What data for this use case looks like
Data for petroleum refining scenarios originates from DCS/APC, LIMS, tank farm metering systems, crude oil evaluation systems, equipment management systems, and energy systems. Daily documents cover operating procedures for refining units, monthly production plans, daily material balance reports, distillate export quality inspection reports, interlock trigger logs, shift handover records, and process change management documents.
Data update frequencies fall into three categories: real-time, per shift, and daily. Fields include crude oil property parameters, unit operating load, product quality indicators, equipment status, and energy consumption data. Field units align with the standard metering formats of the source systems.
What constraints these characteristics impose on HTTP Interfaces and External Systems
Heterogeneous data from multiple sources requires interfaces to support connections to multiple external system endpoints, and adapt to different authentication protocols and data formats. Data sources with varying update frequencies need interfaces with flexible trigger mechanisms to match synchronization needs for real-time equipment data, shift handover records, and daily quality reports.
Document types include structured reports and semi-structured logs. Interfaces must support different request parameters and return field parsing rules. The business characteristic of coupled multiple units requires interfaces to support batch pulling of operating data for associated units, preventing information gaps in single requests.
How to configure settings
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
Authorization | Use the Bearer ${appKey} format carrying an application-level API Key | Adapts to FastGPT v4.17.0 application call authentication rules, avoids permission overreach caused by using global account keys |
variables | Configure business parameters such as crude oil API gravity and unit load thresholds, with values set via on-site calibration | Adapts to personalized refining process business logic, binds on-site data with process rules |
responseData | Filter return fields to distillate export quality, interlock status, and tank farm liquid level, retain the first 200 valid data entries | Streamlines return content, reduces transmission overhead, and matches core data requirements for process document drafting |
| Request timeout period | 60–120 seconds | Matches average response duration for data pulling from refining systems, prevents request interruptions caused by large unit data volumes |
| Number of retries on failure | 2–3 times | Addresses request failures from temporary DCS system fluctuations, ensures stable data pulling |
Three common configuration mistakes
- Symptom: Errors such as
400 do request failed: Post "https://xxx dial tappear, or a key error is triggered. Cause: A global account key was incorrectly used as the application call key, and the dedicated API Key for the target application was not utilized. - Symptom: The interface returns missing or incomplete data fields. Cause: Valid fields were not filtered using the
responseDataconfiguration, leading to the pulling of redundant non-process-related data and subsequent parsing failure. - Symptom: Interface calls consume global API quota. Cause: Authentication parameters were not configured correctly, and the global account authentication method was used, resulting in incorrect quota occupation.
How to confirm successful configuration
- Call the test interface, verify that the request header carries authentication information for the application-level API Key, with no global account identifiers present.
- Review the
responseDatafield returned by the interface, confirm that it only includes core data such as crude oil properties, unit load, and quality indicators required for process documents and abnormal reports. - Simulate a temporary disconnection of the external system, confirm that the interface triggers 2–3 retries before returning a reasonable failure prompt, and does not directly interrupt the call process.
- Simulate a high-volume data request, confirm that the request is not forcibly terminated within the set timeout period, and completes data pulling.
The values provided here are common starting points and should be measured against the reader's own samples.