Abstract: A furnace is monitored by monitoring a statistical variable calculated from a draft measurement and monitoring a process variable related to the operation of the furnace. An abnormal operation of the furnace is determined based upon the statistical variable and the process variable.

Abstract: Methods and apparatus are disclosed for detecting and preventing compressor surge. A transmitter determines a derivative process value of a compressor. A controller obtains the derivative process value from the transmitter. The transmitter is separate from the controller. The controller compares the derivative process value to a threshold value. The threshold value is indicative of the initiation of a surge event in the compressor. In response to determining that the derivative process value fails to satisfy the threshold value, the controller actuates a valve operatively coupled to the compressor to enable an additional derivative process value of the compressor determined by the transmitter to satisfy the threshold value.

Abstract: Methods and apparatus are disclosed for detecting and preventing compressor surge. A transmitter determines a derivative process value of a compressor. A controller obtains the derivative process value from the transmitter. The transmitter is separate from the controller. The controller compares the derivative process value to a threshold value. The threshold value is indicative of the initiation of a surge event in the compressor. In response to determining that the derivative process value fails to satisfy the threshold value, the controller actuates a valve operatively coupled to the compressor to enable an additional derivative process value of the compressor determined by the transmitter to satisfy the threshold value.

Abstract: Systems and methods to monitor pump cavitation are disclosed. An example method includes monitoring a pressure parameter and a vibration parameter associated with an asset in an operating process unit. The example method includes calculating a manipulated pressure value based on the pressure parameter. The example method includes calculating a manipulated vibration value based on the vibration parameter. The example method includes determining a state of cavitation associated with the asset based on at least one of the manipulated pressure value or the manipulated vibration value.

Abstract: A furnace is monitored by monitoring a statistical variable calculated from a draft measurement and monitoring a process variable related to the operation of the furnace. An abnormal operation of the furnace is determined based upon the statistical variable and the process variable.

Abstract: Systems and methods to monitor pump cavitation are disclosed. An example method includes monitoring a pressure parameter and a vibration parameter associated with an asset in an operating process unit. The example method includes calculating a manipulated pressure value based on the pressure parameter. The example method includes calculating a manipulated vibration value based on the vibration parameter. The example method includes determining a state of cavitation associated with the asset based on at least one of the manipulated pressure value or the manipulated vibration value.

Abstract: In a method for monitoring a control loop in a process plant, process gain data associated with a control loop may be collected. The collected process gain data may be used to determine an expected process gain behavior. For example, expected values of a process variable for given values of a load variable may be determined. As another example, expected changes in a process variable for given changes in a load variable may be determined. Then, during operation of the control loop, the process gain may be monitored. If the monitored process gain substantially deviates from the expected behavior, this may indicate an abnormal situation associated with the control loop.

Abstract: A system for detecting abnormal situations associated with a heater in a process plant receives statistical data associated with the heater unit. The statistical data is analyzed to detect whether one or more abnormal situations associated with the heater exist. The statistical data may comprise statistical data generated based on pressure variables sensed by one or more pressure sensors associated with a furnace, a stack, a fuel supply, etc., associated with the heater. Additionally, the statistical data may comprise statistical data generated based on temperature variables sensed by one or more temperature sensors associated with the furnace, the stack, etc. If an abnormal situation is detected, an indicator of the abnormal situation may be generated.

Abstract: A system and method to facilitate the monitoring and diagnosis of a process control system and any elements thereof is disclosed with a specific premise of abnormal situation prevention in a coker heater of a coker unit in a product refining process. Monitoring and diagnosis of faults in a coker heater includes statistical analysis techniques, such as regression. In particular, on-line process data is collected from an operating coker heater in a coker area of a refinery. A statistical analysis is used to develop a regression model of the process. The output may use a variety of parameters from the model and may include normalized process variables based on the training data, and process variable limits or model components. Each of the outputs may be used to generate visualizations for process monitoring and diagnostics and perform alarm diagnostics to detect abnormal situations in the process.