Endress+Hauser CPS11E-GR7AAA4

Digital pH sensor Memosens CPS11E

The Memosens CPS11E is a digital pH sensor designed for standard applications in process and water & wastewater industries. It features Memosens 2.0 digital technology, which enhances process safety and simplifies operation by resisting moisture and enabling lab calibration.

Datasheet:

• Measuring Principle: Potentiometric (pH measurement)

• Measuring Range:

  • Application A: pH 1 to 12

  • Application B: pH 0 to 14

  • Application F: pH 0 to 10

• Process Temperature Range:

  • Application A: -15 to 80 °C (5 to 176 °F)

  • Application B: 0 to 135 °C (32 to 275 °F)

  • Application F: 0 to 70 °C (32 to 158 °F)

• Process Pressure Range: 0.8 to 17 bar (11.6 to 246.5 psi) absolute

• Wetted Materials:

  • Liner: PFA

  • Electrodes: 1.4435 (316L), Alloy C22, Tantalum, Platinum

• Outputs: 4-20 mA HART (active/passive), Pulse/frequency/switch output, Modbus RS485, 4-20 mA

• Digital Communication: HART, MODBUS RS485

• Power Supply: DC 24 V, AC 100 to 230 V, AC 100 to 230 V / DC 24 V (non-hazardous area)

• Hazardous Area Approvals: ATEX, IECEx, cCSAus, EAC, NEPSI, INMETRO, KC, JPN, UK Ex

• Degree of Protection: IP66/67, Type 4X enclosure

• Display/Operation: Integrated temperature measurement, sensor housing made of stainless steel (3A, EHEDG), wetted materials CIP, SIP cleanable, robust, ultra-compact transmitter housing, high ingress protection: IP69K, pre-configured plug connector

Advantages:

• Hygienic Design: Suitable for demanding applications with high hygiene requirements.
• Energy Efficiency: No pressure loss due to cross-section constriction.
• Maintenance-Free: No moving parts, ensuring long-term reliability.
• Diagnostic Information: Full access to process and diagnostic data through numerous I/Os and Ethernet.
• Heartbeat Technology: Integrated verification for compliance and process safety.
• Flexible Installation: Numerous hygienic process connections and remote display options.
• IIoT Ready: Extended storage of calibration and process data, enabling better trend identification and providing a future-proof basis for predictive maintenance and enhanced IIoT services.