Dequantizing low-resolution IoT signals to produce high-accuracy prognostic indicators
First Claim
1. A method for removing quantization effects from a set of time-series signals to produce highly accurate approximations of a set of original unquantized signals, comprising:
- receiving the set of time-series signals from a monitored system, wherein each signal comprises a sequence of quantized values that were sampled from an original signal generated by the monitored system;
for each time-series signal in the set of time-series signals,determining a number of quantization levels (NQL) in the time-series signal;
performing a fast Fourier transform (FFT) on the time-series signal to produce a set of Fourier modes for the time-series signal;
determining an optimal number of Fourier modes (Nmode) to reconstruct the time-series signal based on the determined NQL for the time-series signal;
selecting Nmode largest-amplitude Fourier modes from the set of Fourier modes for the time-series signal; and
performing an inverse FFT operation using the Nmode largest-amplitude Fourier modes to produce a dequantized time-series signal to be used in place of the time-series signal;
analyzing the dequantized time-series signals using a prognostic-surveillance system to detect incipient anomalies that arise during execution of the monitored system; and
when the prognostic-surveillance system detects an anomaly, generating an alarm.
1 Assignment
0 Petitions
Accused Products
Abstract
The disclosed embodiments relate to a system that removes quantization effects from a set of time-series signals to produce highly accurate approximations of a set of original unquantized signals. During operation, for each time-series signal in the set of time-series signals, the system determines a number of quantization levels (NQL) in the time-series signal. Next, the system performs a fast Fourier transform (FFT) on the time-series signal to produce a set of Fourier modes for the time-series signal. The system then determines an optimal number of Fourier modes (Nmode) to reconstruct the time-series signal based on the determined NQL for the time-series signal. Next, the system selects Nmode largest-amplitude Fourier modes from the set of Fourier modes for the time-series signal. The system then performs an inverse FFT operation using the Nmode largest-amplitude Fourier modes to produce a dequantized time-series signal to be used in place of the time-series signal.
-
Citations
14 Claims
-
1. A method for removing quantization effects from a set of time-series signals to produce highly accurate approximations of a set of original unquantized signals, comprising:
-
receiving the set of time-series signals from a monitored system, wherein each signal comprises a sequence of quantized values that were sampled from an original signal generated by the monitored system; for each time-series signal in the set of time-series signals, determining a number of quantization levels (NQL) in the time-series signal; performing a fast Fourier transform (FFT) on the time-series signal to produce a set of Fourier modes for the time-series signal; determining an optimal number of Fourier modes (Nmode) to reconstruct the time-series signal based on the determined NQL for the time-series signal;
selecting Nmode largest-amplitude Fourier modes from the set of Fourier modes for the time-series signal; andperforming an inverse FFT operation using the Nmode largest-amplitude Fourier modes to produce a dequantized time-series signal to be used in place of the time-series signal; analyzing the dequantized time-series signals using a prognostic-surveillance system to detect incipient anomalies that arise during execution of the monitored system; and when the prognostic-surveillance system detects an anomaly, generating an alarm. - View Dependent Claims (2, 3, 4, 5, 6, 7)
-
-
8. A system that removes quantization effects from a set of time-series signals to produce highly accurate approximations of a set of original unquantized signals, comprising:
-
at least one processor and at least one associated memory; a dequantization mechanism that executes on the at least one processor, wherein during operation, the dequantization mechanism; receives the set of time-series signals from a monitored system, wherein each signal comprises a sequence of quantized values that were sampled from an original signal generated by the monitored system; for each time-series signal in the set of time-series signals, determines a number of quantization levels (NQL) in the time-series signal; performs a fast Fourier transform (FFT) on the time-series signal to produce a set of Fourier modes for the time-series signal; determines an optimal number of Fourier modes (Nmode) to reconstruct the time-series signal based on the determined NQL for the time-series signal; selects Nmode largest-amplitude Fourier modes from the set of Fourier modes for the time-series signal; and
performs an inverse FFT operation using the Nmode largest-amplitude Fourier modes to produce a dequantized time-series signal to be used in place of the time-series signal; anda prognostic-surveillance mechanism that executes on the at least one processor, wherein during operation, the prognostic-surveillance mechanism; analyzes the dequantized time-series signals using a prognostic-surveillance system to detect incipient anomalies that arise during execution of the monitored system; and when the prognostic-surveillance system detects an anomaly, generates an alarm. - View Dependent Claims (9, 10, 11, 12, 13)
-
-
14. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for removing quantization effects from a set of time-series signals to produce highly accurate approximations of a set of original unquantized signals, the method comprising:
-
receiving the set of time-series signals from a monitored system, wherein each signal comprises a sequence of quantized values that were sampled from an original signal generated by the monitored system; for each time-series signal in the set of time-series signals, determining a number of quantization levels (NQL) in the 11 time-series signal; performing a fast Fourier transform (FFT) on the time-series signal to produce a set of Fourier modes for the time-series signal; determining an optimal number of Fourier modes (Nmode) to reconstruct the time-series signal based on the determined NQL for the time-series signal; selecting Nmode largest-amplitude Fourier modes from the set of Fourier modes for the time-series signal; and performing an inverse FFT operation using the Nmode largest-amplitude Fourier modes to produce a dequantized time-series signal to be used in place of the time-series signal; analyzing the dequantized time-series signals using a prognostic-surveillance system to detect incipient anomalies that arise during execution of the monitored system; and when the prognostic-surveillance system detects an anomaly, generating an alarm.
-
Specification