Invensys Systems, Inc.

Schneider Electric Systems Usa, Inc.

Ivensys Systems, Inc.

Ajay P Mishra

Diana Ivanov

Erna Banchik

Jeffrey Norris

Peter G Martin

David C Rasmussen

David R Brown

John Carl Gabler

Jeffrey A Norris

Matthew C Meyer

Steve Elliott

Peter P Kral

Francis W Walker, Jr

Shahid Ansari

Kevin Hudson

Murugananth Muthuramalingam

Huan V Nguyen

Gary T Hufton

Anupam Saurabh

John A DiBartolomeo

Michael Kieu

Jr Francis W Walker

Network of safety PLCs employs multi-PLC verification of a programming application before allowing the application to reprogram any PLC on the safety network. Each PLC on the safety network is equipped with authentication capability that detects attempts to reprogram the PLC and issues an authentication challenge requiring the programming application to process a proof-of-work. The authentication challenge is also sent to other PLCs on the safety network along with the response from the programming application for verification purposes. The other PLCs process the authentication challenge and check the response from the programming application for acceptability. If a majority of the PLCs on the safety network determines the response from the programming application is correct, then the programming application is verified and may proceed with the reprogramming. Such group authentication requires a malicious application to hijack multiple PLCs concurrently on the safety network, a highly unlikely outcome, before reprogramming any PLC.

Secure network of safety PLCs for industrial plants

A method for managing soft errors associated with one or more safety programmable logic controllers (PLCs) is provided. The method includes receiving an expected soft error rate for type(s) of input/output (I/O) modules over time, receiving respective soft error data that was aggregated by the respective safety PLCs based on soft errors detected by I/O modules coupled to the respective safety PLCs. Actual soft error rates are determined per I/O module type based on the received soft error data, and soft error rates are predicted for the safety PLC(s) per I/O module type. The actual and/or predicted soft error rates are compared to the expected soft error rate per I/O module type. The method further includes taking one or more actions in response to a threshold deviation between the actual and/or predicted soft error rates relative to the expected soft error rate for the corresponding I/O module type.

Soft error aggregation method for detection and reporting of risks in a safety instrumented system

A method is provided for automatically or semi-automatically analyzing process hazards and validating protection mechanisms for an industrial process. The method can involve establishing communication between a simulation tool and a process hazard analysis tool. The simulation tool simulates operation of the process according to a process model. The method can further involve creating, using the process hazard analysis tool, conditions for hazards in the process based on information learned about the industrial process from the simulation tool; for each of the hazards, simulating the hazards using the simulation tool and attempting to prevent the hazards using the process hazard analysis tool by introducing protective mechanism(s) to the process; and evaluating effectiveness of the introduced protective mechanisms for each of the hazards and creating safety requirements for the process based on the evaluated effectiveness. The safety requirements are used to generate a safety application program, such as for a PLC.

Method and apparatus to automate process hazard, LOPA and safety PLC application program validation for safety instrumented systems

Systems and methods for measuring rotational frequency in rotating machines use variable sliding windows of measurement. The systems and methods count and store the number of internal clock cycles between the start of a measurement interval and each pulse signal from a pulse generator. Rotational frequency is determined by taking a difference between the count for a most recent pulse signal and the count for some previous pulse signal within the measurement interval. The number of pulse signals that have occurred between the most-recent pulse signal and the previous pulse signal represents a window of measurement. This window of measurement, or the size thereof, may then be used along with the count difference to determine the rotational frequency. The window of measurement may then be slid to the counts for next most recent pulse signal and the next previous pulse signal to obtain a new count difference, and so on.

Low latency variable rotational frequency measurements

A fault tolerant control system delivers an embedded functional safety core and a distributed control engine with an onboard communication link in an industrial process control environment. The fault tolerant control system includes a process control workstation connected to a first network and a fault tolerant safety controller connected to a second network, wherein a process controller module, a safety controller module and a field device system integration module are co-located on a power interface board.

Unified communications module (UCM)

A system and method assesses and manages risk of an operation of a user. A rules engine of computer executable instructions stored in the storage device determines at least one of a safety risk measurement based on key performance indicators, an operational safety risk measurement for the operation as a function of the operational safety risk measurement information stored in a storage device and/or a conditional safety risk measurement for the operation as a function of the conditional safety risk measurement information stored in the storage device. A processor connected to the storage device executes the rules engine. An output interface connected to the processor indicates the determined safety risk for the operation.

Real time safety management system and method

In a nuclear process control system, a priority logic module (PLM) is provided. The priority logic module comprises a plurality of input ports, each input port associated with one of a plurality of priorities, a plurality of output ports, and a test mode select port associated with a test mode select signal. The test mode select signal selects one of a normal mode or test mode, each mode being associated with matching signals received by the input ports to signals sent by the output ports. The priority logic module further comprises a configurable priority logic circuit, wherein the priority logic circuit maps one of the input ports to one of the output ports.

Priority logic module

An apparatus comprises an edge detector, a memory and a pulse-input engine. The edge detector is configured to receive an input signal and a counter signal. The edge detector is further configured to send a set of time values based on the input signal and the counter signal. Each time value from the set of time values is uniquely associated with a detected edge transition from the input signal. The memory is coupled to the edge detector. The memory is configured to receive from the edge detector the set of time values. The memory is configured to store the set of time values. The pulse-input engine is coupled to the memory. The pulse-input engine is configured to measure a set of pulse-to-pulse delays based on the set of the time values stored in the memory.

Fault tolerant apparatus and method for determining a revolution rate of a gear

A measurement system and method for determining a revolution rate of a rotating gear is described. Such a rotating gear can be, for example, a turbine or compressor. The described measurement system and method, for example, can perform highly accurate measurements and can be a fault tolerant system providing high reliability. In one embodiment, an apparatus comprises an edge detector, a memory and a pulse-input engine. The edge detector is configured to receive an input signal and a counter signal. The edge detector is further configured to send a set of time values based on the input signal and the counter signal. The pulse-input engine is configured to measure a set of pulse-to-pulse delays based on the set of time values stored in the memory.

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Irvine, CA, United States of America

Ajay P Mishra