequence of measurements, reducing physical complexity while maintaining detection capability.
2Reliability
If constant heating voltage is applied to sensors to reach operating temperature, then sensor operation is maintained, but power consumption increases
Solution Approach 1:
The patent replaces constant heating voltage with periodic pulse heating voltages. The heating element receives voltage in periodic pulses rather than continuously, allowing the sensor to be heated to operating temperature only when needed for measurement. Between pulses, the heating element can cool down, significantly reducing average power consumption while maintaining the ability to reach operating temperature for reliable sensor operation during measurement periods.
3Ease of operation
If traditional identification algorithms use only response values as feature input, then processing is simple, but identification precision is limited due to loss of information
Solution Approach 1:
The patent introduces a convolutional neural network as an intermediary between the raw sensor response data and the final gas concentration identification. The CNN automatically extracts relevant features from the response curves, transforming the raw data into meaningful feature representations. This intermediary processing layer preserves information that would be lost in traditional algorithms while automating the feature extraction process, thereby improving identification precision without requiring manual feature engineering.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method significantly reduces power consumption, decreases device bulk, and improves identification accuracy by extracting more response information from the sensor array, enabling efficient online monitoring of air discharge decomposed products.
Implementation Method 1
a front-side testing electrode 1 and a back-side heating electrode 4 are arranged in a brush-crossing mode... different nanometer gas-sensitive materials are uniformly applied to surfaces of the front-side testing electrode 1... sensing principles based on resistance changes
Implementation Method 2
a pulse heating voltage is applied to the sensor array to form the virtual sensor array... addressing the issue of high power consumption of traditional gas sensor arrays
Data Source
AI summary
Embodiments of the present disclosure relate to a method for detecting an air discharge decomposed product based on a virtual sensor array, comprising: fabricating a virtual sensor array; disposing the virtual sensor array in a hermetically sealed gas chamber, energizing, and initializing; performing gas-sensitive testing to the virtual sensor array and storing a testing result as samples to store; and building a convolutional neural network model diagram for identifying contents of gas components, and identifying an atmosphere. The virtual sensor array fabricated by the present disclosure may reduce the array size and the overall volume of a device to an extreme content; the built convolutional neural network may dig other feature information besides a response value from a response curve of a sensor, thereby effectively improving identification efficiency and identification accuracy.