Patent application number | Description | Published |
20080279155 | Adaptive Scheduling in a Wireless Network - A method of adaptively scheduling communications in a wireless mesh network including a plurality of network nodes includes generating a network routing scheme based on a topology of the wireless mesh network, generating a communication schedule for the wireless mesh network, and automatically updating the communication schedule in response to detecting a change in a transmission requirement of at least one of the plurality of network nodes. The act of generating a communication schedule includes defining a communication timeslot of a predefined duration and defining a plurality of superframes as repeating cycles of a certain number of consecutively scheduled communication timeslots. | 11-13-2008 |
20080279204 | Increasing Reliability and Reducing Latency in a Wireless Network - A mesh communication network for use in, for example, process control plants includes a plurality of network devices transmitting and receiving data according to a network schedule defined as a set of concurrent overlapping superframes, and along a set of graphs defining communication paths between pairs of network devices. A network manager residing in or outside the communication network develops a routing scheme for the network by analyzing the topology of the network and defining a set of graphs for use in routing or transmitting data between various nodes of the network, each graph including one or more communication paths between pairs of network devices. Concurrently or consequently, the network manager defines the network schedule in view of at least transmission requirements, power availability, and signal quality at each network device. If desired, the network manager may begin to define the network schedule upon completing the definition of the graphs of the communication network, so that the network manager may define the network schedule in view both the defined graphs and the transmission, power, etc. parameters associated with each network device. | 11-13-2008 |
20080312757 | ENHANCED TOOL FOR MANAGING A PROCESS CONTROL NETWORK - A process control configuration and management system provides a plurality of function blocks representing a plurality of devices in relation to a spatial layout of a facility in which the process control system is implemented. The configuration and management system also provides process control information and process simulation information related to each of the plurality of devices in relation to the spatial layout of the facility. The configuration and management system may be implemented on a handheld device and it may include a geographic positioning system providing geographic positioning data related to the handheld device and various devices in relation to the spatial layout of the facility. | 12-18-2008 |
20090010205 | Priority-Based Scheduling and Routing in a Wireless Network - A method of routing data in a mesh communication network including a plurality of network devices and operating in a process control environment, including assigning one of a plurality of priority levels associated with the communication network to a data packet, sending the data packet from a source network device included in the plurality of network devices to a destination network device included in the plurality of network devices, and routing the data packet to a destination network device via at least one intermediate network device included in the plurality of network devices. The act of routing includes comparing, at each intermediate network device, the priority level of the data packet to a priority mask of the intermediate network device, and modifying at least one of scheduling or routing of the data packet if the priority level of the data packet is not associated with the priority mask of the intermediate network device. | 01-08-2009 |
20090046675 | Scheduling Communication Frames in a Wireless Network - A method of scheduling communications in a multi-node wireless mesh network which has a first network device and a second network device includes defining a communication timeslot of a predetermined duration, defining a first superframe having a repeating superframe cycle including a first number of the communication timeslots, defining a second superframe having a repeating superframe cycle including a second number of the communication timeslots, aligning the first superframe with the second superframe, so that one of the timeslots of the first superframe begins simultaneously with one of the timeslots of the second superframe, and associating the first and the second superframes with a network schedule, so that the first network device and the second network device transmit data according to the network schedule. | 02-19-2009 |
20090046732 | Routing Packets on a Network Using Directed Graphs - A method of routing a data packet between a first node and a second node on a communication network includes defining a first graph through the first node and the second node and zero or more intermediate nodes, associating several nodes which belong to the communication network with the first graph, associating a first unique graph identifier with the first graph and providing at least partial definitions of the first graph and the first unique identifier to at least some of the nodes associated with the first graph. The method then sends data packet with the graph identifier from the first node, and directs the data packet to the second node via the zero or more intermediate nodes using the graph identifier. This method may include forwarding the packet to a neighbor node of an intermediate node if the intermediate node and the neighbor node are nodes associated with the first graph and if the intermediate node and the neighbor node are connected by at least one direct communication connection. | 02-19-2009 |
20090062932 | Process Model Identification in a Process Control System - Disclosed is a method of controlling and managing a process control system having a plurality of control loops. The method includes implementing a plurality of control routines to control operation of the plurality of control loops, respectively. The plurality of control routines may include at least one non-adaptive control routine. Operating condition data is then collected in connection with the operation of each control loop of the plurality of control loops, and a respective process model is identified for each control loop of the plurality of control loops from the respective operating condition data collected for each control loop of the plurality of control loops. In some embodiments, the identification of the respective process models may be automatic as a result of a detected process change or be on-demand as a result of an injected parameter change. | 03-05-2009 |
20090299495 | Non-Periodic Control Communications in Wireless and Other Process Control Systems - Disclosed is a controller having a processor and a control module adapted for periodic execution by the processor and configured to be responsive to a process variable to generate a control signal for a process. An iteration of the periodic execution of the control module involves implementation of a routine configured to generate a representation of a process response to the control signal. The routine is further configured to maintain the representation over multiple iterations of the periodic execution of the control module and until an update of the process variable is available. In some cases, the update of the process variable is made available via wireless transmission of the process signal. In those and other cases, the controller may be included within a process control system having a field device to transmit the process signal indicative of the process variable non-periodically based on whether the process variable has changed by more than a predetermined threshold. In some embodiments, the field device also transmits the process signal if a refresh time has been exceeded since a last transmission. | 12-03-2009 |
20100222899 | PROCESS PLANT MONITORING BASED ON MULTIVARIATE STATISTICAL ANALYSIS AND ON-LINE PROCESS SIMULATION - Disclosed are systems and methods for on-line monitoring of operation of a process in connection with process measurements indicative of the operation of the process. In some cases, the operation of the process is simulated to generate model data indicative of a simulated representation of the operation of the process and based on the process measurements. A multivariate statistical analysis of the operation of the process is implemented based on the model data and the process measurements. The output data from the multivariate statistical analysis may then be evaluated during the operation of the process to enable the on-line monitoring of the process involving, for instance, fault detection via classification analysis of the output data. | 09-02-2010 |
20110009985 | CUSTOM FUNCTION BLOCKS FOR USE WITH PROCESS CONTROL SYSTEMS - A system and method for creating and incorporating a function block within a process control system enables a user of the process control system to generate a function block by combining a plurality of files selected from a group of files provided by the manufacturer of the process control system to form a source code file associated with the function block. The user can modify the function block source code file to include a procedure, routine or algorithm that is not provided by the manufacturer and can send the modified source code file to the manufacturer for validation. If the function block source code file is validated, a security measure such as a digital signature is provided to the user that enables the user to incorporate the function block within the process control system. The function blocks can be used to incorporate anew function into a process control application or to operatively integrate a data source external to a process control application with the process control application via data mapping functions performed by the function blocks. | 01-13-2011 |
20110022187 | PROCESS CONTROL SYSTEM WITH INTEGRATED EXTERNAL DATA SOURCES - Methods and systems for integrating external and/or enterprise data into a process control system are disclosed. A user interface may be provided to enable browsing and selection of a data item from an external and/or enterprise data source. The selected data item may be associated with a process control entity. At run time, independent of a configuration of the process control entity, an external data integration server or instance of an external data integration service at a process control computing device may periodically communicate with the data source to obtain an updated current value and updated current status for the selected data item for use by the process control entity. The external data integration server and/or external data integration service may consolidate access of external/enterprise data across process control entities, optimize communications with various data sources, and maintain a status of communication with each various data source. | 01-27-2011 |
20110040390 | System Configuration Using Templates - A method in a computer system for developing a process control strategy includes providing a module template having a first plurality of components and being associated with a control operation, receiving a selection of one or more of the first plurality of components of the module template, generating an instance of a module based on the module template, including instantiating only the selected one or more of the first plurality of components, and associating the generated instance of the module with the process control strategy. | 02-17-2011 |
20110288660 | ON-LINE ALIGNMENT OF A PROCESS ANALYTICAL MODEL WITH ACTUAL PROCESS OPERATION - A batch modeling and analysis system uses a simple and computationally inexpensive technique to align data collected from an on-going, currently running or on-line batch process with a batch model formed for the batch process so as to enable the reliable determination of the current operational state of the on-line batch process with respect to the batch model. This data alignment technique enables further statistical processing techniques, such as projection to latent sources (PLS) and principle component analysis (PCA) techniques, to be applied to the on-line batch data to perform analyses on the quality of the currently running batch. These analyses, in turn, provide useful information to a user, such as a batch operator, that enables the user to determine the quality of the batch at the present time, based on the batch model, and the likelihood that the desired batch output quality metrics will be reached at the end of the batch run. | 11-24-2011 |
20110288786 | Method and System for Multi-Zone Modeling to Determine Material Properties in Storage Tanks - In a batch process control system employing storage tanks without mixers, properties of the storage tank pump out feedstock may be modeled to more accurately control the quality of a process. This model may not require the measurement of input or pump out flow or assume perfect blending. Rather, the developed model may assume that feedstock input into a storage tank may remain layered with some mixing due to continuous convection, turbulence during loading, or other factors. The model may include a projection of the properties describing a storage tank layer of input material into the model. For each new load of storage tank input feedstock, model zones may be shifted and the zone from which the feedstock is drawn may be updated with the properties from the new load. | 11-24-2011 |
20110288837 | Multi-Stage Process Modeling Method - A process is modeled by resolving the process into a plurality of process stages, including at least a first process stage and a second process stage, and developing a plurality of models, each model corresponding to a respective one of the plurality of process stages, wherein the model corresponding to each process stage is developed using data from one or more runs of that process stage and output quality data relating to the one or more runs of that process stage and wherein the model corresponding to each process stage is adapted to produce an output quality prediction associated with that process stage, and wherein the output quality prediction produced by the model of a first one of the process stages is used to develop the model of a second one of the process stages. | 11-24-2011 |
20120083917 | PREDICTED FAULT ANALYSIS - Example methods, apparatuses and systems to correlate candidate factors to a predicted fault in a process control system are disclosed. Techniques may include obtaining a value associated with a particular factor corresponding to a process, and predicting a fault based on the value. A set of candidate factors corresponding to the predicted fault may be determined, and a correlation between the predicted fault and at least one factor from the set may be displayed. Different sections of the display may respectively correspond to the predicted fault and to the at least one factor, and the correlation may be indicated by time aligning the different sections. Modifications to one displayed section may result in automatic modification of other sections to maintain the correlation. A user may select one or more candidate factors to be displayed, and may indicate a particular point of a particular section to obtain additional details. | 04-05-2012 |
20130046396 | Self-Diagnostic Process Control Loop For A Process Plant - A method of diagnosing an adaptive process control loop includes measuring process control loop signal data, generating a plurality of process control loop parameters from the process loop signal data and evaluating a condition of the adaptive process control loop from one or more of the plurality of process control loop parameters. The process control loop data is generated as a result of a normal operation of one or more process control devices within the adaptive process control loop when the adaptive process control loop is connected on-line within a process control environment. A self-diagnostic process control loop includes a diagnostic tool adapted to receive a diagnostic index pertaining to a process control loop parameter for a plurality of components of the process control loop and for the complete process control loop. Each diagnostic index is generated from signal data by a corresponding index computation tool. The diagnostic tool is further adapted to evaluate a condition of the process control loop from one or more of the diagnostic indices. | 02-21-2013 |
20130069792 | INFERENTIAL PROCESS MODELING, QUALITY PREDICTION AND FAULT DETECTION USING MULTI-STAGE DATA SEGREGATION - A process modeling technique uses a single statistical model developed from historical data for a typical process and uses this model to perform quality prediction or fault detection for various different process states of a process. The modeling technique determines means (and possibly standard deviations) of process parameters for each of a set of product grades, throughputs, etc., compares on-line process parameter measurements to these means and uses these comparisons in a single process model to perform quality prediction or fault detection across the various states of the process. In this manner, a single process model can be used to perform quality prediction or fault detection while the process is operating in any of the defined process stages or states. | 03-21-2013 |
20130079901 | METHOD AND APPARATUS FOR ELIMINATING ALIASING - In order to reduce or eliminate aliasing in a process control network, filtering of a measurement signal may be set based on the module execution rate in a process control system. A Nyquist frequency for the module may be determined based on the module execution rate where the Nyquist frequency may be twice the execution rate. Filtering after an analog to digital convertor may be set based on the module execution rate. In the analog to digital convertor, digital filtering after the converter may be set based on the module execution rate and the frequency content of the analog signal may be attenuated by a filter at and above the Nyquist frequency for the module execution rate. | 03-28-2013 |
20130184837 | COMPENSATING FOR SETPOINT CHANGES IN A NON-PERIODICALLY UPDATED CONTROLLER - A technique for controlling a process using non-periodically received process variable measurements enables more robust controller responses to setpoint changes. The control technique implements iterations of a control routine to generate a control signal using a reset or rate contribution component that produces an expected process response to the control signal. When a new measurement of the process variable is unavailable to the controller, the reset or rate contribution component that was generated in response to the receipt of the previous process variable is maintained when generating the control signal. However, the reset contribution component is iteratively recalculated during each controller execution cycle so that the output of the reset contribution component incorporates expected process changes that occur as a result of a setpoint change. | 07-18-2013 |
20140249653 | USE OF PREDICTORS IN PROCESS CONTROL SYSTEMS WITH WIRELESS OR INTERMITTENT PROCESS MEASUREMENTS - A control technique that enables the use of slow or intermittently received process variable values in a predictor based control scheme without the need to change the control algorithm includes a controller, such as a PID controller, and a predictor, such as a model based predictor, coupled to receive intermittent feedback in the form of, for example, process variable measurement signals from a process. The predictor, which may be an observer like a Kalman filter, or which may be a Smith predictor, is configured to produce an estimate of the process variable value from the intermittent or slow process feedback signals while providing a new process variable estimate to the controller during each of the controller execution cycles to enable the controller to produce a control signal used to control the process. | 09-04-2014 |
20140249654 | KALMAN FILTERS IN PROCESS CONTROL SYSTEMS - A control technique that enables the use of received process variable values in a Kalman filter based control scheme without the need to change the control algorithm includes a controller, such as a PID controller, and a Kalman filter, coupled to receive feedback in the form of, for example, process variable measurement signals from a process. The Kalman filter is configured to produce an estimate of the process variable value from slow or intermittent process feedback signals while providing a new process variable estimate to the controller during each of the controller execution cycles to enable the controller to produce a control signal used to control the process. The Kalman filter is also configured to compensate the process variable estimate for process noise with non-zero mean value that may be present in the process. The Kalman filter may apply this compensation to both continuously and intermittently received process variable values. | 09-04-2014 |
20140277604 | DISTRIBUTED BIG DATA IN A PROCESS CONTROL SYSTEM - A distributed big data device in a process plant includes an embedded big data appliance configured to locally stream and store, as big data, data that is generated, received, or observed by the device, and to perform one or more learning analyses on at least a portion of the stored data. The embedded big data appliance generates or creates learned knowledge based on a result of the learning analysis, which the device may use to modify its operation to control a process in real-time in the process plant, and/or which the device may transmit to other devices in the process plant. The distributed big data device may be a field device, a controller, an input/output device, or other process plant device, and may utilize learned knowledge created by other devices when performing its learning analysis. | 09-18-2014 |
20140280678 | COLLECTING AND DELIVERING DATA TO A BIG DATA MACHINE IN A PROCESS CONTROL SYSTEM - A device supporting big data in a process plant includes an interface to a communications network, a cache configured to store data observed by the device, and a multi-processing element processor to cause the data to be cached and transmitted (e.g., streamed) for historization at a unitary, logical centralized data storage area. The data storage area stores multiple types of process control or plant data using a common format. The device time-stamps the cached data, and, in some cases, all data that is generated or created by or received at the device may be cached and/or streamed. The device may be a field device, a controller, an input/output device, a network management device, a user interface device, or a historian device, and the device may be a node of a network supporting big data in the process plant. Multiple devices in the network may support layered or leveled caching of data. | 09-18-2014 |
20140282227 | DATA MODELING STUDIO - A data modeling studio provides a structured environment for graphically creating and executing models which may be configured for diagnosis, prognosis, analysis, identifying relationships, etc., within a process plant. The data modeling studio includes a configuration engine for generating user interface elements to facilitate graphical construction of a model and a runtime engine for executing data models in, for example, an offline or an on-line environment. The configuration engine includes an interface routine that generates user interface elements, a plurality of templates stored in memory that serve as the building blocks of the model and a model compiler that converts the graphical model into a data format executable by the run-time engine. The run time engine executes the model to produce the desired output and may include a retrieval routine for retrieving data corresponding to the templates from memory and a modeling routine for executing the executable model. | 09-18-2014 |