What the Data for This Category Looks Like
Data sources for automated equipment intelligent due diligence include equipment manufacturer factory parameter documents, on-site operation and maintenance ledger databases, third-party quality inspection reports, and industry compliance inspection records. Data update rhythms vary:
- Factory parameters are static fixed data, updated only during device firmware upgrades or model iterations
- Operation and maintenance ledgers are time-series data, synced in daily batches or real-time single entries
- Quality inspection reports are batch data, updated upon completion of each batch of device factory inspections
Document structures fall into three categories: structured parameter tables (including fields such as device model, rated power, operating limits), semi-structured PDF inspection reports (including content such as fault records, calibration cycles, qualification marks), and time-series operation and maintenance logs (including statistical items such as cumulative operating duration, number of fault occurrences). Field units include physical measurement and time units such as kW, h, times, and month.
Constraints These Characteristics Impose on the Model Integration and Configuration Link
Multi-source heterogeneous data structures require configuring multi-table association rules. Without these rules, scattered device parameters, operation and maintenance data, and compliance records cannot be integrated into a complete due diligence report. Data with different update rhythms require differentiated pull strategies. Static parameters need full synchronization to ensure initial data completeness. Time-series data needs incremental synchronization to reduce resource usage and data latency. Failure to follow these rules will result in data redundancy or missing values. Diverse unit fields require configuring unified mapping rules. This prevents model-extracted parameters from being unable to be aggregated and analyzed due to inconsistent units. Semi-structured PDF reports require configuring parsing timeout and segmentation rules. This avoids long document parsing failures or key information being truncated. Mandatory verification of compliance fields requires configuring field matching thresholds. This ensures extracted information such as calibration dates and qualification marks meets industry regulatory requirements.
How to Define Configuration Values
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
multi_source_table_join | Enabled, associate operation and maintenance, quality inspection, and parameter tables by device ID | Device data is scattered across multiple independent ledger databases, and a unique identifier is required to complete data integration |
data_update_strategy | Pull static parameters in full, pull operation and maintenance data in 1-hour increments | Matches the update rhythms of different data sources, reduces resource usage and data latency |
unit_mapping_config | Uniformly map to standard units such as kW, h, times, month | Eliminates unit differences across data sources, ensuring model-extracted parameters can be analyzed uniformly |
parse_pdf_timeout | 600 seconds | Adapts to the parsing time of long-page quality inspection reports, preventing task termination due to mid-run timeout |
context_window_size | 800–1200 characters | Matches the average length of device parameter documents, avoiding context truncation or redundancy |
similarity_threshold | 0.75–0.85 | Balances the extraction accuracy and recall rate of compliance fields, ensuring key information is not lost |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to conduct tests on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Unable to view table models defined in each database, with the interface returning an empty list. Cause: Database connection schema permissions are not configured, and metadata read permissions for the corresponding device ledger database are not granted.
- Local model startup fails, with logs containing the
model-uid invaliderror. Cause: The service was not started with the correct model UID parameter, or the model has not completed local deployment verification. - Parsing a device PDF report returns a
504 Gateway Timeouterror. Cause: Theparse_pdf_timeoutsetting is too low, failing to adapt to the parsing time of long documents.
How to Confirm Successful Configuration
- Run a multi-source table association test, verify whether the association results between device parameters and operation and maintenance data meet expectations, and adjust the association rules for
multi_source_table_join. - Trigger a single PDF quality inspection report parsing task, verify whether the parsing time matches the configured
parse_pdf_timeoutthreshold, and adjust the timeout setting. - Test the extraction accuracy of compliance fields by the model, adjust the value of
similarity_thresholdto match business requirements. - Call the database metadata reading interface, confirm that table models from each database can be returned normally, and verify the database connection permission configuration.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.