Csi Technology, Inc.

Fisher-rosemount Systems, Inc

Todd W Reeves

Evren Eryurek

Kai T Bouse

Kenneth Ralph Piety

Scott Nels Hokeness

Christopher G Hilemon

Raymond Earl Garvey, Iii

Stuart A Harris

Michael D Rich

Robert Burke Havekost

Stewart V Bowers, Iii

Cindy Alsup Scott

Richard W Piety

Jason Edwards

Jim Robinson

Keith Walton

Miodrag Glumac

A process control system uses an asset optimization reporter to collect status information of dissimilar types pertaining to the assets of a process plant from various data sources of the plant including, for example, data tools, data collectors, and data generators. This status information is used to generate reports that may be displayed to various users, including maintenance persons, process control persons and business persons. The status information may be used as the basis for further types of status information and/or be categorized in based on an assessment of relative consequence, where each category has a spectrum of status quality values between a good status quality and a relatively worse status quality. The reports are generally displayed via a user interface routine that enables users to view the status information as a graphical representation having a leg of a normalized spectrum of values for each category arranged in order of the relative consequence, the relative status quality value being identified at a point on the respective leg.

Asset optimization reporting in a process plant

A machine condition monitor resides in close proximity to a machine train, such as an AC inductive electric motor coupled to a driven unit such as a centrifugal pump or fan. A plurality of sensing devices are connected to the machine and the machine condition monitor. Machine state and condition parameters sensed by these devices are utilized by the machine condition monitor to derive machine condition values for each component and for the machine train as a whole. These derived condition values are transmitted via an industrial communications network to a control center where they can be trended and monitored. With no particular knowledge of machine analysis techniques or severity of specific machine faults, and no special training, Operators and Production Planners can use the condition values to plan production schedules, adjust process parameters, and request appropriate maintenance action.

Machine condition indication system

A process control system uses an asset optimization reporter to collect status information pertaining to the assets of a process plant from various data sources of the plant including, for example, data tools, data collectors, and data generators. This status information is used to generate reports that may be displayed to various users, including maintenance persons, process control persons and business persons. The status information may be used as the basis for further types of status information and/or be categorized in ways that are useful to the user. The reports are generally displayed via a user interface routine that enables users to view the status information and manipulate the display of the report to correspond to the user's preferences, as contained in a user profile. The user interface routine further enables the user to view reports of various types of status information for various devices, loops, units, areas, etc., including status information for the process plant, and manipulate how the status information is displayed, such as with textual, numerical or graphical depictions or any combination thereof.

Sensors detect machine parameters such as vibration, turning speed, and temperature, and a local processor performs logic operations based on the parameters and inference rules to produce fault information that is reported to a system processor, which selectively uses the fault information to control the plant machines. The inference rules include rules for determining faults as to balance, alignment, bearing condition, electrical condition, and cavitation. The inference rules are contained in rules code that is separate from the analysis code that performs the logical operations. Thus, the inference rules may be easily changed without changing other code, such as the analysis code.

Machine fault information detection and reporting

A method and system for integrating alarms is provided. An external alarm is received at a process control system and includes an external tag. An internal alarm that is associated with the external alarm is determined based on a map. An internal tag associated with the external tag is also determined based on the map. The process control system generates the internal alarm which includes the internal tag and is based on the external alarm. A method and system for generating alarm and tag relations is also provided. At least one external tag associated with an external system is selected. At least one internal tag associated with a process control system related to the external tags is determined. At least one entry in a map is generated to indicate a relation between at least one of the external tags and at least one of the internal tags. At least one external alarm associated with the external system is selected and at least one internal alarm related to the external alarms is determined. At least one entry is generated in the map to indicate a relation between at least one of the external alarms and at least one of the internal alarms.

Method and system for integrated alarms in a process control system

Information related to an operational condition of a machine in a process plant is generated, where the generated information is in a first data format. The information may be generated based on data in a second format. The second format may, for example, correspond to a format used by a certain type or types of process entities, whereas the first format may, for example, correspond to a format used to process operational condition information of other types of process entities in the process plant. Providing operational condition data for various types of process entities in a common format may, for example, assist an operator in ascertaining the relative importance of the operational condition for various types of entities.

Generation of data indicative of machine operational condition

A rotating equipment monitoring device includes a set of sensors, such as temperature, speed, pressure, and vibration sensors, locally connected to a diagnostic unit having a plant communication interface and a processor that implements one or more diagnostic routines. The diagnostic unit collects data from the sensors and performs diagnostics thereon to detect actual or potential problems with the rotating equipment on a continuous or semi-continuous basis. Using the communication interface, the diagnostic unit automatically sends signals indicating detected conditions of the rotating equipment to a maintenance system or a control system via standard or common communication network, such as a HART or Fieldbus network. The diagnostic unit may also be intermittently coupled to an off-line computer, such a one associated with a service provider, who may verify or further define the diagnostics provided by the diagnostic unit.

On-line rotating equipment monitoring device

A hand-held apparatus gathers and analyzes test data associated with rotating electric machines, where the test data is indicative of one or more operational characteristics of the mechanical equipment. The apparatus, which is operable to be carried by an operator from one machine to another along a test route, includes a sensor input port for receiving a sensor signal from a sensor, where the sensor signal is indicative of one or more operational characteristics of the rotating electric machines. The apparatus also includes a signal conditioning circuit for receiving the sensor signal, and for conditioning the sensor signal to produce a conditioned signal which is appropriate in format to be digitally processed. A processor, which is coupled to the signal conditioner, receives and processes the conditioned signal according to processing instructions and processing parameters to produce a test spectrum. The processing parameters determine one or more characteristics of the test spectrum. A memory device, which is coupled to the processor, stores a plurality of executable test expert modules, each containing the processing instructions for processing the conditioned signal in a particular way to determine one or more of the operational characteristics of the rotating electric machines. An operator input device is coupled to the processor for receiving input from the operator to select one of the test expert modules to be executed to process the conditioned signal according to the processing instructions contained in the selected module. The apparatus further includes a display device for displaying the test spectrum to the operator. The test expert modules contain processing instructions for determining whether the processing parameters have been set according to a predetermined configuration for a particular test point on the test route, and for processing the conditioned signal in a way dependent upon whether or not the processing parameters have been set according to such a predetermined configuration.

Expert analysis modules for machine testing

The invention provides a computerized method and apparatus which enables a user, even one who has little or no predictive maintenance skills, to establish a predictive maintenance database that defines information needed to monitor equipment in accordance with a predictive maintenance plan. The type of equipment components to be monitored and associated physical characteristics of the components are input to a computer as an equipment configuration, which may include one or more interconnected components. The computer includes a knowledge base that defines relationships between monitoring practices, component types, and physical characteristic information for component types. A predictive maintenance database is constructed for the components using the inference engine operating on the knowledge base, the selected component type, and the selected physical characteristic information. Multiple measurement technologies may be specified for each component. Preferably, for each measurement technology specified, the predictive maintenance database includes measurement points, an analysis parameter set, and an alarm limit set. Equipment configurations may be defined by the user, or they may be stored in a configuration/component warehouse with little or no configuration definition required of the user.

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Knoxville, TN, United States of America

Todd W Reeves