Image Forming Unit Sound Diagnosis via Multi-Period Drive Comparison
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Solution Overview
Problem
Existing image forming apparatuses, such as copiers and laser printers, are unable to accurately detect and identify both known and unknown abnormal sounds emitted by components nearing the end of their lifespan, which can indicate impending failures.
Innovation Solution
An abnormal sound diagnosis system that utilizes a determination unit to analyze sound wave levels and driving states of multiple units in an image forming apparatus, comparing these states across different time periods to identify the source of abnormal sounds using a cosine similarity method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sound detection is performed only at predetermined timing when known abnormal sound is emitted, then determination on known abnormal sound can be made, but determination on unknown abnormal sound cannot be performed
Solution Approach 1:
The sound detection process is segmented into multiple time periods corresponding to different driving units' operation. By dividing the detection into discrete time segments and comparing sound wave levels across these segments, the system can identify which specific driving unit is generating abnormal sound, thereby enabling detection of both known and unknown abnormal sounds.
Solution Approach 2:
The system adds a temporal dimension to sound detection by measuring sound wave levels across multiple time periods rather than at a single predetermined moment. This multi-dimensional approach allows comparison of sound characteristics across different operating phases, enabling identification of unknown abnormal sounds that occur at various timings.
2Adaptability or versatility
If multiple time periods and driving states are analyzed to specify abnormal sound cause, then both known and unknown abnormal sound can be detected, but system complexity increases
Solution Approach 1:
The system replaces complex mechanical diagnostic procedures with automated computational analysis. By using a determination unit to automatically compare sound wave levels across multiple time periods and correlate them with driving states, the system achieves comprehensive abnormal sound detection without requiring complex manual intervention or additional physical components.
Solution Approach 2:
The diagnosis system performs self-analysis by automatically comparing its own measured sound wave levels against recorded driving states. The determination unit autonomously identifies abnormal sound sources through computational comparison, eliminating the need for external expert intervention and simplifying the overall system architecture.
Data Source
AI summary
An abnormal sound diagnosis system for specifying a cause of abnormal sound in an apparatus that includes a plurality of operating units that perform a predetermined operation and a plurality of driving units that drive the plurality of operating units: determines occurrence of abnormal sound in a plurality of time periods, based on sound wave levels of sound occurring in the apparatus measured in the plurality of time periods; obtains driving states of the plurality of driving units in the plurality of time periods; and specifies a driving unit corresponding to occurrence of abnormal sound based on a plurality of comparison results corresponding to different timings, that are obtained by comparing the driving states and the occurring states obtained at the different timings in the predetermined operation.