Crane Bearing Load Calculation via External Data Processing
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Solution Overview
Problem
Current methods for calculating the bearing load of cranes are computation-intensive and cannot be reasonably performed in real-time during operation, leading to inaccuracies and the need for safety margins that do not fully utilize the crane's load capacity.
Innovation Solution
A process that outsources resource-intensive calculations to an external data processing center, where parameters from the crane are transmitted and used to compute and provide real-time bearing load data, allowing for precise determination of permissible loads based on current conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bearing load tables are computed in advance with external means and stored in the crane, then computation-intensive calculations are performed offline, but it is nearly impossible to make an individual bearing load table available for all different operating situations, leading to inaccuracies in determining permissible bearing load
Solution Approach 1:
The patent pre-computes bearing load tables for all possible combinations of crane-specific and order-specific parameters before operation begins. These comprehensive tables are stored in the crane's memory, enabling the system to quickly retrieve accurate bearing load values for any operating situation without performing complex calculations during actual crane operation.
Solution Approach 2:
The patent implements a dynamic selection mechanism that automatically identifies the most appropriate bearing load table based on current operating conditions. By comparing actual crane parameters with stored table parameters, the system dynamically selects or interpolates between tables to provide accurate bearing load determination for situations not exactly matching pre-computed tables.
2Adaptability or versatility
If all conceivable combinations of bearing load tables are computed before operation, then complete coverage of operating situations is achieved, but the enormous quantity of data makes it impossible to compute and store all tables
Solution Approach 1:
The patent segments the comprehensive bearing load data into multiple individual tables, each covering a specific combination of crane parameters and order-specific parameters. This segmentation allows the system to manage and store data in organized units, retrieving only the relevant segments needed for current operating conditions rather than storing all possible data in a single massive structure.
Solution Approach 2:
The patent computes bearing load tables for all possible parameter combinations (excessive action) during the offline phase, storing these comprehensive tables in the crane's memory. This approach ensures complete coverage of all operating situations without requiring complex real-time calculations, accepting the data storage requirement as a one-time investment that enables accurate operation throughout the crane's service life.
3Adaptability or versatility
If bearing load tables are selected and interpolated for scenarios not computed in advance, then some flexibility is achieved, but interpolation onto the crane between two or more bearing load tables cannot be avoided, introducing additional inaccuracies
Solution Approach 1:
The patent pre-computes bearing load tables for all possible combinations of parameters, eliminating the need for interpolation during operation. By covering all conceivable scenarios in advance, the system can directly retrieve accurate bearing load values without performing approximate calculations, thereby maintaining high precision across all operating conditions.
4Reliability
If a safety margin is included for load torque limitation to account for inaccuracies, then safety is improved, but the bearing load that is actually possible cannot be completely utilized, reducing productivity
Solution Approach 1:
The patent replaces the mechanical safety margin approach with a computational solution. Instead of applying conservative reduction factors to bearing load values, the system uses sophisticated algorithms to compute and retrieve precise bearing load tables that accurately reflect the crane's actual capacity under specific operating conditions. This substitution eliminates unnecessary safety margins while maintaining safety through accurate real-time determination of permissible loads.
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors actual crane operating conditions and uses this information to select or interpolate the most appropriate bearing load table. By comparing real-time parameters with stored table parameters, the system dynamically adjusts the bearing load determination to match actual conditions, maximizing load capacity utilization while maintaining safety through accurate, condition-specific calculations.
Data Source
AI summary
The invention relates to a process for the calculation of relevant data for the operation of at least one crane, particularly of a mobile crane, whereby the system comprises at least one crane, a communication network, as well as a data processing center, whereby, first of all, one or more parameters of the crane are determined on the crane and these are transmitted to the data processing center through the communication network and, in the data processing center, one or more items of data that are relevant for the operation of the crane are computed and/or selected on the basis of the one or more parameters received from the crane and the relevant data computed and/or selected for the operation of the crane is transmitted back to the at least one crane, particularly to its crane control. Furthermore, the invention relates to a system for the calculation and/or selection of data relevant to the operation of at least one crane that is suitable for the implementation of the process in accordance with the invention.