MRI Energy-Saving State Selection Under Readiness Time Constraints
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining the optimal energy-saving state of MRI systems are inflexible, leading to missed energy-saving opportunities due to reliance on time-controlled or event-controlled approaches, and require manual intervention or component communication, which can be costly and labor-intensive.
Innovation Solution
A computer-implemented method using a central control system that receives a rule set and component states to determine the optimal energy-saving state, allowing for automatic determination and implementation of the most energy-efficient state based on activation time and other parameters, without requiring direct communication between components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the MRI system uses time-controlled energy-saving mode, then energy can be saved during predictable idle periods, but the system cannot respond to unexpected usage changes and misses short idle periods
Solution Approach 1:
The system uses a central controller to automatically monitor component states and determine optimal energy-saving modes without manual intervention. The controller receives state information from various components, applies decision rules, and autonomously activates appropriate energy-saving states, enabling the system to adapt dynamically to actual usage patterns rather than relying on fixed schedules or manual operation
Solution Approach 2:
The system implements continuous monitoring of component states (such as patient table position, gradient amplifier status) and uses this feedback information to dynamically adjust energy-saving modes. The central controller receives real-time state data, processes it according to decision rules, and adjusts the energy-saving state accordingly, creating a closed-loop control system that adapts to changing conditions
2Loss of energy
If the MRI system uses event-driven energy-saving mode with component communication, then energy can be saved based on actual usage events, but component replacement becomes complex and costly due to communication protocol requirements
Solution Approach 1:
The central controller serves as an intermediary that receives state information from various components and translates it into energy-saving decisions. Rather than requiring direct communication between all components (which would create complex interdependencies), the central controller acts as a hub that decouples component communication requirements, allowing components to be replaced independently as long as they can communicate their basic state to the controller
Solution Approach 2:
The central controller provides a universal interface for receiving state information from different component types (patient table, gradient amplifier, etc.) and applying unified decision rules. This universal approach allows different components to be replaced with various models as long as they can provide their state information through the standard interface, rather than requiring proprietary communication protocols between specific component pairs
3Loss of energy
If the MRI system shuts down more components for deeper energy-saving mode, then more energy can be saved, but the system takes longer to become ready for use again
Solution Approach 1:
The system dynamically adjusts the depth of energy-saving states based on actual needs. Rather than using fixed deep or shallow states, the central controller continuously evaluates component states and usage patterns to determine the optimal energy-saving level, allowing the system to transition between different activation depths as conditions change
Solution Approach 2:
The system changes operational parameters of components (such as power levels, standby modes, or operational states) based on the determined energy-saving state. The central controller adjusts these parameters dynamically to achieve optimal energy savings while maintaining the ability to quickly reactivate when needed, rather than using fixed parameter sets for each energy-saving mode
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
The invention relates to a computer-implemented method for determining an optimal energy-saving state of a magnetic resonance imaging (MRI) system. The method comprises a process step of receiving (REC-1) a control set with a central controller. The method further comprises a process step of receiving (REC-2) at least one state of at least one component with the central controller. The at least one component is a component of the MRI system and/or an environment of the MRI system. The control set comprises at least one rule by which the optimal energy-saving state can be determined based on the at least one state of the at least one component. The method further comprises a process step of determining (DET) the optimal energy-saving state based on the control set and the at least one state of the at least one component.The procedure also includes a procedural step of providing (PROV) information regarding the optimal energy-saving state.