Can the Recording Interval Be Configured Per Tag in OPC Expert, and Are Compression or Exception Algorithms Available?
OPC Expert supports per-item update rate configuration in the Archive OPC Data module, meaning each subscribed tag can be assigned its own capture frequency independently of other tags in the same archive. For compression and exception reporting, OPC Expert relies on a combination of event-based (on-change) capture at the archive level and OPC deadband settings negotiated with the OPC server at the subscription level. Together, these mechanisms deliver behavior comparable to exception and compression algorithms found in dedicated process historians, without requiring a separate historian product.
Per-Tag Update Rates in Archive OPC Data
When configuring an archive in OPC Expert, the update rate for data capture can be set individually for each item. One tag might write a new record every 500 milliseconds while another writes every 10 minutes, reflecting the different rates of change and analytical requirements for each measurement. This flexibility allows engineers to prioritize storage for fast-moving critical variables while minimizing storage consumption for slow or infrequently changing parameters.
Configuration can be performed through the interface directly or by importing a CSV file that specifies update rates for each tag. For large installations with hundreds of tags, the CSV approach makes it practical to define and maintain per-tag settings without working through the interface item by item.
Event-Based Capture as an Exception Mechanism
Traditional historian compression algorithms, such as swinging door or exception reporting, determine whether a new value is sufficiently different from the last stored value to warrant writing a new record. OPC Expert’s event-based capture mode achieves a similar outcome: a record is written only when the subscribed value changes. When combined with the OPC server’s deadband setting, which filters out changes smaller than a configured threshold before they are even sent to OPC Expert, the result is a storage pattern that closely mirrors exception reporting behavior.
The deadband is configured at the OPC subscription level. OPC DA and OPC UA both support deadband as part of the subscription negotiation, meaning the OPC server itself performs the filtering before transmitting updates. Only changes that exceed the deadband reach OPC Expert, and from there, event-based capture ensures that only those qualifying changes are written to storage. Engineers familiar with historian exception parameters will recognize this as functionally equivalent, even though the terminology differs from products like AVEVA PI or Aspen InfoPlus.21.
Practical Implications for Storage Management
For a typical process with analog measurements that vary gradually, the combination of a well-configured deadband and event-based capture can reduce stored record volume by a significant factor compared to time-based polling at a fixed rate. The archive accurately represents the shape of the process trend because every meaningful deviation is captured, while stable periods generate few or no records.
For discrete or digital tags that transition between a small number of states, event-based capture is a natural fit regardless of deadband settings, since each state change is inherently meaningful and the rate of change is typically low enough that storage impact is minimal.
Relevant Tools
Archive OPC Data handles per-item update rate configuration and event-based capture, writing data to CSV, SQL, and cloud destinations. OPC Viewer provides a way to verify subscription behavior and confirm that deadband settings are being honored by the connected OPC server before archiving is enabled.
Summary
OPC Expert supports per-tag recording intervals through individual update rate configuration in Archive OPC Data. Compression and exception-style behavior is achieved through the combination of OPC server-side deadband settings and event-based capture at the archive level, producing a storage-efficient record that captures meaningful process changes without requiring a dedicated historian product or custom compression algorithm configuration.