Diagnostic Device for Image Forming Noise Analysis
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Solution Overview
Problem
Current diagnostic methods for identifying noise in image forming devices are inefficient, as they often require on-site installation of sound recording capabilities, which may be undesirable for security reasons, and lack effective tools for remote analysis and identification of noise causes.
Innovation Solution
A diagnostic device and system that acquires sound information, performs time-frequency analysis, and displays results to help identify noise causes, using a mobile device connected to a server for data exchange and analysis, allowing remote diagnosis by extracting device information modulated onto inaudible sound signals and comparing with past noise data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-site sound recording is implemented, then noise diagnostic capability is improved, but security risks and device complexity increase
Solution Approach 1:
The patent introduces a server as an intermediary between the sound source and the diagnostician. The server receives sound signals from the image forming device, performs noise analysis, and returns diagnostic results. This eliminates the need for on-site recording equipment and expertise, as the server handles all sound acquisition and analysis functions remotely.
Solution Approach 2:
The patent replaces physical on-site sound recording equipment with a computational system. Instead of using microphones, recording devices, and manual analysis tools at the customer site, the system uses automated sound signal processing, time-frequency analysis, and pattern recognition algorithms executed on a server to diagnose noise issues.
2Ease of operation
If remote diagnosis is implemented, then on-site installation requirements are reduced, but analysis accuracy may deteriorate
Solution Approach 1:
The patent performs preliminary noise analysis by comparing current sound signals against a pre-stored database of normal and abnormal noise patterns. The system proactively identifies deviations from normal operation by matching acoustic signatures against known failure modes, enabling accurate remote diagnosis without requiring physical presence.
Solution Approach 2:
The system implements feedback mechanisms where diagnostic results are returned to the user, and the database of noise patterns is continuously updated with new data. This feedback loop improves analysis accuracy over time by learning from additional cases and refining the distinction between normal and abnormal noise patterns.
3Measurement precision
If time-frequency analysis is performed, then noise source identification is improved, but processing time increases
Solution Approach 1:
The patent applies partial action by performing time-frequency analysis selectively on suspicious frequency components rather than analyzing the entire spectrum in detail. The system first identifies frequency ranges that deviate from normal patterns, then applies comprehensive time-frequency analysis only to those specific regions, reducing overall processing time while maintaining diagnostic accuracy.
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
Enables efficient remote diagnosis of noise in image forming devices by analyzing sound signals for noise causes, reducing the need for on-site sound recording and improving the accuracy of identifying noise sources through time-frequency analysis and comparison with historical data.
Implementation Method 1
an acquisition unit that acquires sound information
Implementation Method 2
The generation unit performs time-frequency analysis on the acquired sound information, and generates a first analysis result expressing change over time in an intensity distribution at each frequency
Implementation Method 3
The display displays a second analysis result chosen on the basis of the first analysis result and the device information, and the first analysis result
Data Source
AI summary
A diagnostic device includes an acquisition unit, an extraction unit, a generation unit, and a display. The acquisition unit acquires sound information. The extraction unit extracts, from the acquired sound information, device information related to a device to be analyzed. The generation unit performs time-frequency analysis on the acquired sound information, and generates a first analysis result expressing change over time in an intensity distribution at each frequency. The display displays a second analysis result chosen on the basis of the first analysis result and the device information, and the first analysis result.