Computational Systems, Inc.

Csi Technology, Inc.

Christopher G Hilemon

Anthony John Hayzen

Trevor Duncan Schleiss

Manikandan Janardhanan

William L Sells

John W Willis

Stewart V Bowers, Iii

Thomas E Nelson

Todd W Reeves

David L Bass

Viva C Williams

Kenneth Ralph Piety

Robert Darrell Skeirik

Richard W Piety

Michael D Rich

Deane M Horn

Michael D Medley

Kai T Bouse

Mark Slemp

Miodrag Glumac

Keith Walton

A vibration data collection device monitors vibration of a machine, generates original machine vibration waveform data based on the monitored vibration, and removes portions of the original machine vibration waveform data that do not indicate an occurrence of a vibration event related to a potential fault in the machine. The vibration data collection device then stores thinned waveform data that includes blocks of the original machine vibration waveform data and excludes the portions that have been removed. A data analysis computer generates a thinned waveform plot based on the thinned waveform data. In some embodiments, the thinned waveform plot includes the blocks of original machine vibration waveform data separated in time by gaps representing the portions that have been removed. In some embodiments, the thinned waveform plot that includes the blocks of the original machine vibration waveform data and representative blocks of data that each represent the portions of the original machine vibration waveform data that have been removed. A display device displays the thinned waveform plot for viewing by an analyst.

Graphical display of discontinuous waveform data

Spectral machine condition energy peaks are graphically represented in a spectral plot using color coding, different line types, and/or filtering. This allows visual differentiation of spectral peaks associated with various fault frequency families from one another, whereby a machine condition analyst using computer-based analysis software can easily see each family of spectral peaks individually, without all the other spectral peaks, or in combinations of families that are relevant to a machine fault under investigation. In addition to current spectral data, the analyst can also view a historical trend of related scalar parameters plotted in conjunction with current spectral data, wherein the spectral data plot is synchronized with a time-based cursor on the trend plot.

Graphical differentiation of spectral frequency families

A computerized apparatus for presenting vibration data that is read under different conditions as a single trend line on a chart. A sensor measures vibration and produces vibration data. A memory stores the vibration data, an indicator of the condition under which the vibration data was produced, and a type associated with the vibration data. A processor reads the vibration data, the condition, and the type from the memory, and selectively plots the vibration data on the trend line when the type of the vibration data matches a given value, even though the condition might be different from data point to data point on the trend line. The processor selectively creates a flag indicating a condition change, and an interface presents a plot of the trend line, and the flag when a condition change occurs between data points.

Trend plot with multiple acquisitions

While monitoring the condition of a machine, vibration data is often collected for analysis by an experienced analyst. Systems and methods for analyzing vibration spectra associated with machine condition monitoring are disclosed herein. A system may be configured to collect vibration data from one or more vibration sensors, generate a vibration spectrum of the vibration data, and generate a spectral plot of the vibration spectrum. The system may receive a selection of a region of the spectral plot and generate a modifiable window of the vibration spectrum that is embedded within the spectral plot. The system may display a set of graphing tools along with the modifiable window that enable a user to make modifications to the window. The system may detect the modifications and update the modifiable window accordingly.

Vibration spectra window enhancement

A process for thinning scalar machine vibration data can reduce the amount of data storage required to store the data by several orders of magnitude, without losing any important machine diagnostic vibration information. The process assumes that because each scalar vibration measurement value has its own range of values, there is a unique delta change in value that does not significantly impact machine diagnostic information provided by the data. Some embodiments provide a method to automatically evaluate the delta change in value. The process can be used to thin data that have already been stored in a database, and also to thin the data in real-time during data collection. Data storage structures for storing the thinned scalar values and processes for displaying a trend plot to indicate where the scalar data have been thinned are also described.

Thinning of scalar vibration data

An apparatus continually monitors predictive maintenance information and analyzes incoming measurements resulting in recommendations for improving setup information, such as machine information and measurement configurations. Smart sensors generate sensor signals corresponding to the parameters of a machine and a transducer converts the sensor signals into digital sensor data, which is stored into memory. An analyzer determines current operating characteristics of each machine and runs an improvement cycle in which it calculates new setup information. For example, the analyzer may calculate a new alert limit, which is a new measurement configuration that may be saved in the database as a new stored measurement configuration replacing an old measurement configuration. The analyzer may also calculate new machine information. For example, the analyzer may identify features in a frequency spectrum that are characteristic of a particular geartrain that is different from the geartrain identity provided in the predictive maintenance database. The analyzer may automatically change the identity of the geartrain in the predictive maintenance database, or it may suggest the change to the operator. The analyzer also runs an analysis cycle during which current operating conditions of each machine are determined and signals are issued based on the current operating conditions.

Method and apparatus for machine monitoring with continuous improvement of a predictive maintenance database

A method of messaging control is implemented in a plant wide monitoring apparatus. A computer based framework infrastructure communicates with monitoring applications throughout the plant that are implemented on computers, monitors and computer-based applications. Sensors are placed on machinery and monitors receive sensor signals and generate event signals in response to defined physical occurrences, such as when vibration in a machine is exceeding a defined limit or a sensor is failing. A messaging application in the framework infrastructure generates messages corresponding to the event signals. The messages are transmitted to users based on send rules and suppression rules, which are user configurable. The send rules identify messages to be sent or not sent to a particular user based on characteristics of event signals. The suppression rules prevent the transmission of a message based on both the content of a particular event signal plus an external factor, such as a prior event signal. Suppression rules may suppress messages based on a repetitive characteristic in a series of event signals occurring within a specified time interval.

Controlling asset messages

An application software platform is provided for use in a process plant or other environment to enable various different applications to run, to obtain access to, and to use data from various different assets in the plant or other asset environment in a consistent and easily understood manner. The software platform includes a class-based object structure or model that is set up and used to organize and to efficiently provide access to data about, generated by, or obtained from the assets in the plant. This class-based object structure may be used to provide efficient and organized communications between the various monitoring or other applications and the plant assets or sources of data. The class-based object structure is extensible and includes or defines various hierarchies of class objects that, in turn, define various levels of the assets or other physical or logic entities being monitored (i.e., from which or about which data is being obtained), as well as properties and behaviors of the assets or physical or logical entities being monitored.

Extensible asset classes in a monitoring system having a common platform

An extensible computing system integrates asset health data and user control of devices made by different manufacturers, using a common computer platform application structure and a common platform services structure. A services bus communicates device signals in a standardized format from the common platform services structure to a proprietary extension services structure, which converts the device communication signals from the standardized format to a proprietary communication format. A data highway bus communicates asset health and reliability data in a standardized data format from the proprietary extension services structure to the common extension services structure. The proprietary services structure converts asset health data from a proprietary data format as received from the proprietary device into the standardized data format. An input communicates data in the proprietary data format from the proprietary device to the computer, and an output sends communication signals in the proprietary communication format to the proprietary device.

Method for communicating between asset health monitoring devices

A span of responsibility access control system for use in plant process management and similar applications. The system leverages span-of-responsibility enabled user accounts and corresponding resource properties to assign, verify, and control access to assets and other resources in the plant process management system on a per user basis. Aspects of the system include configuration of properties for each monitored or controlled asset and association of a span of responsibility based on asset properties, such as asset type and location, with a user account. An access control module compares asset properties to the span of responsibility associated with the user account to determine whether the user is entitled to access any given asset, independent of determining permissions to act on such asset.

Span of responsibility access control system

A machine monitoring system uses generically defined collection definitions, acquisition definitions, and measurement definitions to define machine data to be collected by machine monitoring devices and other data sources in a unified and device/source independent manner. Configuration software of the machine monitoring system defines data to be collected for a particular machine in such a manner that multiple different types of monitoring devices or data sources can each interpret the data definitions and provide the same type of data back to the software system. Thus, the data to be collected is defined once by the configuration software, and the data definition is interpreted internally by each monitoring device or data source. This greatly simplifies the monitoring system and provides the advantage that new monitoring devices can be added to the system to collect data without impacting the software configuration of the data required.

Defining acquisition and measurement definitions in a machine monitoring system

A system collects and manages sets of asset data that are indicative of operational performance of physical assets disposed at multiple physical locations in a plant. The system includes a database that associates each set of asset data to (1) a location at which the data was collected, (2) the asset for which the data was collected, and (3) the monitoring device that was used to collect the data. In this way, each location has its own history of all asset data ever collected on all assets disposed at that location, and its own history of all monitoring devices used to collect data at that location. Also, each asset has its own history of all asset data collected on that asset at all locations at which it was disposed and for all monitoring devices. This sort of asset data is referred to herein as multi-referenced data.

Apparatus and method for maintaining multi-referenced stored data

A machine monitor includes sensors producing a series of scalar values corresponding to sensed physical parameters. An analyzer produces a first database based on the scalar values and determines a median value of the scalar values for each sensor. It also sets a spike level that is offset from the median value by a predetermined multiple of the median value. A spike filter in the analyzer compares the scalar values to the spike level, and identifies a particular scalar value as a potential spike when the particular scalar value differs from the median value by an amount that is equal to or greater than the spike level. A potential spike is determined to be an actual spike if the first and second side values are within a predetermined range of the median value. A second database is produced with the actual spikes eliminated. Using the second database, corrected faults are identified by finding a data point that exceeds a danger level with a preceding data point exceeding a warning level and two trailing data points being less than an advise level.

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Knoxville, TN, United States of America

Christopher G Hilemon