Abstract:
A method and system ( 20 ) is provided for condition based monitoring reliability maintenance capabilities for an asset ( 70 ), such as one or more machines, by establishing a network including of a sensor ( 60 ) or a plurality of sensors installed, temporarily or in generally fixed locations, on asset ( 70 ), wherein sensor ( 60 ) provides time sequenced operational information in the form of data based on vibrations, temperature, electrical signals, or other operating conditions. Sensors ( 60 ) are connected to a local controller ( 40 ) which transmits the data via a local or wide area network ( 45 ), either through wired or wireless communication paths, in data packets, each containing divided portions of the operational information. The data packets are mapped and stored into multiple, dedicated databases for ease of retrieving and analyzing the data. Preferably, a cloud-based storage arrangement ( 120 ) is employed to storing the mapped data.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims the benefit of U.S. Provisional Patent Application Ser. No. 61/533,188 filed on 10 Sep. 2011, entitled “Method and Apparatus For Monitoring and Reporting Equipment Operating Conditions and Diagnostic Information,” which is incorporated herein by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    The present invention pertains to the field of predictive and reliability centered system maintenance and, more specifically, to a method and apparatus for monitoring and reporting equipment operating conditions and diagnostic information. More particularly, the present invention relates to a condition based monitoring network and method which employs local and wide area networks to provide operating condition data to local and remote users with the necessary software to read and analyze data, as well as providing a user interface. 
         [0003]    Operators of machinery must balance the often competing concerns of maximizing operational time and minimizing maintenance costs. On high-value equipment, operators typically invest in real-time monitoring systems, while the remaining “balance of plant” equipment is subject to periodic manual inspection, often using portable equipment. Manual inspection is typically conducted according to some sort of predefined time schedule, or when a significant problem has been identified. 
         [0004]    Manual inspection incurs four significant problems. First, manual inspection generally involves risks associated with the environment and operating conditions of the equipment. Second, manual inspection can involve a significant waste of resources in connection with personnel travelling between various pieces of equipment in various locations, as well as time spent collecting and analyzing data. Third, manual inspection is generally not executed by personnel who are experts in the various fields of concern, e.g., vibration, thermodynamics, and other operating conditions. Finally, data collected is inconsistent due to variances related to the method of inspection, e.g., sensor placement and inspections being performed at irregular intervals. 
         [0005]    Beyond the concerns associated with conducting manual inspections, it turns out that manual inspections are generally not extremely effective at addressing maintenance concerns typical to balance of plant equipment. Often, serious maintenance issues and catastrophic failures of balance of plant equipment are associated with human error during routine maintenance, e.g., insufficient lubrication, improperly installed parts, etc. These issues manifest in a time period that is frequently too short to be addressed by periodic manual inspections. However, real-time monitoring is not a viable solution for the balance of plant equipment due to costs, location and other concerns. To this end, there is a gap in the ability to effectively monitor and evaluate the condition of operating equipment. 
         [0006]    As can be seen from the above discussion, there is considered to be a need in the art for a cost elective, condition based monitoring solution that will provide an operator with the ability to address these issues. 
       SUMMARY OF THE INVENTION 
       [0007]    The present invention is directed to a particular approach to conducting predictive and reliability centered maintenance. The present invention provides to system to monitor the operating condition of “balance of plant” equipment via sensors that are strategically installed, either permanently or temporarily, on equipment to collect data on operating conditions, such as vibration or temperature data. A controller manages the sensors and gathers data collected for transmission via a wireless or wired network. Data is analyzed by software and transmitted, along with the results of the analysis, via a user interface or a plug-in which interfaces with a maintenance management system or operator control system. 
         [0008]    More specifically, the system and method for condition based monitoring of an asset, such as a machine, in accordance with the invention senses time sequenced operational information about the asset through at least one sensor associated with the asset, wherein the operational information encompasses a plurality of time sequenced operational parameters of the asset. The operational information is transferred to a storage device and later transmitted, as a plurality of data packets each containing only as divided portion of the operational information from the storage device into respective mapped locations within multiple, dedicated databases provided in at least one remote storage device. When data analysis is desired, select ones of the plurality of data packets are retrieved from one or more of the mapped locations and the time sequenced operational information from the select ones of the plurality of data packets is analyzed, such as with a portable computer containing user specific software, in diagnosing a predetermined operational feature of the asset. 
         [0009]    A primary advantage of the invention is to provide a system for managing and analyzing large quantities of data that is scalable. 
         [0010]    Another advantage of the invention is to provide a system for monitoring systems and machinery on to near real time basis. 
         [0011]    Another advantage of the invention is to provide a user configurable data retrieval system for monitoring and assessing system operating conditions. 
         [0012]    Another advantage of the invention is to allow for distributed storage of data in remote locations, including “cloud” storage. 
         [0013]    Another advantage of the invention is to provide a method for expert access to data representative of systems for analysis. 
         [0014]    Additional objects, features and advantages of the present invention will become more readily apparent from the following detailed description of preferred embodiments when taken in conjunction with the drawings wherein like reference numerals refer to corresponding parts in the several views. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0015]    The drawings constitute a part of this disclosure and include exemplary embodiments to the invention, which may be embodied in various forms. It is to be understood that, in some instances, various aspects of the invention may be shown exaggerated or enlarged to facilitate an understanding of the invention. 
           [0016]      FIG. 1  is as block diagram showing system components according to a preferred embodiment of the invention. 
           [0017]      FIGS. 2A-2C  are graphs representing a collection of system components. 
           [0018]      FIG. 3  is a schematic diagram of the system of  FIG. 1 . 
           [0019]      FIGS. 4A and 4B  are flow charts showing process steps for a data acquisition service according to a preferred embodiment of the invention. 
           [0020]      FIG. 5  is a flow chart showing process steps for an uploader program according to a preferred embodiment of the invention. 
           [0021]      FIGS. 6A-6C  are flow charts showing the process steps for a downloader program according to a preferred embodiment of the invention. 
           [0022]      FIGS. 7A-7F  are flow charts showing the process steps for a configurator program according to a preferred embodiment of the invention. 
           [0023]      FIGS. 8A-8C  are flow charts showing the process steps for an explorer program according to a preferred embodiment of the invention. 
           [0024]      FIGS. 9A-9C  are flow charts showing the process steps for a dashboard program according to a preferred embodiment of the invention. 
           [0025]      FIGS. 10A-10G  are flow charts showing the process steps for a manager program according to a preferred embodiment of the invention. 
           [0026]      FIGS. 11A and 11B  are flow charts showing the process steps for an integration server program according to a preferred embodiment of the invention. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0027]    Detailed descriptions of preferred embodiments of the invention are provided herein. It is to be understood, however, that the present invention may be embodied in various forms. Therefore, specific details disclosed herein are not to be interpreted as limiting, but rather as a basis for the claims and as a representative basis for teaching one skilled in the art how to employ the present invention in virtually any appropriately detailed system, structure or manner. 
         [0028]    With initial reference to  FIG. 1 , there is shown an overall system  20  for monitoring and reporting equipment operating conditions and diagnostic information. As depicted, a database service including a first, preferably local database or databases  30  provides an area to store information. Data is initially collected by data collection devices  40  which are linked by communication wires to individual sensors  60  attached to a monitored asset  70  which may be as group of machines or various pieces of equipment or infrastructure. Each sensor  60 , or plurality of sensors, installed on a given piece of equipment or asset  70  is connected to data collection devices which may constitute controllers for providing power to sensors  60  and determine the frequency of data collection. Data collection devices  40  also collect data, such as time sequenced operational information from sensor  60 , for transmission via as network or device communication service  45  that is then passed on to a data acquisition service (DAQ) processor  100  and database or databases  30 . The controller is connected to a network, such as a wide area network (WAN) or a local area network (LAN), via either as wired connection or a wireless connection. Data is transmitted via as transmitter such as DAQ processor  100  to a database or a plurality of databases  30 . DAQ processor  100  is responsible for distributing data to the database or databases  30  and from the database or databases  30  to the next level of data distribution or management. DAQ processor  100  receives data from data collection devices  40  and matches a data source with an appropriate data target(s) for storage and analysis. DAQ processor  100  analyzes the data according to a diagnostic configuration associated with the data target(s). DAQ processor  100  then divides the operational information into a plurality of data pockets each containing a portion of the operational information and transmits the plurality of data pockets from local storage device, e.g., database or databases  30  into respective mapped locations in multiple dedicated databases provided in at least one remote storage device, e.g., long term storage  120  and stores analysis results on the appropriate database or databases. Results from database or databases  30  are transmitted via an object linking and embedding for process control (OPC) service to control systems, such as supervisory control and data acquisition (SCADA) or a distributed control system (DCS) via DAQ processor  100  as best seen in  FIG. 3 . Results from the database are also transmitted via a subscription uploader  110  to long term storage (e.g., cloud services, remote storage, or local storage)  120 . Data from long term storage  120  is transmitted to the database at step  30  via a subscription downloader  185 . Database information is also accessible to the user via a user interface constituted by various applications  150 - 180  represents software configured to retrieve select ones of the plurality the data packets from one or more of the mapped locations, and analyzing the time sequenced operational information from the select ones of the plurality of data packets in analyzing a predetermined operational feature of the asset as described in more detail below. The user interface further enables the user to configure the system and manage the database or databases  30 . 
       Design Principle Details 
       [0029]    Principle A: A graph of objects is used to represent a collection of assets, measurements, processing agents and the relationships between them as shown in  FIG. 2A . 
         [0030]      FIG. 2A  shows agent objects  251  interconnected with several other objects such as measurement objects  252 , asset objects  253  and measurement objects  254 . Generally,  FIG. 2A  shows how data may be stored and retrieved as objects.  FIG. 2B  is similar to  FIG. 2A  but adds a configuration  261  which may be imposed on the database, data visualization  263  which may be obtained from the database, data processing  267  and data distribution  254  which may be obtained from the database and event data  268  is also depicted. 
         [0031]    The system may use the MIMOSA object schema for many object primitives (see http://www.mimosa.org/?q=resources/specs for more information which is incorporated herein by reference). Other protocols or object oriented databases may be employed well known to those of skill in the art. 
         [0032]    Principle B: The same graph of objects is used throughout the system to support different activities: mainly configuration, data processing, data distribution, and data visualization as shown in  FIG. 2B . 
         [0033]    Principle C: Data is disassembled for distribution or long term storage as shown in  FIG. 2C : The data processor  270  will send data either to local storage  272  or process the data according to asset configuration updates  274 , asset data updates  276  and asset status updates  278 . From there data can be integrated in a server  280  and then an external system  281  or the data may be sent via a data uploader  282  to storage which may store additional information such as user accounts and access controls  284 , asset configuration updates  286 , asset data updates  288  and asset status updates  290 . When information needs to be retrieved a data downloader  292  will bring the data back to storage  294 . 
         [0034]    Principle D: Users of the data can query for a specific range of data, download a collection of updates, and reassemble the updates into a dataset that provides a specific utility. 
         [0035]    Principle E: Pluggable framework that allows for system extension of data collection, data processing, data exchange, and data visualization capabilities. 
       Use Case Map 
     Installation and Setup 
       [0036]    a) Design principle (A) allows a user to create any asset structure that represents the monitored assets, the sensor assets, the data acquisition assets, and the physical connections between them. This provides the flexibility to model the physical representation of the monitored installation in an intuitive way with limited training. 
         [0037]    b) Design principles (B) and (E) allow the user to use different tools to create a complete configuration that contains measurement and processing objects without being aware of their internal structure. This allows lower-skill personnel to complete complex configuration tasks that would typically require an expert. 
         [0038]    c) Design principle (E) gives users the ability to import assets from external systems or to create them from templates. This simplifies tedious or repetitive configuration work. 
       Data Collection, Data Processing, and Data Distribution 
       [0039]    a) Design principles (B) and (E) allow the data collection sub-system to convert proprietary data structures received from proprietary data acquisition devices to be converted into standard objects, preferably standard MIMOSA objects. This allows the consumers of data to be data acquisition system agnostic. 
         [0040]    b) Design principles (B) and (E) allow the data processing sub-system to invoke embedded or external diagnostic modules and store diagnostic results preferably as MIMOSA measurement event objects. This allows for the system to leverage different diagnostic systems simultaneously and to be extended with limited impact on other sub-systems. 
         [0041]    c) Design principles (C) and (E) allow the system to deliver data to multiple target systems that have unique data formats. This allows for the system to satisfy many integration and data distribution requirements. 
       Data Access, Data Selection, and Data Visualization 
       [0042]    a) Design principles (C) and (D) allow users to search and retrieve data for a specific timeframe or a timeframe in which an asset anomaly is present or a specific data type. This allows users to explore data on computers that have limited capabilities. 
         [0043]    b) Design principles (C) and (D) allow the owner of the data to choose specific data that they would like to share with other local or remote users. This gives data owners the flexibility to manage data access control per asset and per timeframe. 
       Extending the System to Add a New Device and a New Diagnostic Module 
       [0044]    a) Design principles (A), (B), and (E) allow a software developer to add a new asset type and a new diagnostic agent type that represent the new data collection device and the new diagnostic engine. Major system enhancements can be delivered without impacting the core data management and data distribution frameworks. 
         [0045]    Turning back to  FIG. 1 , there is shown a block diagram of the overall system  20  according to a preferred embodiment of the invention.  FIG. 1  shows the main components of system  20 , including the controller which consists of a processor, databases or databases  30 , a wireless and/or wired communication service  45 , and connectors  50  for sensor leads. The controller manages operation of sensors  60  and receives data from connected sensors  60 . Data collected relates to operating condition of equipment or monitored assets  70  including vibration, temperature, and electrical signals, among other sensed data. When configured to collect analog data, the controller includes an analog to digital converter in data collection devices  40 . 
         [0046]    As seen in  FIG. 3  monitored assets  70  are preferably machines equipped with sensors  60  that collect information. A data acquisition device preferably is constituted by a data collection device  40  and communications service  45  that transmits data to local database or databases  30  via a network  245 . A processor preferably constituted by DAQ processor  100  consists of software that is responsible for distributing data to the database or databases  30  and from database or databases  30  to the next level of data distribution or management such as corporate network  246  or control network  247  or a large network of publically accessed computers such as the internet. DAQ processor  100  receives data from controllers and matches the data source with the appropriate data target(s) for storage and analysis. DAQ processor  100  is preferably configured to divide the information into small data packets, send the data packets from local database or databases  30  to multiple databases in long term storage  120  containing information from other machines, and develop mapping information regarding the location of the data packets. DAQ processor  100  analyzes the data according to a diagnostic configuration associated with the data target(s). DAQ processor  100  then stores analysis results on the appropriate database or databases  30 . An uploader  110  service consists of software that is responsible for facilitating transfer of data between DAQ processor  100  and long term storage  120 . A downloader  185  consists of software that is responsible for facilitating transfer of data between long term storage  120  and database or databases  30  to allow monitored asset  70  to be diagnosed based on the data packets retrieved from long term storage  120 . 
         [0047]    The user interface ( 150 - 180 ) consists of at least one application or a piece of client software such as explorer  170  discussed in more detail below and configured to retrieve the data packets by using the mapping information and diagnose machine or monitored asset  70  using the information in the data packets retrieved from long term storage  120 . The user interface includes a configurator  150  which allows the user to establish operating parameters for the present invention and provides a guide for physical installation, and preferably includes a data visualization component which allows a user to view data and analysis results from the database or databases  30  and/or a manager  160  which allows the user to manage the database or databases  30 . The details of the operation each component is described more fully below. 
       Operation of the System 
       [0048]    At a prescribed time or interval, the controller energizes one or more sensors  60 . Each sensor  60  collects data, such as time domain sampling data sets from an accelerometer for vibration data, which is transmitted to the controller. The controller gathers data from the sensor or sensors  60  which are connected to the controller for a designated period of time before de-energizing the sensor or sensors  60  which are connected to the controller. The controller then transmits the collected data set or data sets via a wired or wireless network, WAN or LAN in device communication service  45 , to DAQ processor  100 . DAQ processor  100  receives data from the controller(s) and matches the data source with the appropriate data target(s) for storage and analysis. DAQ processor  100  analyzes the data according to a diagnostic configuration associated with the data target(s). DAQ processor  100  then stores analysis results on the appropriate database or databases  30 . Database or databases  30  provide access to the data and analyses of the data stored locally, remotely, or via long term storage  120  via the user interface such as explorer  170 . 
         [0049]    In an enterprise setting, a plurality of “balance of plant” equipment or assets  70  are equipped with sensors  60  as necessary and data collection device  40 . Each data collection service  40  connects to the network, either LAN or WAN through device communication service  45 . Database or databases  30  are available to maintenance personnel and appropriate specialists to analyze the data and make maintenance decisions regarding “the balance of plant” equipment. 
         [0050]    Step Processor— 
         [0051]    See  FIGS. 4A and 4B  for a flow chart of the process steps for DAQ Processor  100 . 
         [0052]    DAQ Processor  100  is a single instance background program that will Identify sources of data (Startup Process  300 ); and Facilitate data flow (Update Process  400 ). 
       Startup Process 
       [0053]    In startup process  300  ( FIG. 4A ), DAQ Processor  100  retrieves the list of active databases from a Master Database  310 . From each active database, DAQ Processor  100  obtains device list at  330 . DAQ Processor  100  constructs a device database map to determine data processing channels. DAQ Processor  100  queries each device to obtain the data collection schedule and verities data collection is current according to each device&#39;s respective schedule stored in local databases  320 . DAQ Processor  100  then monitors the network for messages at  340 . 
       Update Process 
       [0054]    In update process  400  ( FIG. 4B ), upon receiving a message  410  (from a device or other software component), DAQ Processor  100  identities the message type and verities the configuration ID contained in the message against the configuration ID in the target database(s) at step  420 . If configuration IDs do not match, the message is rejected. The message data is added at step  430  to the target objects in the target database in local databases  320 . When appropriate, DAQ Processor  100  will invoke a diagnostic agent at  440  to analyze data included in a message and save the diagnostic results as well as the data in local databases  320 . DAQ Processor  100  calculates the asset hierarchy status for the local database(s) at step and saves the results on the local database(s)  320 . Based upon the history depth parameter, the DAQ Processor  100  deletes at step  450  the oldest data in the local database(s)  320 . DAQ Processor  100  evaluates the properties of the database, creates appropriate update files at  470 , and saves the file to the database distribution folder  475 . If an integration flag is set at  480  then integration update files are reset to folder  415 . 
         [0055]    CBM Uploader Description— 
         [0056]    See  FIG. 5  for a flow chart of the process steps of an uploader  500 . 
         [0057]    Uploader  500  is a single-instance application that will deliver databases and database updates from the owners of the database to subscribers and Download commands from subscriber to the owner of the database. Uploader  500 , at step  510 , gets a list of approved databases that have subscriptions. Then, at step  520 , uploader  500  scans for update files from various database distribution folders  225 . At step  530  all updated files are uploaded to all subscriber and placed in long term storage system  545 . Master database  310  is provided with a database list to allow it to provide a list of approved databases with subscriptions. At step  550  update records are created for all subscribers and also placed in long term storage system  545 . Updated files are then deleted at  560  and the remaining files in database distribution folders  565  are used to create a file list  540  of those files present after the update. Next uploader  500  scans all subscribers for command records at step  570  and downloads command files at  580  from long term storage system  545 . Command files are also placed in a DAQ command folder  585 . Once all the processes are completed their command files and record files are deleted at  590  and the process ends. 
         [0058]    An application saves a file that describes a given task for the uploader  500  to the Output folder of a given database related to the application. This task file has a special format (e.g., XML) and extension (e.g., UPLOADTASK). The uploader watches the Output folders of all databases (DB) that have subscriptions for new tasks and processes them. 
         [0059]    Each task describes the one event to send to subscribers. Sending an event means uploading a file(s) to a storage device or service and saving a corresponding event record to subscriber&#39;s account in the storage DB. Each event record contains information such as the update type, the reference to uploaded file (if any) and the serialized object that specifies the information about update&#39;s content. For examples, see the list of update types in Table 1. 
         [0000]    
       
         
               
               
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                   
                   
                   
                 Update&#39;s Content 
               
               
                 Type 
                 Description 
                 File 
                 Info 
               
               
                   
               
             
             
               
                 Database 
                 The database to 
                 DIAG.YAP file from 
                 1. Fully-qualified 
               
               
                   
                 install on 
                 the database folder 
                 name of the 
               
               
                   
                 subscriber&#39;s machine 
                   
                 database 
               
               
                   
                   
                   
                 2. The size of the 
               
               
                   
                   
                   
                 file. 
               
               
                   
                   
                   
                 3. DIAG.YAP file&#39;s 
               
               
                   
                   
                   
                 URL. 
               
               
                   
                   
                   
                 4. The hierarchy of 
               
               
                   
                   
                   
                 machines taken 
               
               
                   
                   
                   
                 from the Database 
               
               
                   
                   
                   
                 Profile. 
               
               
                   
                   
                   
                 5. The version of 
               
               
                   
                   
                   
                 the database 
               
               
                   
                   
                   
                 schema. 
               
               
                 Measurement 
                 The update that 
                 MAIN FILE. A file 
                 1. MAIN FILE&#39;S 
               
               
                 Events 
                 contains new 
                 that contains new 
                 URL 
               
               
                 Update 
                 recommendations, 
                 trend measurement 
                 2. The size of the 
               
               
                   
                 trend, spectrum and 
                 events, diagnostic 
                 MAIN FILE. 
               
               
                   
                 time-wave 
                 recommendations 
                 3. SPECTRUM 
               
               
                   
                 measurement events. 
                 and stubs of 
                 FILE&#39;S URL. 
               
               
                   
                   
                 spectrums and time- 
                 4. The size of the 
               
               
                   
                   
                 wave measurement 
                 SPECTRUM FILE. 
               
               
                   
                   
                 events. Spectrums 
                 5. TIMEWAVE 
               
               
                   
                   
                 and time-wave stubs 
                 FILE&#39;S URL. 
               
               
                   
                   
                 are empty spectrum 
                 6. The size of the 
               
               
                   
                   
                 and time-wave 
                 TIMEWAVE FILE. 
               
               
                   
                   
                 measurement events 
               
               
                   
                   
                 (with empty arrays 
               
               
                   
                   
                 of data). 
               
               
                   
                   
                 SPECTRUM FILE. 
               
               
                   
                   
                 A file that contains 
               
               
                   
                   
                 new spectrum 
               
               
                   
                   
                 measurement events. 
               
               
                   
                   
                 TIMEWAVE FILE: 
               
               
                   
                   
                 A file that contains 
               
               
                   
                   
                 new time-wave 
               
               
                   
                   
                 measurement events. 
               
               
                 Alarm 
                 The alarm region 
                 File that contains 
                 The URL of the 
               
               
                 Regions 
                 changes 
                 database 
                 alarm region 
               
               
                 Update 
                   
                 configuration 
                 changes file. 
               
               
                   
                   
                 changes. 
                 The size of a file. 
               
               
                 Machine 
                 The summary status 
                 &lt;NO FILE&gt; 
                 Machine UID. 
               
               
                 Status 
                 of machines 
                   
                 The name and UID 
               
               
                   
                   
                   
                 of the diagnostic 
               
               
                   
                   
                   
                 agent that is the 
               
               
                   
                   
                   
                 provider of the 
               
               
                   
                   
                   
                 status. 
               
               
                   
                   
                   
                 Machine alarm 
               
               
                   
                   
                   
                 status that specifies 
               
               
                   
                   
                   
                 the alarm type of 
               
               
                   
                   
                   
                 most critical alarm 
               
               
                   
                   
                   
                 of the machine (if 
               
               
                   
                   
                   
                 any). 
               
               
                   
               
             
          
         
       
     
         [0060]    Downloader Description— 
         [0061]    See  FIG. 6  for a flow chart of the process steps for a downloader  185 . 
         [0062]    Downloader  185  is a single-instance application that will update user database lists (Startup Process  600  of  FIG. 6A ); retrieve database information (Selection Process  700  of  FIG. 6B ); and update local database servers (Update Process  800  of  FIG. 6C ). 
       Startup Process 
       [0063]    Downloader  185  connects to long-term storage  630 , using one or more user accounts  610 . Based on account access authorization, Downloader  185  gets a list of authorized databases from long-term storage system  630  and compares at step  620  that list with the local copy of the remote database list  650 . Finally, Downloader  185  updates the local remote database list by adding new databases and deleting removed databases at  640 . 
       Selection Process 
       [0064]    A user reviews the database list and at  710  selects a database to retrieve information from. The user identifies criteria at  710  for information to be accessed (e.g., entire data set). Downloader  185  updates the database list with the download criteria at  720  and provides access to the database at  730 . 
       Update Process 
       [0065]    An application  800  changes data in a database. Downloader  185  searches all databases  650  for changes to database files at  820 . Downloader  185  updates the database update lists  830  and downloads at  850  the update files to each database&#39;s distribution folder  880 . Downloader  185  applies changes at  860  to all copies of each local database by merging the update files into the database  870 . Downloader  185  deletes update at  890  files after all updates have been completed. See Table 1, above, for sample update types. 
         [0066]    Configurator— 
         [0067]    See  FIGS. 7A-7F  for as flow chart showing the process steps of the configurator. 
         [0068]    Configurator  150  consists of a software module enabling the user to perform several tasks necessary for installation, configuration, and operation of the condition based monitoring system. Configurator  150  allows the user to: 1) Create, update, delete components of the condition based monitoring system; 2) Determine number of sensors  60  required and placement thereof; 3) Generate a list of required components to facilitate condition based monitoring of a machine or plurality of monitored asset  70 ; and 4) Generate suggested configuration of data analysis software. 
         [0069]    Configurator  150  is a multi-instance program that will: Allow the user to create, connect to, and edit a database (Open Database Process  900  of  FIG. 7A ); Allow the user to manage monitored assets (Create Asset Process  1000  of  FIG. 7B ); Allow the user to manage diagnostic parameters (Build Diagnostics Process  1100  of  FIG. 7C ); Allow the user to create diagnostic agents (Machine Diagnostic Wizard Process  1200  of  FIG. 7D ); Allow the user to complete a database (Complete Database Process  1300  of  FIG. 7E ); and Allow the user to rollback a database (Rollback Database Process  1400  of  FIG. 7F ). 
       Open Database Process 
       [0070]    Master Database  930  houses a list of available databases and database configuration parameters. Via configurator  150 , user  910  accesses at  920  the list of available databases. Configurator  150  allows user  910  to edit the configuration of an existing database from the database list at  960 . Master Database  930  determines the user&#39;s access based on the user&#39;s privileges and database information. The databases are managed by a database server program  950 . 
       Create Asset Process 
       [0071]    Available asset types are stored in an Asset Taxonomy (MIMOSA is one example but others exist well known to those of skill in the art). Configurator  150  provides user  910  access to an Asset Taxonomy database  1030 . User  910  may select an existing asset type at  1020  or create a new asset type at  1040  (e.g., site, asset, or transducer) in order to add an asset instance at  1050  to a database  1060  (created or accessed via the Configurator&#39;s Open Database Process  900 ). Configurator  150  also allows user  910  to establish the relationship(s) between asset instances. Once created, the asset is added to the Asset Hierarchy in database  1060  and, if a new type, the list of asset types. 
       Build Diagnostics Process 
       [0072]    A given database  1060  will house a list of diagnostic agents (diagnostic agents are comprised of several parts including device sampling configuration objects, symptoms and recommendation objects, and layout objects). Via configurator  150 , user  910  accesses the list of diagnostic agents. Configurator  150  will compile all agents which creatures all objects needed to facilitate monitoring. User  910  uses a diagnostic process to insure all diagnostic agents are configured at set  1120 . The process then saves a copy of the database at  1130  in the database folder  1140 . Next at step  1150  diagnostic configurations are loaded from all agents from database  1060 . At step  1160  the process builds data acquisition device sampling configuration objects and then builds diagnostic agent symptom and recommended objects at  1180 . A process then builds a machine user interface layer objects at  1190  and sets the status of all diagnostic agents to complete at  1195 . 
       Machine Diagnostic Wizard Process 
       [0073]    User  910  launches a wizard  1200  on a machine. Configurator  150  checks a database  1060  for existing diagnostic agents and creates one if necessary at  1230 . User  910  selects a diagnostic template  1240  from the machine templates available at  1245 . Configurator  150  maps, at  1250 , the template components to the monitored asset components according to information stored in database  1060 . User  910  enters component parameters at  1255 . User  910  selects the appropriate diagnostic level and sensor requirements at  1260 . Configurator  150  maps at  1265 , the requirements to the monitored asset sensors  60 . Configurator  150  allows user  910  to update the default limit levels at  1270  if user  910  would like to do so. Configurator  150  sets the diagnostic agent processing interval at  1275 . Configurator  150  saves the diagnostic configuration in the diagnostic agent in database  1060  at  1280 . 
       Complete Database Process 
       [0074]    User  910  sets database status to complete in process  1300 , this indicates that database  1060  is ready for monitoring. Configurator  150  ensures that all diagnostic agents are complete at  1320 . Configurator  150  saves a copy of the database assets and diagnostics to a database folder  1335  at  1330 . Configurator  150  then sets the database status to complete at step  1340  in Master Database  930 . 
       Rollback Database Process 
       [0075]    User  910  initiates a database rollback. Configurator  150  ensures that the database  1060  has not been approved and is inactive at  1420 . Configurator  150  deletes all database objects at  1430 . Configurator then loads at  1440  objects from a backup database  1445  and, at  1450 , saves database  1060  to the database server. 
         [0076]    Explorer— 
         [0077]    See  FIGS. 8A-8C  for flow charts showing the process steps of Explorer  170 . 
         [0078]    Explorer  170  is a multiple-instance program that will allow the user to connect to a database (Open Database Process  1500  of  FIG. 8A ); allow the user to connect to a monitored asset (Open Machine Process  1600  of  FIG. 8B ); and allow the use to review data (View Data Process  1700  of  FIG. 8C ). 
       Open Database Process 
       [0079]    Master Database  930  houses a list of available databases configuration parameters. Via explorer  170 , user  910  accesses the list of available databases. Explorer  170  allows user  910  to select at  1540  a database to access from database server  1550 . Master Database  930  determines the user&#39;s access based on the user&#39;s privileges and database information. Databases  1060  are stored on a database server. Explorer  170  will load appropriate user commands at  1560  and load asset hierarchy objects at  1570 . 
       Open Machine Process 
       [0080]    Upon accessing a particular database, Explorer  170  will allow user  910  to access or select any monitored asset  70  at  1620  (e.g., a machine). Explorer  170  will load objects associated with monitored asset  70  for the user  910  to view at  1636 . Explorer  170  allows user  910  to review alarm event objects, view alarm data, review recommendations at  1650 , and open empty charts at  1660 . User  910  may also set default preferences  1670  for empty charts and send new alarm configuration data via the Explorer  170 . 
       View Data Process 
       [0081]    Upon accessing a particular monitored asset, Explorer  170  will allow user  910  to access data associated with monitored asset  70 . User  910  will select symptom(s) to review at  1720 . Explorer  170  loads all objects and allows user  910  to view the associated data at  1730  from database  1060 . User  910  may select symptom samples at  1750  and Explorer  170  will load all related objects unto appropriate views at  1760 . 
         [0082]    Dashboard— 
         [0083]    See  FIGS. 9A-9C  for a flow chart showing the process steps of dashboard  180 . 
         [0084]    Dashboard  180  is a single-instance program that will allow the user to create long term storage access accounts (Add Storage Account Process  1800  of  FIG. 9A ); allow the user to initiate updates (Update Process  1900  of  FIG. 9B ); and allow the user to request a database download (Request Download Process  2000  of  FIG. 9C ). 
       Add Cloud Account Process 
       [0085]    User  910  initiates the process to add a long term storage user account  1820 . Dashboard  180  assigns the account to the appropriate long term storage. User  910  enters the account name and password at  1830 . Downloader  185  saves the long term storage user account at  1840  in the long term storage accounts file  1850 . 
       Update Process 
       [0086]    User  910  initiates an update at  1920 . Dashboard  180  logs in at step  1930  to the long term storage system(s)  1940  using all accounts from the long term storage accounts file  1850 . Dashboard  180  gets the latest update time  1945  from an asset file  1950 . Dashboard  180  queries for new database records at  1955  and if new databases are found saves new asset objects at  1960 . Dashboard  180  queries the long term storage system(s) at  1965  for new status records. Dashboard  180  saves the new machine status objects at  1970  to the machine status file at  1975  and rebuilds the user interface at  1980 . 
       Request Download Process 
       [0087]    User  910  selects, at  2030 , a monitored asset  70 . Dashboard  180  displays the status records at  2030 . User  910  selects an appropriate time range for download at  2040  and requests a download at  2050 . Dashboard  180  sends a message to Downloader  185  to initiate the download at  2060 . 
         [0088]    Manager— 
         [0089]    See  FIGS. 10A-10G  for a flow chart showing the process steps of Manager  160 . 
         [0090]    Manager  160  is a single-instance program that will: Retrieve lists(s) of monitored assets from database server(s) and retrieve their properties for display from the Master Database (Startup Process  2100  of  FIG. 10A ); Allow user to create databases (Create Database Process  2200  of  FIG. 10B ); Allow user to update database status (Change Database Status Process  2300  of  FIG. 10C ); Allow user to copy databases (Copy Database Process  2400  of  FIG. 10D ); Allow user to create guest user accounts (Create Guest User Process  2500  of  FIG. 10E ); Allow user to subscribe a database to log-term storage (Subscribe Database Process  2600  of  FIG. 10F ); and Allow user to modify the data acquisition schedule (Modify Acquisition Schedule Process  2700  of  FIG. 10G ). 
       Startup Process 
       [0091]    Manager  160  will retrieve list(s) of monitored assets  70  from database server(s) at  2120 . Manager  160  will retrieve database properties from Master Database  930  and display the database properties to user  910  at  2130 . 
       Create Database Process 
       [0092]    User  910  will provide a unique database name at  2220 . Manager  150  will create new local folders from database files and empty database files on the database server at  2230 . Manager  160  will create a database master record at  2240  on Master Database  930  and send a database ready message at  2250  once the database has been created to a database server  2110 . 
       Change Database Status Process 
       [0093]    Manager  160  will allow user  910  to change the status of the database (e.g., configuration status or processing status) at  2310 . Manager  160  will update the database status at  2320  on Master Database  930  and send as database status message  2330  to DAQ Processor  100 . 
       Copy Database Process 
       [0094]    User  910  initiates a database copy process  2410 . Manager  160  will contact database server  2110  to release the database at  2420 . Manager  160  creates a new folder and copies, at  2430 , database files to a new location  93 , at  2435 . Manager  160  then creates a database record at  2440  on Master Database  930 , at  2440 . Manager  160  also sets the copied database status to “Complete” if the original database status was “Approved.” Manager  160  then sends a database ready message  2450  to database server  2110 . 
       Create Guest User Process 
       [0095]    User  910 , with appropriate credentials, logs in  2510 . Manager  160  verifies credentials. User  910  initiates the guest user creation module  2520  and enters a unique guest user account name and password at  2530 . The user  910  provides database access information at  2540 . Manager  160  saves the new guest account at  2550  and updates Master Database  930  and long term storage  120 . 
       Subscribed Database Process 
       [0096]    A user  910  selects an approved database at  2610  from master database  930 . manager  160  selects an administrative storage account at  2620  from the account list in master database  930 . manager  160  then saves a subscription record to master database  930  at step  2630 . Next manager  160  sends database status message to  2640  to DAQ processor  100 . 
       Modify Acquisitions Process 
       [0097]    User  910  reads a current 24 hour acquisitions schedule displayed at  2710  by a manager  160 . User  910  then selects a diagnostic agent at  2720 . Which is modified by user  910  to a certain wake up interval, wake up start time. Manager  160  finds all shared diagnostic agents at step  2740  and then updates the wake up interval of all shared agents in associated acquisition devices at step  2750 . User  910  then initiates commit changes at  2760  and manager  160  insures that DAQ Processor  100  is not running at step  2770 . Manager  160  then saves new wake up intervals and wake up start times at  2780  to databases  2790 . 
         [0098]    Integration Server— 
         [0099]    See  FIGS. 11A ,  11 B for a flow chart showing the process steps of the integration server. 
         [0100]    Integration server  190  is a single-instance program that will facilitate communication between database or databases  30  and other enterprise systems  195  (e.g., CMMS, EAM, ERP) via a standard protocol (e.g. OPC, MIMOSA, SOA 2800); and create object hierarchy for enterprise systems (Startup Process  2800  of  FIG. 11A ); and continuously update object values for enterprise system client applications (Update Process  2900  of  FIG. 11B ). 
       Startup Process 
       [0101]    Integration Server  190  will get a list of databases from master database  930  which have been designated for communication with other enterprise systems (e.g., CMMS). Integration Server  190  loads the asset hierarchy, symptom objects at  2820  from database  2790 , alarm, and recommendation objects from the appropriate database(s) at  2830 . Integration Server  190  creates an appropriate hierarchy according to the requisite protocol (e.g., OPC) at  2840 . 
       Update Process 
       [0102]    Integration Server  190  loads at step  2910  symptom event updates, alarm at step  2920 , and recommendation event objects from latest database update files  2930 . Integration Server  190  updates at  2940  the object values according to a requisite protocol and a target engineering unit system  2950  (e.g., Metric). Integration Server  190  runs the update process continuously or on a defined interval  2960 . 
         [0103]    As can be seen from the above discussion, the condition based monitoring solution provides the operator with data on the operating condition of balance of plant equipment and highlights out-of-norm condition in near real-time in order to minimize down time, minimize maintenance costs by indicating the need for repair before a catastrophic failure, and does so without the need for increasing the size of an existing maintenance staff. Such a solution provides data to be communicated to experts for analysis and maintenance recommendations. A condition based monitoring solution further provides an operator with the ability to verify a machine returns to efficient operating conditions following as maintenance or repair event. 
         [0104]    The method and system of the current invention may be employed in conjunction with any of a variety of diagnostic engines or systems appropriate to the machine or device involved. Further, the method and system may be integrated into existing software and control systems already in place at an enterprise or facility. In addition, the method may be scalable to several machines, and employed in a single, mobile unit. Further, the system of the present invention may be utilized on other environments that require levels of monitoring, such as infrastructure, bridges, train tracks, waterways, electrical grid, buildings and the like. 
         [0105]    Although described with reference to preferred embodiments of the invention, it should be readily understood that various changes and/or modifications can be made to the invention without departing from the spirit thereof. In general, the invention is only intended to be limited by the scope of the following claims.