Image-Based Clogged Nozzle Detection for Cleaning Devices
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Solution Overview
Problem
Existing cleaning devices face challenges in detecting clogged nozzles efficiently, which can lead to reduced cleaning performance and effectiveness, as traditional methods often require additional sensors and may not accurately identify blockages in real-time.
Innovation Solution
A method and control unit utilizing an image acquisition device, such as a camera, to read and evaluate current image data within the cleaning device, allowing for the detection of clogged nozzles by comparing image characteristics with stored reference data, and adjusting flushing parameters or providing user notifications for maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sensor-based methods are used to detect clogged nozzles, then detection capability is provided, but device complexity increases due to additional sensors
Solution Approach 1:
The image acquisition device originally designed for monitoring cleaning performance is made multi-functional by enabling it to detect nozzle blockages in addition to its primary monitoring function. This eliminates the need for separate dedicated sensors while maintaining detection capability.
Solution Approach 2:
The cleaning device uses its own existing imaging infrastructure to perform self-diagnosis for nozzle blockages. The system monitors its own operational state using resources already available within the device, avoiding external additions.
2Measurement precision
If image acquisition device is used to detect clogged nozzles, then detection precision is improved, but device complexity remains low as no additional sensors are needed
Solution Approach 1:
Traditional mechanical or electrical sensors are replaced with an optical imaging system for detecting nozzle blockages. The image acquisition device captures visual data of the spray pattern, and image processing algorithms analyze this data to detect blockages, substituting physical sensing with optical observation and computational analysis.
Solution Approach 2:
Instead of directly measuring physical parameters with sensors, the system creates an optical copy (image) of the spray pattern and analyzes this representation to detect blockages. The image serves as a copy of the actual spray state, enabling indirect but precise measurement.
3Productivity
If real-time image evaluation is performed to detect blockages, then productivity is improved through immediate detection, but use of energy increases due to continuous processing
Solution Approach 1:
Instead of continuous real-time processing, the system performs image evaluation at periodic intervals during the cleaning cycle. The image acquisition device captures images at predetermined times, and the evaluation unit processes these images to detect blockages, reducing computational load while maintaining effective monitoring.
Solution Approach 2:
The system performs image acquisition and evaluation in advance during cleaning cycles to detect blockages before they significantly impact cleaning performance. This proactive approach allows for timely intervention while optimizing processing timing to reduce energy consumption.
Data Source
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AI summary
The invention relates to a method for detecting a blocked nozzle for a cleaning device (100), which has an image acquisition device (106) for capturing an interior (104) of the cleaning device (100). The method comprises a step of reading current image data via an interface to the image acquisition device (106) of the cleaning device (100) and a step of evaluating the current image data to detect a blockage of the nozzle.