Machine Ears: Audio Frequency Based Automobile Engine Health Analysis

Journal of Machine and Computing, Journal Year: 2025, Volume and Issue: unknown, P. 197 - 208

Published: Jan. 3, 2025

Maintaining both rider safety and vehicle dependability on motorbikes requires accurate problem detection. Using an improved ResNet architecture with Improved Sea Fish Optimization (ISFO) Deep Convolutional Neural Networks (CNNs), this research proposes a sophisticated method for auditory defect identification in motorbikes. The machine ears start by gathering wide range of audio frequency-based signal datasets from motorbike that span failure scenarios operational settings. To eliminate noise identify distinguishing characteristics, these signals go through preprocessing. Then, to extract high-level features the pre-processed signals, is used, supplemented ISFO. By integrating local global information, architecture's inclusion ISFO makes it easier iteratively update feature representations. further improve representations' discriminative power, CNNs are used. real-time detection system designed specifically uses learned model. trained model used interpret incoming acoustic data motorcycle operations. This allows categorization various issues, such as engine misfires, irregularities valves, wear bearings, clutch bearing failures. Experiments show proposed good fit precisely categorizing issues. Analyses conducted comparison baseline models demonstrate superiority ResNet-ISFO CNN technique, demonstrating its resilience efficiency across fault situations conditions. Overall, potential approach improving maintenance procedures while also assuring automobile engine. Its incorporation into standard operations can aid proactive identification, reducing downtime performance.

Language: Английский

---

Enhancing vehicle fault diagnosis through multi-view sound analysis: integrating scalograms and spectrograms in a deep learning framework

Signal Image and Video Processing, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 1, 2025

Language: Английский

---

Non-invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review

Published: July 9, 2024

This article provides a detailed analysis of non-invasive techniques for prediction and diagnosis faults in internal combustion engines, focusing on the application Proknow-C Methodi Ordinatio systematic review methods. Initially, relevance these promoting energy sustainability mitigating greenhouse gas emissions is discussed, aligning with Sustainable Development Goals (SDGs) Agenda 2030 Paris Agreement. The conducted subsequent sections offers comprehensive mapping state-of-the-art, highlighting effectiveness combining methods categorizing systematizing relevant scientific literature. results reveal significant advancements use artificial intelligence (AI) digital signal processors (DSP) to enhance fault diagnosis, as well underscore crucial role minimizing interference monitored systems. Finally, concluding remarks point towards future research directions, emphasizing need develop twins engines identify gaps further improvements techniques.

Language: Английский

---

Non-invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review

Published: July 2, 2024

This article provides a detailed analysis of non-invasive techniques for prediction and diagnosis faults in internal combustion engines, focusing on the application Proknow-C Methodi Ordinatio systematic review methods. Initially, relevance these promoting energy sustainability mitigating greenhouse gas emissions is discussed, aligning with Sustainable Development Goals (SDGs) Agenda 2030 Paris Agreement. The conducted subsequent sections offers comprehensive mapping state-of-the-art, highlighting effectiveness combining methods categorizing systematizing relevant scientific literature. results reveal significant advancements use artificial intelligence (AI) digital signal processors (DSP) to enhance fault diagnosis, as well underscore crucial role minimizing interference monitored systems. Finally, concluding remarks point towards future research directions, emphasizing need develop twins engines identify gaps further improvements techniques.

Language: Английский

---

Gasoline Engine Misfire Fault Diagnosis Method Based on Improved YOLOv8

Electronics, Journal Year: 2024, Volume and Issue: 13(14), P. 2688 - 2688

Published: July 9, 2024

In order to realize the online diagnosis and prediction of gasoline engine fire faults, this paper proposes an improved misfire fault detection algorithm model based on YOLOv8 for sound signals engines. The improvement involves substituting a C2f module in backbone network by BiFormer attention another substituted CBAM that combines channel spatial mechanisms which enhance neural network’s capacity extract complex features. normal are processed wavelet transformation converted time–frequency images training, verification, testing convolutional network. experimental results show precision is 99.71% tests, 2 percentage points higher than model. time each less 100 ms, making it suitable developing IoT devices driverless vehicles.

Language: Английский

---

Non-Invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6164 - 6164

Published: Dec. 6, 2024

This article provides a detailed analysis of non-invasive techniques for the prediction and diagnosis faults in internal combustion engines, focusing on application Proknow-C Methodi Ordinatio systematic review methods. Initially, relevance these promoting energy sustainability mitigating greenhouse gas emissions is discussed, aligning with Sustainable Development Goals (SDGs) Agenda 2030 Paris Agreement. The conducted subsequent sections offers comprehensive mapping state art, highlighting effectiveness combining methods categorizing systematizing relevant scientific literature. results reveal significant advancements use artificial intelligence (AI) digital signal processors (DSP) to improve fault diagnosis, addition crucial role such as twin minimizing interference monitored systems. Finally, concluding remarks point towards future research directions, emphasizing need develop integration AI algorithms twins engines identify gaps further improvements techniques.

Language: Английский

---

Structuring of the Main Measurement Zones of Acoustic Tracks for Diagnose of the Internal Combustion Engine Components

2020 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO), Journal Year: 2023, Volume and Issue: unknown, P. 1 - 5

Published: June 28, 2023

The article describes the prerequisites for creating a methodology diagnosing an internal combustion engine by noise emitted. used diagnosticians at car services is taken as basis. An overview of works in which analyzed and modeled, source technical means. classification emitted proposed. analysis main cyclic processes engine, should form basis its diagnosis, given. Based on engineering layout zones are proposed it possible to record characteristic noises. experiment was conducted fix sound tracks various points above real car. A preliminary method signal processing results such presented. Conclusions drawn about validity deterministic approaches produced engine.

Language: Английский

---