Abnormal Noise Source Identification in Image Forming Apparatuses
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Solution Overview
Problem
Existing techniques for detecting abnormal noise in image forming apparatuses face challenges in accurately identifying the source of noise due to overlapping waveforms of different frequencies, making it difficult to determine whether abnormal noise has occurred and pinpointing the affected operating body.
Innovation Solution
An electronic device with a control unit that collects operating noise data, performs frequency analysis using CWT conversion, compares it with stored normal spectrogram data, and identifies the source of abnormal noise by matching time ranges in the diagnostic and normal spectrograms, allowing for precise determination and display of the affected component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency spectral waveform data is collected and analyzed to detect abnormal noise, then the ability to detect noise occurs, but overlapping waveforms of different frequencies make it difficult to accurately identify the source of noise
Solution Approach 1:
The patent divides the continuous noise waveform into discrete operational phases corresponding to each operating body's operation period. By segmenting the noise data into time-based phases and creating separate spectrograms for each phase, the system can isolate and analyze noise from individual operating bodies, thereby resolving the overlapping waveform problem and accurately identifying noise sources.
2Reliability
If noise data is collected during normal operation, then operational context is preserved, but determining whether abnormal noise has occurred becomes difficult without reference timing information
Solution Approach 1:
The patent pre-stores timing charts that define the normal operation periods of each operating body before noise detection begins. These timing charts serve as reference data that provide the temporal framework needed to interpret collected noise data, enabling reliable determination of whether abnormal noise occurred during specific operational phases without losing timing reference information.
Solution Approach 2:
The patent creates spectrograms that are visual representations (copies) of the noise data in the frequency-time domain. By generating spectrograms from both the collected noise data and the stored normal operation data, the system can visually compare and identify deviations, making it easier to detect abnormal noise while preserving the temporal context through the spectrogram's time axis.
3Productivity
If multiple operating bodies operate sequentially, then complex processing can be executed, but it becomes difficult to pinpoint which specific operating body is the source of abnormal noise
Solution Approach 1:
The patent segments the noise analysis by creating separate spectrograms for each operating body's operation period based on the timing chart. Each spectrogram corresponds to a specific operating body's operational phase, allowing the system to maintain high productivity through sequential operation while achieving precise noise source identification by comparing anomalies against the segmented temporal framework.
Solution Approach 2:
The timing chart serves as an intermediary that links the collected noise data to the specific operating bodies. By using the timing chart as a reference framework, the system can map detected noise anomalies back to the corresponding operating body that was active during that time period, thereby resolving the identification problem while maintaining the ability to execute complex sequential processing.
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
This approach enables accurate detection and identification of abnormal noise sources by clearly distinguishing noise patterns, even with overlapping frequencies, thereby improving maintenance efficiency and reliability of image forming apparatuses.
Implementation Method 1
a noise collecting device 22 that collects operating noise of the plurality of operating bodies during execution of the processing and outputs operating noise data representing the collected operating noise
Implementation Method 2
the controller subjects the operating noise data to frequency analysis to acquire a spectrogram
Data Source
AI summary
In an image forming apparatus, a controller allows a sound output device to output a starting sound and an ending sound at a start and end of diagnostic image formation processing, respectively, determines whether abnormal noise has occurred by identifying data ranging from the starting sound to the ending sound in an diagnostic spectrogram as a comparison target for data ranging from the starting sound to the ending sound in a normal spectrogram to match both the spectrograms in terms of width in a time-axis direction, and identifies a source of the abnormal noise by identifying the data ranging from the starting sound to the ending sound in the diagnostic spectrogram as a comparison target for data in ranging from a timing of start to a timing of end in a timing chart to match the diagnostic spectrogram with the timing chart in terms of width in the time-axis direction.