Safety and Predictive Diagnostics

The ability to detect changes in process variables and equipment condition is vital to avoiding pump damage, environmental incidents, and negative business impact. Pump safety and monitoring systems may cause unnecessary trips and not provide accurate information regarding the health of the pump and its components, removing visibility of impending issues until after a failure has occurred.

Vibration and oil analysis for all rotating equipment results in less facility downtime and reduced maintenance costs. These unique technologies offer insight and can detect failures very early on, allowing for scheduled maintenance and root cause analysis. An integrated database for all rotating assets reduces network requirements, eliminates redundant databases, and correlates various sources of data for accurate identification of component health and informed decision making.

The AMS 6500 Machinery Health Monitor is designed for process automation and protection system upgrade projects, and combines prediction and protection in a single chassis for rotating and reciprocating assets. The AMS 6500 is fully compliant with API 670 and integrates protection, prediction, real-time performance monitoring, and process automation by preventing missed trips. Emerson’s PlantWeb digital architecture provides enterprise-wide information needed for real-time decision making.

Emerson's AMS 9420 Wireless Vibration Transmitter delivers vibration information over a highly-reliable, self-organizing wireless network for use by operations and maintenance personnel. Configuration, diagnostics, and alerts are imported into AMS Suite: Intelligent Device Manager. The AMS 9420 is ideal for vibration monitoring applications, especially in hard-to-reach or cost prohibitive locations, and provides reliability with advanced accuracy for all installations.


PROGNOST Systems GmbH provides specialized technology for asset performance management of reciprocating piston compressors. Operation and monitoring of these assets, which are often process-critical, occurs under extremely varying operating conditions. With high-frequency data recording, automated real-time diagnoses, and self-learning damage pattern recognition, PROGNOST® systems meet industry requirements and enable the linkage of component condition data with maintenance cycles to acquire life-cycle information for efficient maintenance scheduling.

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