Offset Sampling for Coin Authentication
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Solution Overview
Problem
Existing electronic transaction systems face challenges in accurately classifying items of value due to high computational complexity and noise introduced by time and frequency domain techniques, which are sensitive to variations and introduce quantization noise and aliasing, making them costly and complex.
Innovation Solution
The implementation of an offset sampling method that samples signals at a frequency offset from the fundamental frequency, reducing aliasing errors and allowing for classification using frequency domain signals, which are then processed with lower-order filters to achieve accurate authentication and recognition of items like coins and banknotes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time domain techniques are used to model sensor output signals, then measurement sensitivity is improved, but computational complexity and quantization noise increase
Solution Approach 1:
The patent replaces complex time domain computational processing with a simplified frequency domain approach. By transforming the signal processing from time domain to frequency domain, the system achieves comparable measurement sensitivity with significantly reduced computational complexity and quantization noise, effectively substituting a complex mechanical/computational system with a simpler alternative.
2Measurement precision
If sampling rate is increased above Nyquist rate to reduce quantization noise, then measurement precision is improved, but system complexity and cost increase
Solution Approach 1:
The patent changes the sampling parameter by introducing an offset to the sampling frequency, sampling at frequencies that are offset from integer multiples of the fundamental frequency. This parameter change allows the system to achieve reduced quantization noise and aliasing without requiring excessively high sampling rates, thereby maintaining lower system complexity and cost while improving measurement precision.
3Measurement precision
If high order anti-aliasing filters are used to reduce quantization noise, then measurement precision is improved, but system cost and complexity increase
Solution Approach 1:
The patent changes the sampling frequency parameter to be offset from integer multiples of the fundamental frequency, which naturally pushes aliasing components to frequencies where they do not overlap with the signal band. This parameter change eliminates the need for high-order anti-aliasing filters, reducing both system cost and complexity while maintaining measurement precision.
4Measurement precision
If frequency domain techniques are used to determine signal properties, then aliasing errors are reduced, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by performing an offset sampling transformation before full frequency domain analysis. By sampling at offset frequencies first, the system pre-reduces aliasing errors in the sampled signal, which then simplifies subsequent frequency domain processing. This preliminary step reduces the computational burden of frequency domain techniques while maintaining their aliasing reduction benefits.
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 the complexity and cost of systems by minimizing aliasing errors and noise, enabling accurate classification of items of value with lower-order filters, thus improving the efficiency and reliability of electronic transaction systems.
Implementation Method 1
Electromagnetic sensors, for example, are operated to induce eddy currents in a coin, and obtain a response of how the magnetic field varies due to the presence of a coin
Implementation Method 2
Electromagnetic sensors, for example, are operated to induce eddy currents in a coin
Data Source
AI summary
A handling apparatus comprising an offset sampling module and a digital processing module is described herein. The offset sampling module is configured to provide a sampled signal by sampling at least one signal at a sampling frequency that is offset from a fundamental frequency of the signal by an offset factor; and the digital processing module configured to convert the sampled signal into a frequency domain signal. The handling apparatus further includes an authentication module to determine at least one characteristic property based at least on the frequency domain signal; and to classify the inserted item of value based on the determination.