"Intelligent" sensor data analysis for device diagnostics

Abstract

The invention relates to intelligent sensor data analysis for device diagnostics. A system for performing sensor data analysis for device diagnostics features an alarm feature and a diagnostic detector having a signal processor configured to: receive signaling containing information, and send the signaling to the diagnostic detector; the information is related to alarm characteristics which are time-stamped aiming at captured alarm characteristic parameters so as to monitor sensed data of the rotary equipment and also related to diagnostic detector characteristics of a diagnostic detector related to alarm conditions of the rotary equipment; and determining a corresponding signaling containing information about an alarm diagnosis based on a match between the alarm feature and one of the diagnostic detector features contained in the received signaling.

Description

[0001] This application is a divisional application of the Chinese patent application filed on August 13, 2020, with application number 201880089332.8 and invention name “Smart Sensor Data Analysis for Equipment Diagnosis”. The international filing date of the parent application is December 12, 2018, and the international application number is PCT / US2018 / 065189.

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of Provisional Application No. 62 / 598,123, filed December 13, 2017, which is incorporated herein by reference in its entirety. Technical Field

[0004] The present invention relates to a system for monitoring rotating equipment; more particularly, to a system for monitoring rotating equipment and diagnosing alarm conditions. Background Art

[0005] In the prior art, large data sets (so-called "big data") are required to develop alarm detectors. The large data sets need to be provided from sensor modules placed or arranged on the rotating equipment and transmitted to a remote processing computer, server or other processing configuration. The large data sets can be transmitted using known hardwired or wireless data communication technologies, which causes large-scale remote data processing problems, including bandwidth problems, etc.

[0006] Furthermore, physics-based models are currently used in the prior art to diagnose equipment alarms. Their success rate is approximately 50 / 50 and requires resident experts to complete the diagnosis.

[0007] In view of these shortcomings of known techniques, there is a need in the industry for better methods of monitoring rotating equipment and diagnosing alarm conditions that develop in rotating equipment. Summary of the invention

[0008] The present invention solves this problem in the art by using large sets of smart data from a large number of smart sensors that can be used for data analysis to effectively diagnose the root cause of equipment alarms.

[0009] According to some embodiments, the present invention may include or take the form of a system or device for performing sensor data analysis for device diagnostics, the system or device being characterized by an alarm feature and a diagnostic detector having a signal processor configured to

[0010] receiving signaling containing information regarding alarm characteristics of sensed data time-stamped for captured alarm characteristic parameters for monitoring rotating equipment and also regarding diagnostic detector characteristics of diagnostic detectors related to an alarm condition of the rotating equipment; and

[0011] Corresponding signaling containing information regarding an alarm diagnostic is determined based on a match between the alarm signature and one of the diagnostic detector signatures contained in the received signaling.

[0012] According to some embodiments of the present invention, the system may include one or more of the following features:

[0013] The signal processor may be configured to provide corresponding signaling containing information regarding the alarm diagnostic for further processing, including shutting down the rotating equipment for repair, or providing an audio or visual alarm warning signal, or scheduling an appropriate maintenance event.

[0014] The system may include an intelligent condition monitoring device positioned relative to the rotating equipment and configured to sense captured alarm signature parameters, time stamp the sensed captured alarm signature parameters, and provide sensed signaling containing information about the sensed, time stamped and captured alarm signature parameters.

[0015] The intelligent condition monitoring device may include or form part of an alarm feature and a diagnostic detector, or vice versa.

[0016] For example, the sensed, time-stamped, and captured alarm characteristic parameters may include one or more of the following:

[0017] Vibration (X, Y, Z axis),

[0018] Equipment temperature,

[0019] Oil level or temperature and %RH (water presence),

[0020] Suction or discharge pressure,

[0021] Motor torque, flux or speed,

[0022] flow, or

[0023] Seal health.

[0024] By way of further example, the diagnostic detector features may include features relating to: a cavitation alarm condition, a dry run alarm condition, a bearing fault alarm condition, a mechanical misalignment alarm condition, a mechanical looseness alarm condition, a vibration (X, Y, Z axis) alarm condition, an equipment temperature alarm condition, an oil level (% RH (water present)) or temperature alarm condition, a suction or discharge pressure alarm condition, a motor torque, flux or speed alarm condition, a flow alarm condition, or a seal health alarm condition.

[0025] Each alarm signature and diagnostic detector may use a corresponding or unique subset of the captured alarm signature parameters.

[0026] The alarm signature and diagnostic detector may be configured to self-learn, for example by receiving tagged or untagged alarm signatures for storage as one or more stored diagnostic detector signatures in a diagnostic detector signature database in memory.

[0027] For example, the signal processor may be configured to:

[0028] comparing the unlabeled alert signature to one or more of the existing diagnostic detector signatures to find the best match,

[0029] marking the unmarked alarm signature as an updated marked alarm signature, and

[0030] The diagnostic detector signature database is updated with the updated labeled alarm signature, thereby learning new diagnostic detector signatures.

[0031] The alarm features and diagnostic detectors may be configured remotely from the intelligent condition monitoring device, for example, contained in a cloud-based server at an off-site location remote from the rotating equipment.

[0032] According to some embodiments, the present invention may also take the form of a method having steps for performing the following operations:

[0033] receiving, with a signal processor in an alarm signature and diagnostic detector, signaling containing information regarding an alarm signature of sensed data time-stamped for alarm signature parameters captured for monitoring the rotating equipment and also regarding a diagnostic detector signature of the diagnostic detector related to an alarm condition of the rotating equipment; and

[0034] The signal processor determines corresponding signaling containing information regarding the alarm diagnostic based on a match between the alarm signature and one of the diagnostic detector signatures contained in the received signaling.

[0035] The method may further comprise one or more of the features set out herein.

[0036] The present invention provides a better method of monitoring rotating equipment and diagnosing alarm conditions that develop in rotating equipment.

[0037] Applications may include, for example, the following: Industrial equipment diagnostics, such as for rotating equipment like pumps, motors, fans. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings include Figure 1-5 , not necessarily to scale:

[0039] Figure 1 is a diagram of a smart sensor data analysis system according to some embodiments of the present invention.

[0040] Figure 2 is an exemplary i-Alert for the following device categories according to some embodiments of the present invention, for example TM Graph of a sensor summary report: Pump with 187 hours of run time, 3555 RPM, 15 motor HP, with Vrms axial, Vrms radial, Vrms horizontal graphs showing alarm identification and data capture, and also contains a temperature graph.

[0041] Figure 3 is a diagram illustrating the creation of alarm features, for example, where the creation is based on some combination of parameters related to oil %RH level / temperature, seal health, motor torque, motor flux / speed, equipment temperature, pressure (e.g., including suction / discharge), vibration (e.g., using time waveform (TWF)), flow, etc.

[0042] Figure 4 is a diagram showing an alarm signature on the left and a diagnostic detector on the right, and an indication of a match for a bearing fault based on a so-called "best" matching method, according to some embodiments of the present invention.

[0043] Figure 5 is a block diagram of a system having an alarm feature and a diagnostic detector with a signal processor for implementing signal processing functionality according to some embodiments of the present invention. DETAILED DESCRIPTION

[0044] Figure 1

[0045] Figure 1A smart sensor data analysis system, generally indicated at 100, is shown according to some embodiments of the present invention, and includes a rotating device 102, for example, having smart devices or sensors, labeled 1 to 17, placed or arranged on the rotating device 102 to sense one or more parameters related thereto. The smart devices or sensors 1 to 17 may include one or more seal sensors 1, oil quality sensors 2 for sensing % contamination, fluid level, temperature, etc., three-axis accelerometers 3 for sensing vibrations, for example, along the X, Y, or Z axis, embedded motor drives and sensors 4, embedded pump logic sensors 5 (for example, including the known PumpSmart developed by the assignee of the present invention), and the like. TM logic), suction pressure sensor 6, discharge pressure sensor 7, pump temperature sensor 8, motor temperature sensor 9 for sensing motor bearing and winding temperature, wireless communication module 10 for exchanging sensor data and signaling, DC power module for providing DC power 11 to rotating equipment, viscosity sensor 12 for sensing oil viscosity, motor current sensor 13 for sensing motor current of rotating equipment, motor flux sensor 14 for sensing magnetic flux changes to check motor health and detect faults, pH monitor 15 for sensing pH of the liquid being transported, VOC "sniffing" sensor 16, and / or drive / shaft phase / position sensor 17. The smart device or sensor may also include a network gateway for connecting the smart sensor (device) to the 'cloud'. This allows sensor data to be delivered to the 'cloud' for use in future 'cloud computing' and data analysis consistent with the functionality of the rotating equipment 102 described herein.

[0046] In the smart sensor data analysis system 100, smart devices or sensors 1 to 17 may provide, for example, smart device or sensor signaling containing smart sensor data to a "big data" cloud configuration. The smart sensor data may include one or more alarm data 'signatures'. The alarm data 'signatures' may be compared to one or more diagnostic 'detectors' (also referred to as "diagnostic 'detector' signatures"), and if the alarm data 'signatures' match the diagnostic 'detector' signatures, then the smart sensor data analysis system provides a report 'alarm' diagnostic. For example, the comparison may be implemented locally in the smart devices or sensors 1 to 17, as well as remotely in an off-site cloud-based server configuration. For example, the report 'alarm' diagnostic may be further processed to disconnect rotating equipment, issue appropriate audio or visual alarm warnings, schedule appropriate maintenance events, etc. (The scope of the present invention is not intended to be limited to the type or kind of further processing performed or required, for example, by the report 'alarm' diagnostic, and may include further processing now known or later developed in the future.)

[0047] According to some embodiments, one or more of the smart devices or sensors 1-17 may include or take the form of an alarm feature and diagnostic detector for implementing the signal processing functionality of the present invention. Embodiments are contemplated, and the scope of the present invention is intended to include implementation of the alarm feature and diagnostic detector signal processing functionality in devices or components other than smart sensors, for example, including situations where the device or component is local to the one or more of the smart devices or sensors as well as remotely located, such as for off-site implementations, etc.

[0048] Figure 2

[0049] For example, Figure 2 i-Alert TM A sensor summary report, for example, for equipment class: Pumps, with 187 hours of run time, 3555 RPM, 15 motor HP, has Vrms axial, Vrms radial, Vrms horizontal graphs showing alarm identification and data capture. Figure 2 The sensor summary report shown also includes a temperature graph.

[0050] and Figure 2 As shown in the figure, all smart sensor data captured from the timestamp of the alarm may contain one or more of the following:

[0051] - Vibration (X, Y, Z)

[0052] - Temperature - Equipment

[0053] - Temperature - Oil

[0054] -Oil level

[0055] -pressure

[0056] -Motor torque

[0057] - Seal health, etc.

[0058] An 'alarm' data feature may be created from all smart sensor data captured from an 'alarm' timestamp, for example, consistent with the disclosure herein.

[0059] Figure 3

[0060] For example, Figure 3 1 shows, for example, alarm signature creation based on a combination of one or more of the following: oil %RH level / temperature, seal health, motor torque, motor flux / speed, equipment temperature, pressure (e.g., including suction / discharge), vibration (e.g., using time waveform (TWF)), flow, etc. In practice, each alarm condition creation can be accompanied by, for example, Figure 4The alarm signature creation of one or more diagnostic detectors may be pre-programmed and stored in a diagnostic detector signature database in the alarm signature and diagnostic detectors, and / or learned and updated over time by the alarm signature and diagnostic detectors and stored in the diagnostic detector signature database, e.g., consistent with the following description.

[0061] Figure 4

[0062] Figure 4 On the left the alarm signature AS is shown and on the right the various diagnostic detector signatures D1 to D5 of the diagnostic detector are shown, together with an indication of a match for a bearing fault based on a so-called "best fit" matching approach between the alarm 'signature' and the diagnostic 'detector' signature of the bearing fault. Figure 4 As shown in , a visual comparison of the alarm 'signatures' and diagnostic 'detector' signatures for cavitation alarm conditions, dry running alarm conditions, mechanical misalignment alarm conditions, mechanical looseness alarm conditions, etc., is not as well matched as the diagnostic 'detector' signature for the bearing fault alarm condition, and is therefore not a "best" match.

[0063] For example, a cavitation alarm condition may be based in part on captured parameters including flow having greater than 25% loss, pressure having greater than 25% loss, and motor torque having greater than 5% increase. See diagnostic 'Detector' feature D1.

[0064] For example and similarly, a dry run alarm condition may be based in part on captured parameters including flow with greater than 25% loss, pressure with greater than 25% loss, and motor torque with greater than 5% increase.See diagnostic 'detector' feature D2 which has a different waveform than D1.

[0065] For example, a bearing fault alarm condition may be based in part on captured parameters including temperature greater than 75°C, oil temperature greater than 105°C, low oil level, oil %RH greater than 40%, poor seal health, and motor torque with greater than 5% increase. See diagnostic 'Detector' feature D3.

[0066] For example, a mechanical misalignment alarm condition may be based in part on captured parameters including motor torque changed by greater than 15%, motor speed changed by greater than 25%, and motor torque changed by greater than 15%. See diagnostic 'Detector' feature D4.

[0067] For example, a mechanical loose alarm condition may be based in part on captured parameters including motor flux that changes by more than 15% and motor speed that changes by more than 15%. See diagnostic 'Detector' feature D5.

[0068] exist Figure 4 It is important to note the following:

[0069] Each 'detector' may use a unique subset of the captured alarm 'signature' parameters, as shown.

[0070] 'Detectors' can learn themselves by feeding them labeled and unlabeled alert data 'features'.

[0071] For example, an unlabeled alarm 'signature' may be compared to an existing diagnostic 'detector' signature to find the so-called 'best' match. This 'unlabeled' signature may then become 'labeled' and result in a potential update to the 'overall detector' algorithm.

[0072] Figure 5 :Signal Processor Implementation

[0073] The system 100 for performing sensor data analysis for device diagnostics may include an alarm feature and a diagnostic detector having, for example, a signal processor or processing circuit / module 112 that may be configured to perform basic signal processing functionality for implementing the present invention, for example, consistent with the disclosure herein. For example, the signal processor 110 may be configured as a separate signal processor or signal processing module, forming part of a control or controller circuit / module, etc., or forming part of some other circuit / circuitry system / module. Many different types and kinds of signal processors, controllers, and controller modules are known in the art, for example, including programmable logic controllers, etc. For example, based on the understanding of such known signal processors, those skilled in the art will be able to configure the signal processor 110 to perform the aforementioned signal processing functionality consistent with the description herein.

[0074] By way of yet another example, the functionality of the signal processor 110 may be implemented using hardware, software, firmware, or a combination thereof, but the scope of the present invention is not intended to be limited to any particular embodiment thereof. In a typical software implementation, this signal processor or signal processing module may include one or more microprocessor-based architectures having a microprocessor, random access memory (RAM), read-only memory (ROM), input / output devices and controls, data and address buses connecting them similar to those in element 112, such as for running program code based on algorithms consistent with those disclosed herein. Those skilled in the art will be able to program this microprocessor-based implementation to perform the signal processing functionality described herein without undue experimentation, including situations where a signal processor and memory are combined to implement a program such as a code stored in the memory so that the signal processor implements the aforementioned signal processing functionality. The scope of the present invention is not intended to be limited to any particular implementation using technology now known or later developed in the future.

[0075] Signal processor 110 may include one or more other circuits / modules similar to element 112 to perform other functionality that is known in the art, does not form part of the underlying invention, and is not described in detail herein. For example, other circuits / modules 112 may include input / output circuits / modules, memory circuits / modules (e.g., RAM, ROM, EPROM, etc.), bus circuits / modules or architectures for exchanging signaling between various circuits / modules, etc.

[0076] In operation, the signal processor 110 may be configured to: receive a signaling containing information about an alarm feature of sensed data time-stamped for captured alarm feature parameters for monitoring rotating equipment and also about a diagnostic detector feature of a diagnostic detector related to an alarm condition of the rotating equipment; and determine a corresponding signaling containing information about an alarm diagnosis based on a match between the alarm feature and one of the diagnostic detector features contained in the received signaling. For example, the signaling may be stored in a database in a memory forming part of the element 112 and provided to the signal processor 110.

[0077] In addition, the signal processor 110 can be configured to determine and provide corresponding signaling containing information about the alarm diagnosis for further processing, including shutting down the rotating equipment for repair, providing an audio or visual alarm warning signal, or scheduling an appropriate maintenance event. For example, the provision of the corresponding signaling can be implemented by an output module forming part of the element 112.

[0078] Rotary equipment

[0079] Rotating equipment and vibrating machines or structures, such as pumps or rotary devices, reciprocating machines, engines, blowers, are known in the art and are not described in detail herein. In addition, the scope of the present invention is not intended to be limited to any particular type or kind thereof now known or later developed in the future.

[0080] Best Match Feature Comparison Technique

[0081] Best match feature comparison techniques are known in the art, and the scope of the present invention is not intended to be limited to any particular type or kind thereof now known or later developed in the future. For example, the signal processor may be configured to convert a feature waveform containing information about the alarm feature AS (see Figure 4 left) and diagnostic detector features D1 to D5 (see Figure 4 The similarity between the waveforms of the alarm feature AS and the diagnostic detector feature D3 is shown in Figure 4 It is visually apparent that is the best match, especially when compared to the waveforms of diagnostic detector features D1-D2 and D4-D5.

[0082] Regarding the implementation methods including the above embodiments, the following technical solutions are also disclosed:

[0083] Solution 1. A system for performing sensor data analysis for equipment diagnostics, comprising:

[0084] An alarm feature and diagnostic detector having a signal processor configured to

[0085] receiving signaling containing information regarding alarm characteristics of sensed data time-stamped for captured alarm characteristic parameters for monitoring rotating equipment and also regarding diagnostic detector characteristics of diagnostic detectors related to an alarm condition of the rotating equipment; and

[0086] Corresponding signaling containing information regarding an alarm diagnostic is determined based on a match between the alarm signature and one of the diagnostic detector signatures contained in the received signaling.

[0087] Option 2. A system according to Option 1, wherein the signal processor is configured to provide the corresponding signaling containing information about the alarm diagnosis for further processing, including shutting down the rotating equipment for repair, or providing an audio or visual alarm warning signal, or scheduling an appropriate maintenance event.

[0088] Option 3. A system according to Option 1, wherein the system comprises:

[0089] An intelligent condition monitoring device is positioned relative to the rotating equipment and is configured to sense the captured alarm signature parameters, time stamp the sensed captured alarm signature parameters, and provide sensed signaling containing information about the sensed, time stamped and captured alarm signature parameters.

[0090] Option 4. A system according to Option 3, wherein the intelligent condition monitoring device includes the alarm feature and a diagnostic detector.

[0091] Embodiment 5. The system of embodiment 3, wherein the sensed, time-stamped and captured alarm characteristic parameters include one or more of the following:

[0092] Vibration (X, Y, Z axis),

[0093] Equipment temperature,

[0094] Oil level or temperature and %RH,

[0095] Suction or discharge pressure,

[0096] Motor torque, flux or speed,

[0097] flow, or

[0098] Seal health.

[0099] Option 6. A system according to Option 1, wherein the diagnostic detector features include features related to: cavitation alarm conditions, dry running alarm conditions, bearing fault alarm conditions, mechanical misalignment alarm conditions, mechanical looseness alarm conditions, vibration (X, Y, Z axis) alarm conditions, equipment temperature alarm conditions, oil level, %RH or temperature alarm conditions, suction or discharge pressure alarm conditions, motor torque, flux or speed alarm conditions, flow alarm conditions, or seal health alarm conditions.

[0100] Embodiment 7. The system of embodiment 1, wherein each alarm signature and diagnostic detector uses a respective subset of the captured alarm signature parameters.

[0101] Embodiment 8. The system of embodiment 1, wherein the alarm signature and diagnostic detector are configured to self-learn by receiving labeled or unlabeled alarm signatures to be stored as one or more stored diagnostic detector signatures in a diagnostic detector signature database in the memory.

[0102] Embodiment 9. The system according to embodiment 8, wherein the signal processor is configured to:

[0103] comparing the unlabeled alert signature to one or more of the existing diagnostic detector signatures to find the best match,

[0104] marking the unmarked alarm signature as an updated marked alarm signature, and

[0105] The diagnostic detector signature database is updated with the updated flagged alarm signature.

[0106] Embodiment 10. A system according to Embodiment 3, wherein the alarm feature and diagnostic detector are configured remotely from the intelligent condition monitoring device.

[0107] Solution 11. A method for performing sensor data analysis for equipment diagnostics, comprising:

[0108] receiving, with a signal processor in an alarm signature and diagnostic detector, signaling containing information regarding an alarm signature of sensed data time-stamped for alarm signature parameters captured for monitoring rotating equipment and also regarding a diagnostic detector signature of a diagnostic detector related to an alarm condition of the rotating equipment; and

[0109] The signal processor determines corresponding signaling containing information regarding an alarm diagnostic based on a match between the alarm signature and one of the diagnostic detector signatures contained in the received signaling.

[0110] Option 12. A method according to Option 11, wherein the method includes providing the corresponding signaling containing information about the alarm diagnosis with the signal processor for further processing, including shutting down the rotating equipment for repair, or providing an audio or visual alarm warning signal.

[0111] Option 13. A method according to Option 11, wherein the method includes placing an intelligent condition monitoring device relative to the rotating equipment to sense the captured alarm characteristic parameters, time-stamping the sensed captured alarm characteristic parameters, and providing a sensed signal containing information about the sensed, time-stamped and captured alarm characteristic parameters.

[0112] Option 14. A method according to Option 13, wherein the method includes configuring the intelligent condition monitoring device with the alarm feature and diagnostic detector.

[0113] Option 15. A method according to Option 13, wherein the method includes configuring the alarm feature and diagnostic detector remotely from the intelligent condition monitoring device.

[0114] Embodiment 16. The method of embodiment 13, wherein the sensed, time-stamped and captured alarm characteristic parameters include one or more of the following:

[0115] Vibration (X, Y, Z axis),

[0116] Equipment temperature,

[0117] Oil level or temperature and %RH,

[0118] Suction or discharge pressure,

[0119] Motor torque, flux or speed,

[0120] flow, or

[0121] Seal health.

[0122] Option 17. A method according to Option 11, wherein the diagnostic detector characteristics include characteristics related to: cavitation alarm conditions, dry running alarm conditions, bearing fault alarm conditions, mechanical misalignment alarm conditions, mechanical looseness alarm conditions, vibration (X, Y, Z axis) alarm conditions, equipment temperature alarm conditions, oil level or temperature and %RH alarm conditions, suction or discharge pressure alarm conditions, motor torque, flux or speed alarm conditions, flow alarm conditions, or seal health alarm conditions.

[0123] Embodiment 18. The method of embodiment 11, wherein each alarm signature and diagnostic detector uses a corresponding subset of the captured alarm signature parameters.

[0124] Embodiment 19. The method of embodiment 1, wherein the method includes configuring the alarm signature and the diagnostic detector to self-learn by receiving labeled or unlabeled alarm signatures to be stored as one or more stored diagnostic detector signatures in a diagnostic detector signature database in a memory.

[0125] Embodiment 20. The method according to embodiment 19, wherein the method comprises configuring the signal processor to:

[0126] comparing the unlabeled alert signature to one or more of the existing diagnostic detector signatures to find the best match,

[0127] marking the unmarked alarm signature as an updated marked alarm signature, and

[0128] The diagnostic detector signature database is updated with the updated flagged alarm signature.

[0129] Scope of the Invention

[0130] It should be understood that any features, characteristics, alternatives or modifications described with respect to a particular embodiment herein may also be applied, used or incorporated with any other embodiment described herein unless otherwise stated herein. Furthermore, the drawings herein are not drawn to scale.

[0131] While the present invention has been described and illustrated with respect to exemplary embodiments thereof, the foregoing and various other additions and omissions may be made therein and thereto without departing from the spirit and scope of the present invention.

Claims

1. A system for performing sensor data analysis for equipment diagnostics, comprising: An alarm feature and diagnostic detector having a signal processor configured to receiving signaling containing information regarding an alarm feature of sensed data with an alarm time stamp for captured alarm feature parameters to monitor rotating equipment and regarding a diagnostic detector feature of a diagnostic detector associated with an alarm condition of the rotating equipment; as well as determining corresponding signaling containing information regarding an alarm diagnostic based on a match between the alarm characteristic and one of the diagnostic detector characteristics contained in the received signaling; as well as an intelligent condition monitoring device positioned relative to the rotating equipment and configured to sense the captured alarm signature parameters, time stamp the sensed captured alarm signature parameters with an alarm, and provide sensed signaling containing information about the sensed, time stamped and captured alarm signature parameters, Therein, each alarm signature and diagnostic detector uses a unique subset of the captured alarm signature parameters.

2. A system according to claim 1, wherein the signal processor is configured to provide the corresponding signaling containing information about the alarm diagnostic for further processing, including shutting down the rotating equipment for repair, or providing an audio or visual alarm warning signal, or scheduling an appropriate maintenance event.

3. The system of claim 1 wherein the intelligent condition monitoring device comprises the alarm feature and a diagnostic detector.

4. The system of claim 1, wherein the sensed, time-stamped, and captured alarm characteristic parameters include one or more of the following: Vibration (X, Y, Z axis), Equipment temperature, Oil level or temperature and %RH, Suction or discharge pressure, Motor torque, flux or speed, flow, or Seal health.

5. The system of claim 1 , wherein the diagnostic detector features include features related to: a cavitation alarm condition, a dry run alarm condition, a bearing fault alarm condition, a mechanical misalignment alarm condition, a mechanical looseness alarm condition, a vibration (X, Y, Z axis) alarm condition, an equipment temperature alarm condition, an oil level, %RH or temperature alarm condition, a suction or discharge pressure alarm condition, a motor torque, flux or speed alarm condition, a flow alarm condition, or a seal health alarm condition.

6. The system of claim 1, wherein the alarm signature and diagnostic detector are configured to self-learn by receiving labeled and unlabeled alarm signatures for storage as one or more stored diagnostic detector signatures in a diagnostic detector signature database in memory.

7. The system of claim 6, wherein the signal processor is configured to: comparing the unlabeled alert signature to one or more of the existing diagnostic detector signatures to find the best match, marking the unmarked alarm signature as an updated marked alarm signature, and The diagnostic detector signature database is updated with the updated flagged alarm signature.

8. The system of claim 1, wherein the alarm features and diagnostic detectors are remotely located from the intelligent condition monitoring device.

9. A method for performing sensor data analysis for equipment diagnostics, comprising: placing an intelligent condition monitoring device relative to the rotating equipment to sense captured alarm signature parameters, time stamping the sensed captured alarm signature parameters with alarms, and providing sensed signaling containing information regarding the sensed, time stamped and captured alarm signature parameters; receiving, with a signal processor in an alarm signature and diagnostic detector, sensed signaling containing information regarding an alarm signature from the intelligent condition monitoring device to monitor sensed data of the rotating equipment and regarding a diagnostic detector signature of a diagnostic detector associated with an alarm condition of the rotating equipment; as well as determining, by the signal processor, a corresponding signaling containing information regarding an alarm diagnosis based on a match between the alarm characteristic and one of the diagnostic detector characteristics contained in the received signaling, Therein, each alarm signature and diagnostic detector uses a unique subset of the captured alarm signature parameters.

10. The method of claim 9, wherein the method includes providing the corresponding signaling containing information about the alarm diagnostic with the signal processor for further processing, including shutting down the rotating equipment for repair, or providing an audio or visual alarm warning signal.

11. The method of claim 9, wherein the method includes configuring the intelligent condition monitoring device with the alarm feature and a diagnostic detector.

12. The method of claim 9, wherein the method includes configuring the alarm feature and diagnostic detector remotely from the intelligent condition monitoring device.

13. The method of claim 9, wherein the sensed, time-stamped, and captured alarm characteristic parameters include one or more of: Vibration (X, Y, Z axis), Equipment temperature, Oil level or temperature and %RH, Suction or discharge pressure, Motor torque, flux or speed, flow, or Seal health.

14. The method of claim 9, wherein the diagnostic detector features include features related to: a cavitation alarm condition, a dry run alarm condition, a bearing fault alarm condition, a mechanical misalignment alarm condition, a mechanical looseness alarm condition, a vibration (X, Y, Z axis) alarm condition, an equipment temperature alarm condition, an oil level or temperature and %RH alarm condition, a suction or discharge pressure alarm condition, a motor torque, flux or speed alarm condition, a flow alarm condition, or a seal health alarm condition.

15. The method of claim 9, wherein the method includes configuring the alarm signature and diagnostic detector to self-learn by receiving labeled and unlabeled alarm signatures for storage as one or more stored diagnostic detector signatures in a diagnostic detector signature database in memory.

16. The method of claim 15, wherein the method comprises configuring the signal processor to: comparing the unlabeled alert signature to one or more of the existing diagnostic detector signatures to find the best match, marking the unmarked alarm signature as an updated marked alarm signature, and The diagnostic detector signature database is updated with the updated flagged alarm signature.

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