Garbage Truck Hopper Volume Detection via Machine Vision
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Solution Overview
Problem
Current garbage trucks inefficiently operate the compactor, leading to excessive energy consumption, noise generation, and pollutant emission, especially when little refuse is present, causing unnecessary wear on truck components.
Innovation Solution
Integration of a machine vision system with modulated light and a camera sensor to determine the volume and distribution of refuse in the hopper, allowing the compactor to be controlled based on specific operating modes, reducing unnecessary operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the compactor is operated continuously in current garbage trucks, then the refuse is compacted and transported, but unnecessary noise and contaminants are generated, energy is wasted, and parts are unnecessarily worn out when no or small amount of refuse is present
Solution Approach 1:
The system uses machine vision means (camera and light source) to continuously monitor the hopper and provide feedback information about refuse volume to the control unit. The control unit adjusts compactor operation based on this feedback, operating only when sufficient refuse is detected, thereby eliminating energy waste from unnecessary operation while maintaining compaction efficiency when needed.
Solution Approach 2:
The machine vision system automatically detects refuse volume and triggers compactor operation without continuous human intervention or unnecessary operation. The system serves itself by monitoring its own operational conditions and adjusting accordingly, activating the compactor only when the hopper contains sufficient refuse, thus preventing energy waste and unnecessary wear.
2Productivity
If the compactor is operated continuously, then refuse is compacted, but unnecessary noise and pollutant emission are generated
Solution Approach 1:
The control unit receives real-time feedback from the machine vision system about refuse volume in the hopper. Based on this feedback, the compactor is activated only when sufficient refuse is present, preventing noise and pollutant emission during empty or partially-filled operations while maintaining compaction productivity when the hopper is adequately filled.
3Productivity
If the compactor is operated continuously, then refuse is compacted, but parts and consumables such as oil and bearings are unnecessarily worn out
Solution Approach 1:
The control unit monitors refuse volume through the machine vision system and uses this feedback to control compactor operation. The compactor runs only when the hopper contains sufficient refuse, reducing unnecessary mechanical wear on parts, bearings, and oil while maintaining compaction efficiency when needed, thereby improving component reliability and reducing maintenance needs.
4Loss of energy
If machine vision means are added to monitor refuse volume, then compactor operation is optimized, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical monitoring systems with an optical machine vision system consisting of a camera and light source. This substitution reduces mechanical complexity while enabling automatic refuse volume detection, which optimizes compactor operation and reduces energy consumption without requiring complex mechanical sensors or switches.
Solution Approach 2:
The machine vision system acts as an intermediary between the hopper contents and the control unit. The camera and light source provide a simple optical interface that translates refuse volume into electrical signals for the control unit, simplifying the overall system architecture compared to direct mechanical monitoring while enabling intelligent operation control.
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
Reduces energy consumption and pollutant emission by optimizing compactor operation only when necessary, minimizing wear on truck components and enhancing operational efficiency.
Implementation Method 1
The machine vision means comprise a source of modulated light, a camera sensor, and means for periodically generating geometries corresponding to the interior of the hopper
Implementation Method 2
This allows distances from the camera sensor to different points in the hopper to be determined based of a time-of-flight principle (ToF). Based on this principle, distances from the camera sensor to different points in the hopper are accurately determined based on time difference between the emission of modulated light and its return to the camera sensor.
Implementation Method 3
The camera sensor is connected to the source of modulated light and arranged for receiving light that is reflected by the hopper, or by the refuse placed therein
Data Source
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AI summary
The garbage truck (100) comprises a hopper (200) for collecting refuse, a compactor (400) for compacting refuse inside the hopper (200), machine vision means (500), and a control unit (600) connected to the machine vision means (500) and configured for monitoring an area of the interior (210) of the hopper (200) so as to determine a volume of refuse present inside the hopper (200) for controlling the compactor (400) according to a given operating mode depending on the volume of refuse present in the hopper (200).