Binary Event History Coding for Storage Reduction
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Solution Overview
Problem
Existing event history coding schemes require significant storage and bandwidth for time-sensitive data, impacting maintenance scheduling and equipment utilization efficiency due to the need to monitor occurrence times or cumulative durations of events.
Innovation Solution
A method and device for coding event history using binary '0' and '1' values to represent two states of an event over defined time intervals, reducing data storage needs and allowing for efficient transmission and archiving, with optional additional compression techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occurrence time of events is monitored, then event timing information is captured, but storage requirements and bandwidth requirements increase significantly
Solution Approach 1:
The patent extracts only the essential information needed for event history coding - specifically whether the event is in state 0 or state 1 during each time interval - and discards redundant data such as precise occurrence timestamps. This extraction principle reduces the data volume from continuous time-series data to discrete binary states, directly resolving the contradiction between capturing event timing information and minimizing storage requirements.
Solution Approach 2:
The patent changes the parameter representation from continuous time values to discrete binary states (0 or 1). Instead of storing precise occurrence times as continuous parameters, the system encodes event states as binary parameters over defined intervals. This parameter transformation dramatically reduces data quantity while preserving the essential timing and state information needed for maintenance scheduling and equipment utilization analysis.
2Measurement precision
If cumulative time duration between events is monitored, then event duration information is captured, but storage and processing requirements increase
Solution Approach 1:
The patent extracts only the necessary state information (0 or 1) for each time interval and eliminates the need to calculate and store cumulative durations. By monitoring event states at discrete intervals rather than tracking continuous duration, the system captures event duration information implicitly through state transitions while significantly reducing processing complexity.
Solution Approach 2:
The patent implements periodic sampling of event states at defined intervals rather than continuous monitoring. This periodic action approach captures event duration information through the pattern of state changes over intervals, reducing processing requirements compared to continuous duration tracking while maintaining sufficient precision for maintenance scheduling decisions.
3Loss of information
If detailed event history data is stored, then complete event information is preserved, but data transmission bandwidth and post-processing time increase
Solution Approach 1:
The patent extracts and retains only the essential event state information (0 or 1) for each time interval, discarding redundant detailed data. This extraction maintains sufficient event information completeness for maintenance scheduling and equipment utilization analysis while dramatically reducing post-processing time requirements compared to handling detailed continuous event histories.
Solution Approach 2:
The patent transforms event history data from detailed continuous parameters to simplified binary parameters. This parameter change preserves the critical information needed for decision-making while reducing data volume, which directly decreases both transmission bandwidth requirements and post-processing time, resolving the contradiction between information completeness and processing efficiency.
Data Source
AI summary
A method for coding an event history is disclosed. Information relating to a real time state of an event is received. For a defined interval of time, it is determined whether the state of the event is in one of two states. In response to the event being in a first state, a data stream is appended with a first characteristic representative of the first state, and in response to the event being in a second different state, the data stream is appended with a second characteristic representative of the second state. The appended data stream is saved, and the process repeated for the next sequential defined interval of time.