Abstract: Stiction analysis of a conventional or legacy valve operation in a fluid process plant is described. The method includes receiving a series of setpoint signals, SP, generating, by the controller, a series of controller output signals, OP, driving the valve operation by applying the OP, to the valve, measuring a series of process variable signals, PV, downstream of the valve, receiving the series of process variable signals at the controller, performing inverse modelling on the PV, to estimate a manipulated variable, , receiving and analyzing by a system processor, the SP, the OP, and the , and outputting the estimated stick values, S, the estimated jump values, J, an average of the estimated stick values, an average of the estimated jump values, a confidence interval for the average of the stick values, and a confidence interval for the average of the jump values.

Abstract: Methods and systems for optimizing the gas-oil separation plant (GOSP) operating parameters in order to maximize the stabilized crude oil recovery in an integrated framework of GOSP operation. The ambient temperature variations daily (day and night) and seasonal (summer and winter) are incorporated to show their impact on liquid recovery. An artificial intelligence model predicts stabilized crude oil recovery for a range of ambient temperatures. The optimal GOSP separator pressures which yield maximum stabilized crude oil recovery are determined for each ambient temperature. The separator pressures of the GOSP may be adjusted to achieve the maximum stabilized crude oil recovery under changing ambient temperatures.

Abstract: A method and system for compensating for stiction of a control valve in a pneumatically controlled valve system. A digital twin model of the pneumatically controlled valve system is generated. A current segment of data signals is received from a process measurement device connected to the pneumatically controlled valve system. Operation of the pneumatically controlled valve system is monitored by comparing the current segment to the digital twin model. Stiction is detected when the digital twin model directly detects stiction or when the nonlinearity and Gaussian index are above a certain threshold. A severity of the stiction is determined. Instructions for a stiction control device are used to generate control signals to be applied to the actuator to compensate for the severity of the stiction. Further, the digital twin model is displayed with a representation of the severity of the stiction.

Abstract: A method of determining a fouling location of a shell and tube heat exchanger is provided. Under the method, a simulation model of the heat exchanger is partitioned into multiple segments. Each segment corresponds to a different one of multiple operating scenarios of the heat exchanger. For each operating scenario, temperature data and pressure drop data are generated from the simulation model of the heat exchanger. The fouling location of the heat exchanger corresponds to a respective segment in each of the multiple operating scenarios. The temperature data and the pressure drop data are classified based on the multiple segments of the simulation model by inputting the temperature data and the pressure drop data to one or more machine learning classification algorithms. The fouling location and a value of accumulated fouling at the fouling location are determined based on the classified temperature data and the classified pressure drop data.

Abstract: A method and system for compensating for stiction of a control valve in a pneumatically controlled valve system. A digital twin model of the pneumatically controlled valve system is generated. A current segment of data signals is received from a process measurement device connected to the pneumatically controlled valve system. Operation of the pneumatically controlled valve system is monitored by comparing the current segment to the digital twin model. Stiction is detected when the digital twin model directly detects stiction or when the nonlinearity and Gaussian index are above a certain threshold. A severity of the stiction is determined. Instructions for a stiction control device are used to generate control signals to be applied to the actuator to compensate for the severity of the stiction. Further, the digital twin model is displayed with a representation of the severity of the stiction.

Abstract: In a method for failure, detection, operational data from a plurality of components in a system are received. A bank of submodels is created based on the operational data. The bank of submodels corresponds to a normal mode and one or more faulty modes of the system and is valid in different operating regimes of the system. Each of the banks of submodels has a respective weight (validity) and a respective suboutput. An output of the system is a weighted sum of the suboutputs of the submodels. The operational data is therefore processed to generate a validity profile through a constrained Kalman Filter (KCF) based multimodel fault detection and diagnosis (FDD). Subsequently, the validity profile is output. The validity profile is indicative of an operation state of the system at a given time, and the operation state includes a normal state and a fault state.

Abstract: This disclosure presents methods and systems of controlling a counter flow double pipe heat exchanger (DPHE) that includes a hot fluid pipe and a cold fluid pipe. In a method, a temperature error between a reference temperature and a temperature at an outlet of the hot fluid pipe of the counter flow DPHE is determined. A cold fluid mass flow rate is determined from an output of a proportional-integral-derivative (PID) controller based on the temperature error being input to the PID controller. The cold fluid mass flow rate is used for a cold fluid in the cold fluid pipe of the counter flow DPHE. The temperature error is controlled within a predefined range by utilizing parameters of the PID controller that are set by using a harmony search algorithm (HSA) to obtain a minimization of a cost function.

Abstract: Methods and systems for optimizing the gas-oil separation plant (GOSP) operating parameters in order to maximize the stabilized crude oil recovery in an integrated framework of GOSP operation. The ambient temperature variations daily (day and night) and seasonal (summer and winter) are incorporated to show their impact on liquid recovery. An artificial intelligence model predicts stabilized crude oil recovery for a range of ambient temperatures. The optimal GOSP separator pressures which yield maximum stabilized crude oil recovery are determined for each ambient temperature. The separator pressures of the GOSP may be adjusted to achieve the maximum stabilized crude oil recovery under changing ambient temperatures.

Abstract: In a method for failure detection, operational data from a plurality of components in a system are received. A bank of submodels is created based on the operational data. The bank of submodels corresponds to a normal mode and one or more faulty modes of the system and is valid in different operating regimes of the system. Each of the banks of submodels has a respective weight (validity) and a respective suboutput. An output of the system is a weighted sum of the suboutputs of the submodels. The operational data is therefore processed to generate a validity profile through a constrained Kalman Filter (KCF) based multimodel fault detection and diagnosis (FDD). Subsequently, the validity profile is output. The validity profile is indicative of an operation state of the system at a given time, and the operation state includes a normal state and a fault state.

Abstract: A pneumatic valve system that includes an actuator that pneumatically actuates a valve, and circuitry that calculates a control signal to control the actuator by compensating for nonlinear dynamic of the actuator using a stable inverse model of the valve, optimizes parameters of the stable inverse model such that a difference between output information of the pneumatic valve system and desired reference information is reduced, and outputs the control signal to control the actuator.

Abstract: A pneumatic valve system that includes an actuator that pneumatically actuates a valve, and circuitry that calculates a control signal to control the actuator by compensating for nonlinear dynamic of the actuator using a stable inverse model of the valve, optimizes parameters of the stable inverse model such that a difference between output information of the pneumatic valve system and desired reference information is reduced, and outputs the control signal to control the actuator.

Abstract: A pneumatic valve system that includes an actuator that pneumatically actuates a valve, and circuitry that calculates a control signal to control the actuator by compensating for nonlinear dynamic of the actuator using a stable inverse model of the valve, optimizes parameters of the stable inverse model such that a difference between output information of the pneumatic valve system and desired reference information is reduced, and outputs the control signal to control the actuator.

Abstract: A pneumatic valve system that includes an actuator that pneumatically actuates a valve, and circuitry that calculates a control signal to control the actuator by compensating for nonlinear dynamic of the actuator using a stable inverse model of the valve, optimizes parameters of the stable inverse model such that a difference between output information of the pneumatic valve system and desired reference information is reduced, and outputs the control signal to control the actuator.