Equivalent Time Sampling for High-Resolution Sensor Data Reconstruction
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Solution Overview
Problem
Existing sensor data acquisition systems in complex systems like automobiles often cannot provide high enough sampling rates to accurately characterize rapid changes in parameters, such as cylinder pressure, due to limitations in sensors and analog-to-digital converters, making it impractical and costly to increase sampling rates across all sensors.
Innovation Solution
The method of Equivalent Time Sampling is used to improve the effective sampling rate of sensor data by constructing high-resolution data sets from existing low-sampling-rate sensors, which are then used in system models for accurate estimation and control, enabling fault diagnosis and control applications without the need for high-sampling-rate sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sampling rate of sensor data acquisition systems is increased to accurately characterize rapid changes in parameters, then measurement precision is improved, but device complexity and cost increase due to the need for high-sampling-rate sensors and analog-to-digital converters
Solution Approach 1:
The patent creates a virtual copy of the high-sampling-rate sensor signal by synthesizing it from lower-sampling-rate measurements using an equivalent time sampling model. Instead of physically sampling at high rates, the system reconstructs what the high-rate signal would look like based on the mathematical model of the measured parameter, thereby achieving high measurement precision without the complexity of high-speed hardware
Solution Approach 2:
The patent introduces a mathematical model as an intermediary between the low-sampling-rate sensor and the high-resolution diagnostic requirements. This model acts as a mediator that transforms the limited sensor data into high-resolution equivalent time samples, resolving the contradiction between measurement precision and device complexity
2Measurement precision
If the sampling rate of all sensor data acquisition systems is increased to meet diagnostic and control requirements, then measurement precision is improved, but cost increases due to the large number of sensors and high-sampling-rate circuitry required
Solution Approach 1:
The patent makes the low-sampling-rate sensor perform multiple functions: it not only provides direct measurement data but also serves as the basis for generating high-resolution equivalent time samples through the mathematical model. This multi-functionality allows a single low-rate sensor to replace what would otherwise require multiple high-rate sensors, reducing the quantity of hardware needed
3Device complexity
If existing low-sampling-rate sensors are used without data manipulation, then device complexity is reduced, but measurement precision is insufficient to accurately characterize rapid parameter changes
Solution Approach 1:
The patent performs preliminary data manipulation by pre-processing the low-sampling-rate sensor data through the equivalent time sampling model before the data is used for diagnostic and control purposes. This preliminary transformation of the data into high-resolution format occurs in advance, allowing the simple hardware to effectively provide high-precision measurements when needed
Data Source
AI summary
A method and system for using Equivalent Time Sampling to improve the effective sampling rate of sensor data, and using the improved-resolution data for diagnosis and control. Data samples from existing sensors are provided, where the sampling rate of the existing sensors is not sufficient to accurately characterize the parameters being measured. High-resolution data sets are reconstructed using Equivalent Time Sampling. High-resolution input data sets are used in a system model to simulate the performance of the system being measured. Results from the system model, and high-resolution output data sets from Equivalent Time Sampling, are provided to an estimator, which provides accurate estimation of measured quantities and estimation of quantities not measured. Output from the estimator is used for fault diagnosis and control of the system being measured.