FIELD OF THE INVENTION

[001] The invention relates to the field of asset management, and more specifically to condition monitoring of industrial equipment such as rotating machines (e.g. motors, generators etc.).

BACKGROUND OF THE INVENTION

[002] Process information (e.g. failure time, repair time, process uptime etc.) of industrial equipment such as rotating machines, is typically collected either manually or by meta-processing on ERP (Enterprise resource planning) data.

Manual data collection suffers from mistakes and oversights in addition to resource cost which leads to data being available only at a high level (or not at all), while meta-processing on ERP data necessarily requires access from the plant owner which is often cumbersome to acquire.

[003] This information is necessary for efficient inventory management, criticality analysis to find appropriate maintenance solution, maintenance cost optimization and fleet-level reliability studies associated with a plant. All this put together can be useful to optimize the life cycle cost of the fleet (i.e. one or multiple type of industrial equipment spread across a plant).

[004] Manufacturers need this data to gauge product reliability and get accurate inputs for future designs and optimally priced warranty extensions. Due to risk of data inaccuracy and time involved, industries use pre-analyzed reliability data from sources like IEEE, OREDA (Offshore Onshore Reliability Data) etc. Uncertainty prevails if pre-analyzed data of particular set of machines of different makes and operating conditions with different maintenance practices can be applied to another set of machines under different operating conditions and makes. [005] In an industrial environment, obtaining data from a plurality of industrial equipment (e.g. motors spread across a plant) is difficult. This becomes especially true when the data is not being sourced from a plant database system (e.g. ERP / Production / Maintenance database, inventory management system etc.). In such a case where access to the plant database system is not available, the data has to be sourced from alternate sources. For example, data may be collected from a condition monitoring device associated with an industrial equipment (e.g. motor). In such a case, there needs to be correlation between condition assessments performed with measurements at the condition monitoring device, and maintenance activities being performed on the industrial equipment (or components of the industrial equipment). Absent such information, it is difficult to reliably gather process information.

SUMMARY OF THE INVENTION

[006] The invention provides a condition monitoring device and a method for monitoring a rotating machine (e.g. a motor). The method can be performed with a processor of the condition monitoring device, and / or a processor of a server and / or a gateway device in communication with the condition monitoring device. Alternately, the method can be performed with the processor of the condition monitoring device, and the processor of the server and / or the gateway device.

[007] The rotating machine may be one of several rotating machines spread across an industrial environment such as a process plant. The condition monitoring device is associated with the rotating machine (e.g. mounted on a housing / frame). The condition monitoring device comprises one or more sensors and optionally a memory, the processor and a communication unit.

[008] The memory has one or more reference signatures (e.g. signature associated with a monitored parameter of the rotating machine such as vibration, magnetic field, temperature, current etc.). The one or more reference signatures can be stored on a database of a server or a gateway device (in addition to, or in place of storing in the memory of the condition monitoring device). The one or more reference signatures are associated with one or more maintenance activities (e.g. bearing change, rotor repair etc.). Each maintenance activity of the one or more maintenance activities is associated with one of the rotating machine (e.g. servicing of a motor) and a component of the rotating machine (e.g. replacement of a bearing).

[009] The one or more sensors are configured for detecting one or more parameters of the rotating machine (e.g. vibration, temperature, humidity, magnetic field etc.). In an embodiment, the one or more sensors comprises an accelerometer. The accelerometer can be a multi-axial accelerometer which can measure acceleration along two or more axes. In accordance with the embodiment, an extract from a signal received from the accelerometer is compared with a corresponding reference signature of the one or more reference signatures for detecting the maintenance activity. The corresponding reference signature can comprise a plurality of spikes in a time period, wherein the average acceleration value over the time period is greater than a threshold value. For example, in a normal condition, determined from accelerometer data observed over a long period of time (e.g. hours, days or weeks), the average acceleration value over a period of time (e.g. 1 sec) is within a range / threshold. However, in the event of a maintenance activity, there are several spikes in the acceleration value, and the average acceleration value over the period of time is outside the range / threshold.

[0010] In an embodiment, the one or more sensors comprises an accelerometer and a magnetometer. The accelerometer can be a multi-axial accelerometer which can measure acceleration along two or more axes, and the magnetometer can be a multi-axial magnetometer which can measure magnetic field along two or more axes. In such a case, an extract from a signal received from the accelerometer is compared with a first reference signature of the one or more reference signatures, and an extract from a signal received from the magnetometer is compared with a second reference signature of the one or more reference signatures. Here, the comparison of the extract from the magnetometer signal with the second reference signature can be based on the comparison of the extract from the signal received from the accelerometer with the first reference signature, for detecting the maintenance activity.

[0011] The processor processes measurements received from the one or more sensors. This processor can be the processor of the condition monitoring device, or the server / gateway device in communication with the condition monitoring device. Alternately, the processor of the condition monitoring device and the processor of the server and / or the gateway device can process the measurements. Here, the processor receives one or more signals associated with the one or more parameters of the rotating machine from the one or more sensors, and compares an extract from the one or more signals, with the one or more reference signatures associated with the one or more maintenance activities. The processor detects a maintenance activity based on the comparison of the extract with the one or more reference signatures.

[0012] The processor also updates a status of the rotating machine based on the detection. For example, the processor can update data maintained at the condition monitoring device. The status of the rotating machine may be maintained at one of the server and the gateway device. In such a case, the processor of the condition monitoring device may trigger a communication for one of the gateway, and the server to update the status of the rotating machine maintained thereof. Updating the status of the rotating machine can also include generating an alert for a mobile device and a Human Machine Interface (HMI) associated with the condition monitoring device.

[0013] The communication unit of the condition monitoring device enables communication between the condition monitoring device and one or more of the gateway, the server, the mobile device and the HMI. BRIEF DESCRIPTION OF DRAWINGS

[0014] Fig. 1 shows a simplified representation of a system for monitoring a rotating machine, in accordance with an embodiment of the invention.

[0015] Fig. 2 shows a block diagram of a condition monitoring device associated with the rotating machine, in accordance with the invention.

[0016] Figs. 3 and 4 are sample plots of measurements of magnetic field along the one or more axes, versus time.

[0017] Fig. 5 is a sample plot of measurements of acceleration versus time.

[0018] Fig. 6 is a flowchart of a method for monitoring the rotating machine, in accordance with an embodiment of the invention.

DETAIL DESCRIPTION

[0019] The invention provides a condition monitoring device and a method for monitoring a rotating machine (e.g. a motor, a generator, a pump, a shaft line etc.). The condition monitoring device may be a device for non-invasive condition monitoring of the rotating machine. As shown in Fig. 1, the condition monitoring device (120) may be mounted on a housing (or frame) of a rotating machine (110) for monitoring of the rotating machine. The condition monitoring device may have a housing (205, shown in Fig. 2) designed to enable such mounting of the condition monitoring device on the rotating machine. The condition monitoring device may alternately be part of a control unit of the rotating machine. The rotating machine may be one of several (number / type) rotating machines located in a plant (e.g. one of several low voltage motors spread across a plant).

[0020] In accordance with various embodiments, the condition monitoring device has one or more sensors (240, 250), a processor(s) (220), a communication unit (280), and a memory. The memory may be a non-transitory memory module (230) with one or more reference signatures. The one or more reference signatures can be stored on a database of a server or a gateway device (in addition to, or in place of storing in the memory of the condition monitoring device). The one or more reference signatures are associated with one or more maintenance activities. Here, each maintenance activity of the one or more maintenance activities is associated with maintenance of one of the rotating machine (e.g. service of a motor, generator etc.) and a component of the rotating machine (e.g. bearing, rotor etc.).

[0021] The one or more sensors of the condition monitoring device detect one or more parameters of the rotating machine. For example, the condition monitoring device may have sensors for detecting parameters selected from the group of vibration, magnetic field, acoustic, ultrasonic, temperature, pressure, location, and humidity. In accordance with the embodiment of Fig. 2, the condition monitoring device has an accelerometer (250) and a magnetometer (240). It should be apparent that while the condition monitoring device is shown to include only two sensors in Fig. 2, the condition monitoring device can have one or multiple sensors enclosed in one housing. In accordance with various embodiments, the accelerometer measures acceleration along two or more axes, and the magnetometer measures magnetic field along two or more axes. In an embodiment, the one or more sensors comprises an accelerometer. The accelerometer can be a multi-axial accelerometer which can measure acceleration along two or more axes.

[0022] The processor (or processors) receives and processes measurements from the sensors of the condition monitoring device. For instance, one or more signals associated with the one or more parameters of the rotating machine are received at the processor from the one or more sensors. Continuous measurements may be performed by various sensors of the condition monitoring device. Each sensor sends the measured data to the processor. For example, the accelerometer and magnetometer measurements may be sent continuously to the processor. [0023] An extract from the one or more signals, is compared with the one or more reference signatures associated with the one or more maintenance activities. For instance an extract from accelerometer signal is compared with a corresponding reference signature. Similarly an extract from magnetometer signal is compared with a corresponding reference signature. The comparison is performed at the processor of the condition monitoring device. In response to the comparison of the extract with the reference signatures, a maintenance activity is detected at the processor. For example, there may be a change in a parameter associated with performance of a bearing, and such change may be detected based on the comparison of measurements before and after the maintenance activity.

[0024] According to the detection, various actions may be performed. For example, the processor may update data associated with a status of the rotating machine, based on the detection of the maintenance activity. Such status may be maintained at the condition monitoring device and communicated to an external device. Alternately, the status of the rotating machine may be maintained at an external device (e.g. a gateway, or a server). Updating the status may include generating an alert for a mobile device or a Human Machine Interface (HMI) (explained herein below).

[0025] It should be noted that the method can be performed with the processor of the condition monitoring device as described above, or with a processor of a server (130) and / or a gateway device (160) in communication with the condition monitoring device. Alternately, the method can be performed with the processor of the condition monitoring device, and with the processor of the server and / or the gateway device.

[0026] In accordance with some embodiments, a model for condition assessment is updated according to the detection of the maintenance activity. Here, the model refers to a virtual representation of the industrial equipment, created and maintained in a processing device / system to reflect the status of the industrial equipment including its operation, condition (health) and component history.

[0027] In some embodiments, the model is provided at the condition monitoring device, or at one of the gateway and the server in communication with the condition monitoring device. The condition monitoring device may communicate with the server directly, or via the gateway or a mobile device (140). A network interface of the communication unit of the condition monitoring device can be configured for communication with an external device (e.g. the gateway / server). In one embodiment, the network interface is capable of communicating over wireless media such as Bluetooth, Wireless HART, etc. The network interface may communicate data using an antenna (190) as shown in Fig. 2.

[0028] The data / functions associated with the model may be distributed across the condition monitoring device, the gateway and / or server. Also, the model at the condition monitoring device may be updated / adapted including data/function associated with the model according to communication received from the gateway / server.

[0029] There may be certain functions associated with communication of alerts in the model. Such functions when executed on receipt of measurements from the sensors, can generate alerts based on functional configurations as defined in the model. In some embodiments, a communication is sent to one or more of the gateway, the server, a mobile device and a communication device / system linked with the specific industrial equipment in a plant system. For example, in response to detecting a maintenance activity, an alert may be sent to the mobile device of a factory personnel or received at a HMI of the industrial equipment / monitoring station. Such an alert is likely to enable performing all maintenance activities pending for the motor (identified based on measurements received from the condition monitoring device). [0030] In accordance with various embodiments, the virtual representation of the industrial equipment is provided with a reliability model. Here, based on measurements from the sensors (including detection of maintenance activity), the reliability model is updated for effectively tracking condition (e.g. health) of the industrial equipment or component thereof. For example, a bearing may be replaced as a result of maintenance activity, in view of which the reliability model associated with the specific component (bearing) can be updated to estimate condition / life of the bearing and / or the industrial equipment, taking into account the replacement. Here, the bearing related signal received from the sensors will change before and after the maintenance activity. Such information can be correlated with condition assessments (e.g. bearing condition assessment) performed using measurements (from the same sensors) to improve confidence of condition assessment with the model at the condition monitoring device. Also, the model parameters associated with reliability assessment / model can be updated / adapted.

[0031] The following describes an embodiment of the invention, wherein the condition monitoring device comprises an accelerometer and a magnetometer. As shown in Fig. 2, the condition monitoring device (200) comprises an assembly of a tri-axial magnetometer (240) and a tri-axial accelerometer (250) may be arranged along with a processor (220) and memory (230). The condition monitoring device may be installed on the surface of the required machine (e.g. motor) in a predetermined location (e.g. on the body near drive-side bearing).

[0032] In accordance with the embodiment, the processor is configured to wake up and process signals if an accelerometer or a magnetometer signal exceeds a threshold unique to the machine, automatically determined based on the baseline value observed after installation. This is done in order to compensate for the orientation of the installation in relation to the earth's gravity and magnetic field.

[0033] In order to gather data for reliability, the following states can be detected: Machine is running

Machine is under maintenance

Machine is in idle state

[0034] It is possible to calculate failure time, repair time and process uptime by detecting above conditions and the respective time duration.

[0035] In order to detect whether machine is running or in idle state, start or stop of the rotating machine may be detected. An example of motor start detection is shown in Fig. 3. In accordance with the method, measurements along at least one magnetic field direction on motor body, are used for motor start detection. In Fig. 3, magnetic field along one axis (such as x-axis parallel to axis of the rotor) is used for detection in case of motor start (302).

[0036] As shown in the figure, the amplitude of magnetic field increases rapidly when motor starts running. Such signal character is obvious and easy to be detected. In the presented example, the motor start detection method is implemented based on a threshold value. When the amplitude of signal is larger than the given threshold, it is considered that motor started. This functionality can be realized as an embedded functionality of a sensor such as a digital magnetometer sensor.

[0037] In a similar manner, motor stop detection can be performed. Fig. 4 presents example of magnetic field (x-axis) in case of motor stop (402). As shown in the figure, the amplitude of magnetic field decreases rapidly when motor stops running. Same as in the case of motor start, such signal character is obvious and easy to be detected. In the presented example, the motor stop detection method is also implemented based on threshold value. When the amplitude of signal is smaller than the given threshold, it is considered that motor has stopped. This functionality can be realized as an embedded functionality of a sensor such as a digital magnetometer sensor. [0038] Similarly the rotating machine's idle state is simply when it is not running. The machine can become idle because of inherent failure, process failure or duty cycling. It is possible to differentiate between inherent failure and duty cycling by analyzing condition monitoring data. It is also possible to differentiate between inherent failure and process failure from condition monitoring data on downstream equipment such as gearboxes and pumps.

[0039] As for condition two (i.e. machine is under maintenance), major maintenance on a rotating machine may be characterized by the machine being lifted from its foundation. This can be detected by a threshold (e.g. first reference signature) tripping on the accelerometer with no concomitant signature (e.g. second reference signature) on the magnetometer.

[0040] In accordance with the embodiment wherein the condition monitoring device has an accelerometer and a magnetometer, the signature for a running motor in the magnetometer signal is distinctive and can be very reliably judged by the Signal to Noise Ratio (SNR) of the maximum frequency peak in relation to the rest of the spectrum. So when the rotating machine (e.g. motor) is lifted, the accelerometer threshold would trip and wake up the processor.

[0041] The processor can then check the magnetometer signal to check whether the rotating machine has actually started or whether the rotating machine is simply being lifted, dropped, moved or hammered (all of these would have spike characteristics on the vertical, horizontal or axial axes of the accelerometer time domain signal).

[0042] Major maintenance is likely to begin with a lift, then a drop, then movement and so on until the motor begins to run again. All of these lifts, drops and hammerings can be logged on the processor's storage to be later extracted and processed for maintenance information on the motor. The reliability of this information is likely to be quite high since the incidence of spikes will be high and the sensitivity can be tuned in order to create an abundance of logs. These logs can be subsequently filtered offline with algorithms correlating motor starts and motor status to the incidence frequency of spikes.

[0043] It should be noted that signal from one or multiple sensors may be used (e.g. an accelerometer signal) for detection in accordance with the present invention. Example graph of accelerometer data from a motor being lifted using a constant-velocity crane is shown in Fig. 5. The acceleration signal has values of acceleration over time in two axis (502, 504). As can be seen, the initial value of acceleration is stable (506), after which there is a variation in the acceleration value. There can be a plurality of spikes observed in a time period (e.g. 0.5 seconds, 1 second, 3 seconds etc.). In Fig. 5 such spikes are observed after around 2 seconds in the signal. In such a case, the average acceleration value over the time period is greater than a threshold value.

[0044] A reference signature for a maintenance activity may be determined based on a pattern of spikes in the signal. For example, the maintenance activity may be classified by looking at the number and spacing between impacts (spikes) that are observed in the accelerometer signal. For instance, rotor removal from the frame would be characterized by a few impacts while the end shield is being removed followed by further impacts as the rotor is being removed. Rotor reattachment would be characterized by a similar sequence in reverse.

[0045] The following Fig. 6 is a flowchart of the method of monitoring the rotating machine in accordance with an embodiment. The method can be performed with the processor of the condition monitoring device, or the processor of the server and / or the gateway device in communication with the condition monitoring device. Alternately, the method can be performed with the processor of the condition monitoring device, and the processor of the server and / or the gateway device. [0046] The method comprises receiving one or more signals associated with the one or more parameters of the rotating machine from the one or more sensors at 602. In an embodiment, the one or more signals comprises an accelerometer signal, and a magnetometer signal. In another embodiment, the one or more signals is an accelerometer signal. The signal may be monitored continuously / periodically at the processor of the condition monitoring device. The method further comprises comparing an extract from the one or more signals, with the one or more reference signatures associated with the one or more maintenance activities at 604.

[0047] In the embodiment, wherein the one or more sensors comprises the accelerometer and the magnetometer, an extract from a signal received from the accelerometer is compared with a first reference signature of the one or more reference signatures, and an extract from a signal received from the magnetometer is compared with a second reference signature of the one or more reference signatures. Here, the extract from the signal received from the magnetometer may be compared with the second reference signature, based on the comparison of the extract from the signal received from the accelerometer with the first reference signature. In accordance with the embodiment, wherein the sensor is an accelerometer, an extract from a signal received from the accelerometer is compared with a corresponding reference signature of the one or more reference signatures for detecting the maintenance activity. The corresponding reference signature can comprise a plurality of spikes in a time period, wherein the average acceleration value over the time period is greater than a threshold value. For example, in a normal condition, determined from accelerometer data observed over a long period of time (e.g. hours, days or weeks), the average acceleration value over a period of time (e.g. 1 sec) is within a range / threshold. However, in the event of a maintenance activity, there are several spikes in the acceleration value, and the average acceleration value over the period of time is outside the range / threshold. [0048] In addition, the method comprises detecting a maintenance activity based on the comparison of the extract with the one or more reference signatures at 606. The detection may be performed as explained hereinabove. According to the detection, a status of the rotating machine is updated at 608. For example, the processor can update data maintained at the condition monitoring device. The status of the rotating machine may be maintained at one or more of a server and a gateway. In such a case, the processor may trigger a communication for one or more of the gateway, and the server to update the status of the rotating machine maintained at the server / gateway. Updating the status of the rotating machine can also include generating an alert for a mobile device and a Human Machine Interface (HMI) associated with the condition monitoring device.

[0049] In some embodiments, a model for condition assessment may be updated. The model may be at one or more of the condition monitoring device, a gateway and a server. Updating the model may comprise estimating a model parameter associated with a reliability assessment, according to the detection of the maintenance activity. Alternately, an alert may be displayed at one or more of the mobile device and the Human Machine Interface (HMI) associated with the condition monitoring device, based on the detection. The alert may be generated based on a health assessment and the detection of the maintenance activity. Here, the health assessment is performed based on the measurements received from the one or more sensors of the condition monitoring device.

[0050] With the invention, actionable insights on asset data can be made efficiently, as the need of ERP systems as data source is eliminated / minimized. The invention when combined with condition monitoring solution can be useful for fleet analysis on component level and useful for root cause analysis. The data collected on fleet level can give key insights of machine / components installed in a plant. This information can be used in turn by a manufacturer for coming up with better and efficient designs. Other possible benefits based on data analysis would be service contracts and warranty extension.