Refuse Vehicle Compaction System Using Image-Based Profile Selection
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Solution Overview
Problem
Existing refuse vehicle systems lack efficient methods to optimize compaction based on the type of refuse being collected, leading to suboptimal storage capacity and operational efficiency.
Innovation Solution
A refuse vehicle system equipped with a camera and processing circuits that analyze image data to determine the refuse category, thereby adjusting the compaction system's operation parameters to optimize packing profiles for different types of refuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single compaction profile is used for all refuse types, then the system operation is simple, but the storage capacity and compaction efficiency are suboptimal
Solution Approach 1:
The compaction system transitions from a static single-profile operation to a dynamic multi-profile system that automatically adjusts compaction parameters based on refuse type. The system dynamically selects packing profiles (e.g., compact vs. gentle compaction) according to the detected refuse category, optimizing storage capacity for each material type while maintaining manageable system complexity through automated decision-making.
Solution Approach 2:
The system changes compaction parameters such as compaction force, actuator speed, and pressure levels based on the detected refuse type. By varying these parameters according to material characteristics (e.g., higher force for dense materials, lower force for fragile materials), the system maximizes storage capacity without requiring manual intervention or overly complex user interfaces.
2Productivity
If manual adjustment of compaction parameters is required, then the system remains simple, but operational efficiency and adaptability are reduced
Solution Approach 1:
The system performs self-adjustment by automatically detecting refuse type through sensors and selecting appropriate compaction profiles without operator intervention. The automated system monitors refuse characteristics and independently modifies compaction parameters, eliminating the need for manual adjustment while maintaining high operational efficiency and adaptability across different material types.
Solution Approach 2:
The system incorporates feedback mechanisms where sensors detect refuse type and compaction effectiveness in real-time, and the control system automatically adjusts parameters based on this feedback. This closed-loop control enables the system to adapt to varying refuse conditions automatically, improving operational efficiency without requiring manual monitoring or adjustment.
3Productivity
If compaction parameters are optimized for each refuse type, then storage capacity increases, but the risk of incorrect compaction and operational errors increases
Solution Approach 1:
The system replaces manual operator judgment and mechanical adjustment mechanisms with automated sensor-based detection and electronic control. Sensors automatically identify refuse types, and the control system electronically selects and applies appropriate compaction parameters, eliminating human error while maximizing storage capacity. This substitution of mechanical/manual processes with automated systems enhances both productivity and reliability.
Solution Approach 2:
The system creates and stores multiple pre-optimized compaction profiles as templates for different refuse types. Instead of calculating parameters in real-time, the system copies and applies pre-verifies parameter sets from the database, reducing computational complexity and operational errors while maintaining optimized storage capacity for each material type.
Data Source
AI summary
A refuse vehicle includes a chassis, a body coupled to the chassis, a compaction system, a camera, and one or more processing circuits. The body defines a refuse compartment configured to store refuse therein. The one or more processing circuits are configured to acquire, from the camera, image data corresponding to an object associated with refuse acquired by the refuse vehicle, determine, based on the image data, a refuse category associated with the object, determine, based on the refuse category, a first packing profile for the compaction system, and operate the compaction system according to the first packing profile. The first packing profile includes at least one packing parameter associated with operation of the compaction system.