Hydraulic Pump Load Gating for Construction Machine Engine Diagnosis
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Solution Overview
Problem
Existing engine diagnosing technologies for construction machines, such as hydraulic excavators, face challenges in accurately determining engine degradation while minimizing costs, as they require large volumes of data and sophisticated controllers, leading to increased communication costs and potential measurement errors due to varying work loads and site conditions.
Innovation Solution
A construction machine equipped with a controller that determines the hydraulic pump's loaded state to acquire diagnosis data, validates torque command variables, and generates time history data for engine diagnosis, reducing data volume and suppressing noise to improve diagnosis accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If long-term frequency distribution information is accumulated and compared to detect engine degradation, then diagnosis accuracy is improved, but data volume and memory requirements increase significantly
Solution Approach 1:
The patent extracts only the necessary diagnostic information (engine output power intensity and occurrence frequency) from the hydraulic pump control data, rather than accumulating and storing all raw frequency distribution information. This extraction approach maintains diagnostic accuracy while significantly reducing the volume of data that needs to be stored and processed.
Solution Approach 2:
The patent performs preliminary processing of control data to generate engine output power intensity and occurrence frequency information before storage. By pre-processing the data to extract only diagnostic-relevant features, the system avoids the need to store large volumes of raw data while maintaining the capability to detect engine degradation accurately.
2Measurement precision
If sophisticated controllers are used to process large volumes of diagnostic data, then diagnosis capability is improved, but system cost increases
Solution Approach 1:
The patent extracts only the essential diagnostic parameters (engine output power intensity and occurrence frequency) from the control data, eliminating the need for sophisticated controllers to process entire datasets. This extraction reduces computational requirements and allows simpler, more cost-effective controller implementations.
Solution Approach 2:
The patent performs preliminary data processing to generate condensed diagnostic information before it reaches the controller. This pre-processing step reduces the computational burden on the controller, enabling the use of simpler, less expensive control units while maintaining diagnostic capability.
3Loss of information
If large volumes of diagnostic data are transmitted via wireless communication, then remote analysis capability is improved, but communication cost increases
Solution Approach 1:
The patent extracts only the critical diagnostic information (engine output power intensity and occurrence frequency) for transmission, rather than sending complete frequency distribution datasets. This extraction dramatically reduces communication bandwidth requirements and associated costs while maintaining the ability to perform remote engine degradation analysis.
Solution Approach 2:
The patent performs preliminary processing and condensation of diagnostic data before transmission. By pre-processing the data to retain only essential diagnostic features, the system minimizes communication costs and energy consumption while preserving remote analysis capability.
4Measurement precision
If frequency distribution information is accumulated over long periods, then engine degradation trend detection is improved, but measurement uncertainty from varying work loads increases
Solution Approach 1:
The patent applies local quality by focusing analysis on specific, relevant parameters (engine output power intensity and occurrence frequency) rather than attempting to analyze all aspects of frequency distribution data. This focused approach reduces the influence of varying work loads on measurement uncertainty while maintaining the ability to detect degradation trends.
Solution Approach 2:
The patent performs preliminary processing to generate occurrence frequency information that normalizes the data against varying work loads. This pre-processing step reduces measurement uncertainty caused by different operating conditions while preserving the ability to detect true engine degradation trends over time.
Data Source
AI summary
A cost required to perform the diagnosis of the degradation such as a reduction in output power of an engine while engine degradation diagnosis accuracy is improved. To this end, a controller 37 (engine diagnosing device) determines whether a hydraulic pump 12 is in a preset loaded state (an operation scene where a load torque of the hydraulic pump 12 is in a stable state) for acquiring diagnosis data of an engine 10, and validates a controlled variable related to a torque command value Ta of speed sensing control as the diagnosis data of the engine 10 when it is determined that the hydraulic pump 12 is in the present loaded state, generates time history data using this validated controlled variable as a current feature variable, and enables this time history data to be displayed as trend data for engine diagnosis on a display device 38.