> For the complete documentation index, see [llms.txt](https://infosys.selmotech.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://infosys.selmotech.com/selmo-solution/selmo-solution-en/selmo-documentation/7-safety-and-monitoring/pair-check-and-additional-checks.md). # Pair-check & additional checks ### Physical plausibility Besides interlocks (`i`) and CMZ there are other monitoring mechanisms that do not control the sequence and do not secure system integrity, but rather **monitor the physical plausibility of states**. These checks ensure that **impossible or contradictory states** are detected and clearly diagnosed. *** ### Goal of physical plausibility checks Plausibility checks answer the question: > **Can this signal state even exist in the real world?** They serve to: * detect faulty sensors * reveal wiring errors * make mechanical defects visible * explicitly test implicit assumptions The following applies: > **A physically impossible state**\ > **is always an error – regardless of the sequence.** *** ### Pair-Check #### Basic principle The **Pair-Check** monitors **related signals**,\ whose simultaneous occurrence is physically impossible. Typical examples: * Cylinder **end position front** and **end position rear** active at the same time * Valve **open** and **closed** reported simultaneously * Axis **position reached left** and **right** simultaneously These signals are defined as **pair** . *** #### Behavior of the pair check If an impossible state is detected: * the sequence is not continued * the state is recognized as faulty * a **clear diagnosis** is generated The pair check: * interprets nothing * corrects nothing * does not decide on the sequence > **It merely determines that**\ > **reality contradicts the model.** *** ### Pair check in the model context The pair check is: * bound to **zones** independent of the current state * not state-dependent like an interlock * not system-wide like a CMZ * It thus complements: Interlock → logical consistency * CMZ → system integrity * Pair-Check → * physical plausibility **Other plausibility checks** *** ### In addition to the pair check, further checks can be defined, e.g.: Processing check #### Monitoring that a processing operation only takes place under physically sensible conditions. Processing only at reached position Examples: * Processing only with active tool * Processing not when the medium is stationary * Consistency checks *** #### Monitoring logical relationships between signals. Feedback without prior actuation Examples: * State change without possible cause * Signal change outside physical time limits * Automatic diagnosis *** ### All plausibility checks generate automatic diagnosis **This diagnosis:**. points to the affected zone * describes the contradictory state * is independent of the operator * is not interpretation-dependent * no manual fault assignment There are: * no aggregated messages * no tacit corrections * The diagnosis names the impossible state – > **not a suspected cause.**\ > **Distinction from other safety mechanisms** *** ### Pair check & other checks For clear classification: * **check physical plausibility** * operate independently of the sequence * generate diagnosis * checks sequence conditions * **Interlock (`i`)** * acts state-dependently * protects system integrity * **CMZ** * prevents any movement * Plausibility checks: do not replace safety * do not replace interlocks * do not replace CMZ * They complement **the model with verifiable reality.** Typical mistakes in dealing with plausibility checks *** ### Using plausibility checks as sequence control Common mistakes are: * compensating missing checks with logic * tolerating impossible states * suppressing or summarizing diagnosis * What is physically impossible Rule of thumb: > **must not be silently accepted in the model.**\ > **Pair check & other plausibility checks:** *** ### Summary detect impossible states * make physical contradictions visible * produce automatic, unambiguous diagnosis * increase robustness and explainability * Plausibility checks ensure that > **the model fits reality –**\ > **or the deviation is clearly named.**\ > **or the deviation is clearly named.** --- # Agent Instructions This documentation is published with GitBook. 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