Bridge Disease Identification: Inspection Monitoring, Alarm Judgment, and Database Operations

Bridge Disease Identification: Inspection Monitoring, Alarm Judgment, and Database Operations

Data Structure for This Category

Bridge inspection teams collect high-definition visual images, structural stress sensor data, and time-series vibration monitoring files as data sources. Update frequency aligns with on-site inspection cycles and is adjusted accordingly. Each data entry includes disease location coordinates, disease classification tags, original detection file path, detection timestamp, and unique bridge identifier. Field units cover physical quantities such as pixel coordinates, megapascals, and milliseconds. Most documents use a mix of structured JSON, unstructured images, and time-series files.

Requirements for Database and Operations Workflows

Deploy databases that support both structured queries and large file storage to handle mixed structured and unstructured data. Use a dual storage link configuration. Adjust database connection pool parameters to accommodate concurrent access peaks caused by fluctuating update frequencies tied to inspection schedules. Create targeted indexes for queries involving multi-dimensional associated fields to shorten response times. Include both structured databases and associated file storage resources in data backups. This prevents data mismatches during recovery.

Configuration Settings

Reference only; verify against the target FastGPT release and deployment documentation.

Configuration ItemRecommended ValueRationale
PG_URLpostgresql://user:pass@host:5432/bridge_disease?sslmode=disableStores structured fields including disease tags, bridge IDs, and detection times. Supports associated queries for relational data
MONGODB_URImongodb://user:pass@host:27017/bridge_filesStores unstructured inspection images and vibration monitoring time-series files. Supports large file metadata management
DB_MAX_LINK20–30Adapts to concurrent connection peaks during batch inspections. Prevents service interruptions caused by exhausted connections
REDIS_URLredis://:pass@host:6379/0Caches frequently queried disease classification mappings and basic bridge information. Reduces database access pressure
Database access whitelistInspection device IP ranges, background operation IPsOnly allows authorized devices and operation terminals to access the database. Mitigates unauthorized connection risks

Three Common Misconfigurations

  • Symptom: Database connection error with prompt Access denied for user 'xxx'@'xxx', status code 1045. Cause: The external request IP of the inspection device was not added to the database whitelist. Access was blocked.
  • Symptom: Syntax error returned during database operations, prompt You have an error in your SQL syntax, result count 0. Cause: The database was not configured to support multi-line query execution. Only single statement submissions are allowed. This prevents multi-statement scripts generated by AI from running normally.
  • Symptom: After restoring project backups, knowledge base and agent configurations do not appear. The backend prompts missing data. Cause: Only project configuration files were restored. Associated database backups and file storage data were not synchronized. This leads to mismatched business data and configurations.

How to Verify Proper Configuration

  • Run a database connection test script to verify connectivity for PG_URL and MONGODB_URI. Confirm no connection timeouts or permission errors.
  • Submit a single structured data entry and its associated image file. Verify normal data writing and correct association between entries.
  • Simulate batch inspection data submission. Monitor database connection pool usage. Confirm DB_MAX_LINK configuration adapts to concurrent peaks.
  • Trigger a database backup and recovery process. Verify that both structured data and unstructured files can be restored normally.

The values provided are common starting points. They should be evaluated against the reader's own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.