Accelerometer Signal Processing for Engine Misfire Detection
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Solution Overview
Problem
Existing methods using accelerometer sensors to detect engine misfire face challenges in accurately identifying misfires under low load and idle conditions due to signal noise and low signal amplitudes, making it difficult to distinguish between combustion and non-combustion events.
Innovation Solution
A method involving real-time accelerometer signal processing, including digitization, filtering, integration, and comparison with a predetermined reference data set to detect misfires, which amplifies the difference between signal noise and combustion signals, and incorporates a look-up table for engine-specific reference data based on operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If accelerometer sensors are used to detect engine misfire, then misfire detection capability is provided, but measurement precision deteriorates under low load and idle conditions due to signal noise and low signal amplitudes
Solution Approach 1:
The patent applies preliminary action by pre-processing the accelerometer signal through digitization, filtering, and integration before comparison. The signal is filtered to remove noise components and integrated to accumulate the combustion signal over time, enhancing the signal-to-noise ratio before the actual misfire detection comparison occurs. This preliminary processing ensures that even weak combustion signals under low load conditions are sufficiently amplified for accurate detection.
Solution Approach 2:
The patent uses an intermediary approach by introducing a reference data set as a mediator between the raw accelerometer signal and the misfire detection decision. The reference data set, stored in a look-up table based on engine operating conditions, serves as a benchmark for comparison. This intermediary reference allows the system to distinguish between normal variation and actual misfire events, improving measurement precision under varying load conditions.
2Measurement precision
If signal filtering and integration are applied to enhance combustion signal detection, then measurement precision improves, but device complexity increases due to additional signal processing steps
Solution Approach 1:
The patent applies segmentation by dividing the signal processing task into distinct modular stages: digitization, filtering, integration, and comparison. Each stage handles a specific aspect of signal processing, making the overall complex system manageable and implementable. The filtering stage separates noise from signal, the integration stage accumulates combustion information, and the comparison stage evaluates against reference data, allowing each module to be optimized independently.
Solution Approach 2:
The system applies self-service by using the engine's own operating conditions (speed, load) to automatically select the appropriate reference data from the look-up table. The controller retrieves the matching reference data based on current operating parameters without requiring manual intervention or complex adaptive algorithms, simplifying the device while maintaining high measurement precision across varying conditions.
3Adaptability or versatility
If a look-up table with engine-specific reference data is implemented, then adaptability to different operating conditions improves, but device complexity increases due to additional data storage and retrieval requirements
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing reference data sets for various engine operating conditions in a look-up table before actual operation. During runtime, the system only needs to retrieve the appropriate reference data based on current speed and load parameters, rather than performing complex real-time calculations. This preliminary preparation enables rapid adaptation to different operating conditions while keeping the runtime processing simple and efficient.
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
The method effectively detects engine misfires with high accuracy and robustness, even under challenging conditions, by converting filtered signals to absolute values and integrating them to enhance signal differentiation, allowing for precise identification of misfire events.
Implementation Method 1
Accelerometer sensors are sold commercially for use as knock sensors for detecting engine knock
Implementation Method 2
band-pass filtering the real-time accelerometer signal to isolate data in a frequency range that corresponds to a characteristic frequency of the engine bearing cap assembly
Implementation Method 3
integrating the filtered signal data set to produce an integrated signal data set
Data Source
AI summary
The method comprises operating an engine and collecting a real-time accelerometer signal from an accelerometer sensor. The real-time accelerometer signal is digitized and filtered to isolate data in a frequency range associated with combustion to produce a filtered signal data set. The filtered signal data set is integrated to produce an integrated signal data set, and misfire is detected by comparing the integrated signal data set with a predetermined reference data set associated with the same operating point. The apparatus is a control system for an engine that comprises an accelerometer sensor mounted to the engine; a look-up table in which is stored predetermined reference data sets, in association with predetermined operating conditions; and an electronic controller programmed to carry out the foregoing method.