Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable. Multivariate process data includes multiple process variables each having a multiple observations. On-line process data is collected from a process control system when the process is on-line. The on-line process data includes multiple observations of multiple process variables. A multivariate statistical analysis represents the operation of the process based on a set of the on-line process data. The representation a result. The representation and the set of on-line process data are stored. An output is generated based on a parameter of the representation. The parameter includes a result generated by the representation of the operation of the process, a process variable used to generate the representation of the operation of the process and/or the set of collected on-line process data.

Abstract: A method and system for monitoring a process in a process plant includes collecting data from a process control system within the process plant, where the data is representative of a normal operation of the process when the process is on-line and operating normally, performing a multivariate statistical analysis to represent the normal operation of the process based on a set of collected on-line process data comprising a measure of the normal operation of the process when the process is on-line and operating normally, and representing a real-time on-line operation of the process using monitored on-line process data as an input to the representation of the normal operation of the process, where the monitored on-line process data comprises a measure of a real-time operation to the process when the process is on-line.

Abstract: Methods and systems to detect transient operations from abnormal operations, and to detect abnormal operations in a coker heater, include collecting on-line process data. The collected on-line process data is generated from a plurality of process variables of the process, or coker heater. A first representation of the operation of the process, or coker heater, is generated based on a first set of the collected on-line process data generated from a first set of the process variables. The first representation is adapted to be executed to generate a first result. A second representation of the operation of the process, or coker heater, is generated based on the first result and based on a second set of the collected on-line process data generated from a second set of the process variables. The second representation is adapted to be executed to generate a prediction of data generated from the second set of the process variables.

Abstract: Methods and systems to detect abnormal operations in a process of a process plant include collecting on-line process data. The collected on-line process data is generated from a plurality of dependent and independent process variables of the process, such as a coker heater. A plurality of multivariate statistical models of the operation of the process are generated using corresponding sets of the process data. Each model is a measure of the operation of the process when the process is on-line at different times, and at least one model is a measure of the operation of the process when the process is on-line and operating normally. The models are executed to generate outputs corresponding to loading value metrics of a corresponding dependent process variable, and the loading value metrics are utilized to detect abnormal operations of the process.

Abstract: A method and system of monitoring multivariate process data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes defining each process variable as a process variable vector comprising a set of observation components, where the set of observation components comprises time dependent process data corresponding to the observations of the process variable, calculation, a multivariable transformation as a function of a plurality of process variable vector transformation each corresponding to one of the process variables, where each process variable vector transformation is a function of a univariate variable unifying the process variables, and representing the operation of the process based on the multivariable transformation, where the representation of the operation of the process designates a multivariate projection of the process data by the univariate variable for each of the process variables.

Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes collecting on-line process data from a process control system within the process plant when the process is on-line, where the collected on-line process data comprises a plurality of observations of a plurality of process variables and where the plurality of observations of the set of collected process data comprises a first data space having a plurality of dimensions, performing a multivariate statistical analysis to represent the operation of the process based on a set of collected on-line process data comprising a measure of the operation of the process when the process is on-line within a second data space having fewer dimensions than the first data space, performing a univariate analysis to represent the operation of the process as a multivariate projection of the on-l

Abstract: Methods and systems to detect transient operations from abnormal operations, and to detect abnormal operations in a coker heater, include collecting on-line process data. The collected on-line process data is generated from a plurality of process variables of the process, or coker heater. A first representation of the operation of the process, or coker heater, is generated based on a first set of the collected on-line process data generated from a first set of the process variables. The first representation is adapted to be executed to generate a first result. A second representation of the operation of the process, or coker heater, is generated based on the first result and based on a second set of the collected on-line process data generated from a second set of the process variables. The second representation is adapted to be executed to generate a prediction of data generated from the second set of the process variables.

Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes collecting on-line process data from a process control system within the process plant when the process is on-line, where the collected on-line process data comprises a plurality of observations of a plurality of process variables and where the plurality of observations of the set of collected process data comprises a first data space having a plurality of dimensions, performing a multivariate statistical analysis to represent the operation of the process based on a set of collected on-line process data comprising a measure of the operation of the process when the process is on-line within a second data space having fewer dimensions than the first data space, performing a univariate analysis to represent the operation of the process as a multivariate projection of the on-l

Abstract: A method and system of monitoring multivariate process data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes defining each process variable as a process variable vector comprising a set of observation components, where the set of observation components comprises time dependent process data corresponding to the observations of the process variable, calculation, a multivariable transformation as a function of a plurality of process variable vector transformation each corresponding to one of the process variables, where each process variable vector transformation is a function of a univariate variable unifying the process variables, and representing the operation of the process based on the multivariable transformation, where the representation of the operation of the process designates a multivariate projection of the process data by the univariate variable for each of the process variables.

Abstract: Methods and systems to detect abnormal operations in a process of a process plant include collecting on-line process data. The collected on-line process data is generated from a plurality of dependent and independent process variables of the process, such as a coker heater. A plurality of multivariate statistical models of the operation of the process are generated using corresponding sets of the process data. Each model is a measure of the operation of the process when the process is on-line at different times, and at least one model is a measure of the operation of the process when the process is on-line and operating normally. The models are executed to generate outputs corresponding to loading value metrics of a corresponding dependent process variable, and the loading value metrics are utilized to detect abnormal operations of the process.

Abstract: A method and system for monitoring a process in a process plant includes collecting data from a process control system within the process plant, where the data is representative of a normal operation of the process when the process is on-line and operating normally, performing a multivariate statistical analysis to represent the normal operation of the process based on a set of collected on-line process data comprising a measure of the normal operation of the process when the process is on-line and operating normally, and representing a real-time on-line operation of the process using monitored on-line process data comprising a measure of a real-time operation of the process when the process is on-line as an input to the representation of the normal operation of the process.

Abstract: A system and method of monitoring and diagnosing on-line multivariate process variable data in a process plant, where the multivariate process data comprises a plurality of process variables each having a plurality of observations, includes collecting on-line process data from a process control system within the process plant when the process is on-line, where the collected on-line process data comprises a plurality of observations of a plurality of process variables, performing a multivariate statistical analysis to represent the operation of the process based on a set of collected on-line process data comprising a measure of the operation of the process when the process is on-line, where the representation of the operation of the process is adapted to be executed to generate a result, storing the representation of the operation of the process and the set of collected on-line process data, and generating an output based on a parameter of the representation of the operation of the process, where the parameter

Abstract: Microwave energy may be used to dielectrically heat a medium, which can remediate the medium. An apparatus or a system employing this concept is well-suited for various environmental applications, such as in-situ remediation of soil, sludge or spills. The system comprises a microwave energy source having a preselected microwave frequency for emitting microwave energy. The system also comprises a wave-guide section having a cross-section dimensioned in accordance with the wavelength of the microwave frequency for transmitting microwave energy. A broadband mode converter may be disposed in alignment with the wave-guide section. An applicator element is disposed in alignment with the broadband more converter for applying microwave energy directly to the medium without confining the medium, thereby removing contaminants from the medium.

Abstract: Apparatus for automatic tuning of microwave energy in a de-emulsifier system usng a wave guide applicator with impedance matching element wherein microwave energy incident on and reflected from the applicator element is continually monitored to derive an indication of voltage standing wave ratio for input to a computer that controls a servo control motor to position a phase shifter thereby to maintain an optimum voltage standing wave ratio and, therefore, maximum efficiency of emulsion irradiation.

Abstract: Apparatus for de-emulsification of liquids using microwave energy as radiated into an applicator section of characteristic frequency dimensions consisting of a wave guide section that has a taper applicator element of low dielectric constant material separating the wave guide section into a radiation input void end and a larger volume liquid-filled output end; whereby emulsion under pressure is input to the wave guide section output end adjacent the applicator element to undergo radiation and convection heating and subsequent separation into constituent components.