Augmented Mesh Delivery System for Signal Reconstruction
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Solution Overview
Problem
Mesh telemetry systems face challenges in delivering data with variable transport delays and signal sample loss, which degrades the quality of uniformly sampled time series signals and prevents full reconstruction of lost information.
Innovation Solution
A method involving a controller that receives signal samples and associated sampling time indications, applies a compacting algorithm, transforms the signal into a discrete Fourier spectrum, filters it in the frequency domain, and performs an inverse discrete Fourier transform to generate a uniformly sampled recovered signal, allowing for adjustments to electricity supply characteristics based on the recovered signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If signal samples are transmitted through a mesh telemetry system, then data delivery is achieved, but variable transport delays and signal sample loss occur degrading signal quality
Solution Approach 1:
The system performs preliminary actions by capturing timing information (timestamps) alongside signal samples at the source node before transmission. This timing data is preserved through the mesh network and used later for signal reconstruction, allowing the system to compensate for delays and losses without requiring real-time synchronization or perfect signal delivery.
Solution Approach 2:
The patent introduces an intermediary reconstruction process at the destination node that acts as a mediator between the imperfect received signal and the required uniform time series output. This intermediary step uses the timing information and signal samples to mathematically reconstruct what the signal would look like under uniform sampling conditions, effectively bridging the gap between mesh network limitations and signal processing requirements.
2Productivity
If signal samples are delivered with variable delays through mesh network, then data transmission is achieved, but uniformly sampled time series signal quality is degraded
Solution Approach 1:
The system captures and preserves timing information (timestamps) as a preliminary action at the source node. This timing data is embedded with the signal samples and transported through the mesh network, serving as a foundation for later reconstruction. By having this timing information available in advance, the system can compensate for variable delays and reconstruct uniform sampling without sacrificing transmission efficiency.
Solution Approach 2:
The patent applies parameter changes by transforming the signal from the time domain to the frequency domain using Fast Fourier Transform (FFT). This transformation changes the representation parameters of the signal, allowing the system to work with frequency components that are less sensitive to timing variations. After filtering in the frequency domain, the inverse FFT transforms the signal back to the time domain, producing uniformly sampled output despite variable transmission delays.
3Productivity
If signal samples are lost during transmission, then data delivery continues, but lost information cannot be fully reconstructed
Solution Approach 1:
The system implements feedback by using the timing information (timestamps) associated with each signal sample to track and identify lost or delayed samples during reconstruction. This feedback mechanism allows the reconstruction algorithm to aware of gaps in the data and apply appropriate interpolation or estimation techniques, improving the ability to recover lost information while maintaining data delivery continuity.
Solution Approach 2:
The patent transforms the signal into the frequency domain using FFT, which changes the parameter representation from time-domain samples to frequency-domain components. This transformation enables better handling of lost information because frequency components can be reconstructed from incomplete time-domain samples through spectral analysis and filtering. The inverse FFT then transforms the processed frequency data back to the time domain, producing a complete uniform time series even when original samples were lost during transmission.
4Loss of information
If signal reconstruction is performed to compensate for losses, then information completeness is improved, but processing complexity increases
Solution Approach 1:
The patent uses parameter changes by applying Fast Fourier Transform (FFT) to convert the signal from the time domain to the frequency domain. This transformation simplifies the reconstruction process by allowing standard filtering operations in the frequency domain, which are computationally more efficient than time-domain convolution methods. The inverse FFT then transforms the processed frequency data back to the time domain, producing uniformly sampled output. This approach reduces processing complexity compared to direct time-domain interpolation methods.
Data Source
AI summary
A method is disclosed including receiving with a controller at a destination node signal samples and associated sampling time indications. The signal samples and the associated sampling time indications are received from a source node via a mesh network. The signal samples are delivered with sampling time indications generated at the source node to form a series of signals corresponding to one or more characteristic(s) related to electricity supplied to one or more electrical devices from a power source. The method also includes applying a time domain convolution procedure to the received signal in the time domain that is uniformly sampled. The weighting of sample values in time domain convolution procedure is determined at least partially based on information indicative of the statistical behavior of a corresponding realized sample process.