PLC Device Noise Signal Appliance Identification
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Solution Overview
Problem
Current electric appliance identification methods based on smart meter data become inefficient as the number of appliances increases, leading to exponential feature combinations and high maintenance costs for Power Line Communication (PLC) devices affected by electromagnetic interference.
Innovation Solution
A method and apparatus where a PLC device directly collects noise signals from the circuit, extracts time-frequency features, and uses an electric appliance identification model to identify interfering appliances without additional devices, continuously improving the model's accuracy through server training with received data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If smart meter data with multiple feature combinations is used to identify electric appliances, then identification capability is improved, but system complexity increases exponentially as the number of appliances increases
Solution Approach 1:
The patent extracts only the necessary time-frequency features from noise signals generated by electric appliances, rather than analyzing all possible feature combinations. By focusing on specific temporal and spectral characteristics of the noise, the system achieves effective appliance identification without the exponential complexity growth associated with comprehensive feature analysis.
Solution Approach 2:
The patent transforms the identification approach by changing from analyzing multiple appliance features to analyzing the time-frequency parameters of noise signals. This parameter transformation converts a high-dimensional feature combination problem into a more manageable time-frequency analysis problem, reducing system complexity while maintaining identification capability.
2Measurement precision
If comprehensive smart meter monitoring is implemented to identify all electric appliances, then identification accuracy is improved, but maintenance costs increase due to system complexity
Solution Approach 1:
The patent converts the harmful electromagnetic interference (noise) generated by electric appliances into a useful identification signal. By analyzing the time-frequency characteristics of this noise, the system achieves accurate appliance identification without requiring complex monitoring infrastructure, thereby reducing maintenance costs while improving identification accuracy.
Solution Approach 2:
The system uses the appliances' own operational characteristics (noise signals) for identification purposes, eliminating the need for additional monitoring devices or complex smart meter systems. This self-service approach reduces system complexity and maintenance requirements while maintaining high identification accuracy.
3Measurement precision
If additional devices like smart meters are deployed to improve appliance identification, then measurement capability is improved, but device complexity and cost increase
Solution Approach 1:
The PLC device performs appliance identification using its own existing noise signal collection capability, without requiring additional smart meters or monitoring devices. The device leverages the noise signals naturally present in the power line to extract time-frequency features for identification, eliminating the need for extra hardware while maintaining measurement capability.
Solution Approach 2:
The PLC device is designed to perform multiple functions: power line communication and appliance identification. By integrating the identification functionality into the existing PLC device that already collects noise signals for communication purposes, the system avoids adding separate monitoring devices, thereby reducing overall system complexity while enhancing measurement capability.
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
This approach reduces maintenance costs by efficiently identifying interfering appliances using noise signals, improving communication quality without the need for additional devices like smart meters, and enhances accuracy through continuous model training.
Implementation Method 1
The electric appliance in the circuit generates electromagnetic interference (namely, a noise signal) in a use process
Data Source
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Figure 3~4(b)
Figure 4(c)
AI summary
An electric appliance identification method and apparatus are provided. The method includes: A PLC device obtains a noise signal in a circuit. The PLC device obtains first data based on the noise signal, where the first data is used to describe a time-frequency feature of the noise signal. The PLC device obtains, based on an electric appliance identification model and the first data, an electric appliance identification result corresponding to the noise signal, where the electric appliance identification model is obtained based on a signal including a noise signal of at least one known electric appliance. In this way, without using an additional device, for example, a smart meter, the PLC device is directly configured to collect the noise signal, extract the time-frequency feature of the noise signal as the first data, and identify an electric appliance with severe interference to a line based on the electric appliance identification model.