Technical System State Evaluation Using Continuous Condition Parameters
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Solution Overview
Problem
Existing methods for assessing the condition of technical systems characterized by discrete state parameters struggle to provide accurate predictions due to abrupt state changes and stochastic estimates that do not consider the actual system state, limiting timely corrective actions.
Innovation Solution
Incorporating a second state parameter, which can be continuous or have more values than the first discrete parameter, to derive an evaluation parameter for assessing the system's condition, allowing for a more accurate prediction of the system's state and enabling timely interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If binary or discrete state parameters are used to characterize the system, then the system state can be simplified for assessment, but the prediction accuracy of state changes deteriorates
Solution Approach 1:
The invention segments the state parameter into two parts: a discrete first state parameter (with N possible values) and a continuous second state parameter. This segmentation allows the discrete parameter to provide simplified system state characterization while the continuous parameter provides the detailed information needed for accurate prediction of state changes.
Solution Approach 2:
The invention transitions from a purely discrete state parameter to a two-dimensional state space combining discrete and continuous parameters. The continuous second state parameter adds a new dimension that enables gradual change detection and improved prediction accuracy without complicating the overall system assessment framework.
2Reliability
If stochastic approaches such as fault trees or Markov chains are used, then the probability of system failures can be estimated, but the actual system state information is not taken into account
Solution Approach 1:
The invention introduces feedback by using the continuous second state parameter to reflect the actual system state. This feedback mechanism allows the reliability assessment to be continuously updated based on real system conditions, enabling more accurate failure probability estimates that incorporate current system state information.
Solution Approach 2:
The invention changes the parameter representation from purely discrete to a combination of discrete and continuous parameters. The continuous second state parameter captures subtle changes in system condition, providing rich state information that enhances failure probability estimation while avoiding the information loss inherent in purely stochastic approaches.
3Ease of operation
If a discrete first state parameter with N values is used, then the system assessment is simplified, but the ability to detect gradual state changes deteriorates
Solution Approach 1:
The invention segments the state parameter into discrete and continuous components. The discrete first state parameter maintains assessment simplicity by providing clear state categories, while the continuous second state parameter enables detection of gradual changes through its ability to capture subtle variations in system condition.
Solution Approach 2:
The invention introduces dynamics by using the continuous second state parameter to track gradual changes in system condition over time. This dynamic parameter complements the static discrete states, enabling the detection of trends and gradual deteriorations that precede discrete state transitions.
Data Source
Figure 1~2
AI summary
According to a computer-implemented procedure for the state assessment of a technical system (1), which is characterizable by a given first state parameter and which is characterizable by a given second state parameter, wherein the first state parameter can assume N different discrete values, where N is a natural number and greater than one, and the second state parameter of the system (1) can assume all values in a continuous range of values or M different discrete values, where M is a natural number and greater than N, and from each value that the second state parameter can assume, one of the N discrete values for the first state parameter can be uniquely calculated, a measurement result of at least one measurement on the system (1) is obtained.Depending on the measurement result, a current value for the second state parameter is determined, and depending on the current value and a given first critical value of the N discrete values for the first state parameter, an evaluation characteristic is determined.