WO2020183730A1 - Monitoring system, information processing device, and information processing method - Google Patents

Abstract

The present invention provides a monitoring system comprising: a control device that receives sensing data from one or a plurality of sensors provided to a device including a power source, and that calculates one or a plurality of feature amounts from the sensing data; a storage device that associates the feature amounts and the sensing data received from the control device; and an information processing device that monitors the feature amounts, generates audio data or scoring data indicating the operation state of the device on the basis of a vibration waveform included in the sensing data, and outputs the audio data or the scoring data.

Description

Monitoring system, information processing device, and information processing method

The present invention relates to a monitoring system, an information processing device, and an information processing method.

In Patent Document 1, a plurality of vacuum pumps are collectively monitored by using signals from an AE (Acoustic Emission) sensor, a current sensor, and a temperature sensor, and operated on a workstation connected by a LAN, which is peculiar to the vacuum pump. A failure prediction system for a mechanical booster type vacuum pump that uses a failure prediction standard has been proposed. According to the failure prediction system, clogging failure caused by products deposited in the casing of the mechanical booster type vacuum pump is predicted in advance, and replacement of the pump is urged to avoid product defects due to sudden failure of the pump. , Product yield can be improved and pump maintenance cost can be reduced.

Further, in Patent Document 2, data of a specific analysis frequency is extracted from the data output by an accelerometer that measures the vibration of a rotating machine, and the amount of time change of the extracted analysis frequency data is obtained. A lifespan diagnosis system that determines the lifespan by comparing it with a threshold has been proposed. According to the life diagnosis system, it is possible to diagnose the life of a rotating machine with high sensitivity and stability by observing the amount of time change of acceleration due to distortion, damage, etc. of the rotating machine.

Japanese Unexamined Patent Publication No. 2000-64964 Japanese Unexamined Patent Publication No. 2003-232705

Whether or not a failure has actually occurred even when a failure is predicted in advance or the life of the rotating machine is determined using the sensing data measured by each sensor as in Patent Documents 1 and 2. In reality, it is not possible to know whether or not the product has reached the end of its useful life without conducting an overhaul disassembly survey. The skilled technician confirms the overhaul result and recognizes how much time there is for the replacement of parts and the like for the life. Therefore, it is difficult for even a skilled technician to judge a failure or the like only by inspecting the device from the outside. In addition, there is a current problem that the number of skilled technicians has decreased and the experience of skilled technicians has not been handed down, so anyone can judge whether or not a failure actually occurred or whether or not the life has expired. I can't give it down.

Therefore, an object of the technique of the present disclosure is to provide a technique for presenting data that can quantitatively evaluate or judge an abnormality of the device or a sign of the abnormality.

The technology of the present disclosure adopts the following configuration in order to solve the above-mentioned problems.

That is, the monitoring system according to an example of the technique of the present disclosure receives each sensing data from one or a plurality of sensors provided in a device including a power source, and calculates one or a plurality of feature quantities from the respective sensing data. Based on the control device, the storage device that stores each feature amount received from the control device and the sensing data in association with each other, the feature amount is monitored, and the vibration waveform included in the sensing data is included. The device includes an information processing device that generates sound data or scoring data representing an operating state of the device and outputs the sound data or the scoring data.

According to the above configuration, sound data or scoring data based on the vibration waveform is output as necessary while monitoring each feature amount based on each sensing data of each sensor provided in the device including the power source. Therefore, it is possible to provide a technique for presenting data capable of quantitatively evaluating or determining an abnormality of an apparatus or a sign of an abnormality. By presenting objective and easily determinable data such as sound data or scoring data, even non-skilled technicians can determine whether or not a failure has actually occurred or whether or not the product has reached the end of its useful life. It becomes possible to make a more appropriate judgment.

The power source is, for example, a rotating machine, and includes a motor, a vacuum pump, a compressor, a turbine, and the like. Also, the one or more sensors include at least one from various sensors such as vibration sensors, current sensors, temperature sensors, pressure sensors, flow meters, and heat flow sensors. When the sensing data is a vibration waveform, the feature quantity includes, for example, a peak amplitude value, an impact degree, a power spectrum after a fast Fourier transform, and the like. The impact degree can be obtained by integrating, for example, frequency waveform data frequency-converted from vibration waveform data over the entire frequency domain or a predetermined frequency domain. When the sensing data is a current value, temperature, or the like, the feature amount is, for example, an average value or a peak interval.

Further, the device is, for example, a CVD (Chemical Vapor Deposition) device, a labeling device (labeler device), a cutting device, or other devices or devices installed at a production site such as a factory. The control device is, for example, a PLC (programmable logic controller) or a sequencer, and is a device that sequentially controls according to programs such as logical operations, sequence operations, and arithmetic operations. The storage device is, for example, a database capable of storing data and information, and may be configured separately from the information processing device or may be configured inside the information processing device. The information processing device may be, for example, a computer and may have any information processing function.

When the information processing device in the monitoring system according to the above example detects an abnormality of the device based on each feature amount, the sound data of the vibration waveform within a predetermined time based on the time when the abnormality is detected is obtained. May be converted to. According to this configuration, when an abnormality of the device is detected based on the feature amount, it is possible to reproduce sound data based on the vibration at the time of the abnormality, and it is possible to determine the abnormality of the device more appropriately and more easily. Possible data can be presented. As a result, the user (for example, a technician) does not have to actually go to the installation location of the device and check the vibration sound of the device.

The information processing device in the monitoring system according to the above example may convert the vibration waveform of the section specified by the user among the vibration waveforms stored in the storage device into the sound data. According to this configuration, by making it possible to compare the past sound data at the time of normal with the sound data at the time of abnormality, it is possible to present data that can more appropriately and more easily determine the abnormality of the device. can do.

The information processing device in the monitoring system according to the above example is a comparison target with each of the feature quantities, and each threshold value used for abnormality determination may be adjusted based on the normality or abnormality determination result of the user. According to this configuration, when an abnormality is determined by the system, the threshold value used for the abnormality determination can be adjusted to a more appropriate value by feeding back the normality or abnormality determination result by the user. As a result, more appropriate abnormality determination can be performed.

The control device in the monitoring system according to the above example may be capable of adding the calculation of the feature amount according to the abnormality content of the device. According to this configuration, by analyzing the feature amount at the time of abnormality, a new feature amount calculation program can be added to the control device so that a new feature amount according to the abnormality content is calculated. ..

The information processing device in the monitoring system according to the above example may display the scoring data and an appropriate range for the scoring data on the display device. According to this configuration, by displaying the scoring data indicating the abnormality of the device and the appropriate range thereof, even an unskilled user can easily visually determine whether the device is normal or abnormal.

The information processing device in the monitoring system according to the above example may display the comparison result between the scoring data and the appropriate range on the display device. According to this configuration, by displaying the comparison result between the scoring data and the appropriate range thereof, even an unskilled user can more appropriately judge whether the device is normal or abnormal.

Further, the information processing device according to an example of the technique of the present disclosure includes a monitoring unit that monitors each feature amount calculated based on each sensing data from one or a plurality of sensors provided in the device including a power source. It includes a generation unit that generates sound data or scoring data indicating an operating state of the device based on the vibration waveform included in each of the sensing data, and an output unit that outputs the sound data or the scoring data. According to this configuration, it is possible to provide a technique for presenting data capable of more appropriately determining an abnormality or a sign of an apparatus.

Further, the information processing method according to an example of the technique of the present disclosure includes a monitoring step of monitoring each feature amount calculated based on each sensing data from one or a plurality of sensors provided in a device including a power source. Information processing includes a generation step of generating sound data or scoring data indicating an operating state of the device based on the vibration waveform included in each of the sensing data, and an output step of outputting the sound data or the scoring data. The device runs. According to this method, it is possible to provide a technique for presenting data capable of more appropriately determining an abnormality of an apparatus.

According to the technology of the present disclosure, it is possible to provide a technology for presenting data capable of more appropriately determining an abnormality of an apparatus.

FIG. 1 schematically illustrates an example of an application scene of the monitoring system according to the present embodiment. FIG. 2 schematically illustrates an example of the hardware configuration of the control device according to the present embodiment. FIG. 3 schematically illustrates an example of the hardware configuration of the information processing device according to the present embodiment. FIG. 4 schematically illustrates an example of the functional configuration of the control device according to the present embodiment. FIG. 5 schematically illustrates an example of the functional configuration of the information processing apparatus according to the present embodiment. FIG. 6 is a flowchart illustrating an example of the processing procedure of the monitoring system according to the present embodiment. FIG. 7 is a flowchart showing an example of the correction process of the provisional standard according to the present embodiment. FIG. 8 is a schematic view showing an example of the monitoring stem according to the first embodiment. FIG. 9 is a diagram showing an example of a screen including an overview according to the first embodiment. FIG. 10 is a diagram showing time-series changes in the feature amount of the sensing data according to the first embodiment. FIG. 11 is a diagram showing an example of sound reproduction according to the first embodiment. FIG. 12 is a diagram showing an example of a screen for vibration waveform analysis according to the first embodiment. FIG. 13 is a diagram showing an example of a screen displaying monitoring data (feature amount) of the servo motor according to the first embodiment. FIG. 14 is a schematic diagram showing an example of the monitoring system according to the second embodiment. FIG. 15 is a diagram showing an example of a vibration waveform and a feature amount according to the second embodiment. FIG. 16A is a diagram showing an example of a monitor screen during blade contact adjustment according to the second embodiment. FIG. 16B is a diagram showing an example of a monitor screen in which the labeler device according to the second embodiment is in operation. FIG. 17 is a schematic diagram showing an example of the monitoring system according to the third embodiment. FIG. 18 is a diagram showing the relationship between the maximum amplitude of the vibration waveform according to the third embodiment and the processing resistance.

Hereinafter, embodiments relating to one aspect of the disclosed technology (hereinafter, also referred to as “the present embodiment”) will be described with reference to the drawings. However, the present embodiment described below is merely an example of the disclosed technology in all respects. Needless to say, various improvements and modifications can be made without departing from the scope of the disclosed technology. That is, in implementing the disclosed technology, a specific configuration according to the embodiment may be appropriately adopted. The data appearing in the present embodiment are described in natural language, but more specifically, the data is specified in a pseudo language, commands, parameters, machine language, etc. that can be recognized by a computer.

§1 Application example First, an example of a situation in which the disclosed technology is applied will be described with reference to FIG. FIG. 1 schematically illustrates an example of an application scene of the monitoring system 1 according to the present embodiment. The monitoring system 1 according to the present embodiment is a system that monitors the state of the device 10 based on the sensing data acquired from the sensors 20A to C provided in the device 10 installed at the production site such as a factory. The number of sensors is not particularly limited, and at least one is sufficient.

As shown in FIG. 1, the monitoring system 1 is obtained by a device 10 including a power source such as a rotary machine installed in a factory or the like, sensors 20A to C provided in the device 10, and sensors 20A to C. A control device 100 that performs a predetermined calculation on the received sensing data to calculate each feature amount, a storage device 200 that stores each feature amount and each sensing data output from the control device 100 in association with each other, and each feature. It includes an information processing device 300 that monitors the amount or each sensing data. The Area 1 in which the device 10 to be monitored and the control device 100 are installed is, for example, a production site such as a factory or a facility, and the Area 2 in which the storage device 200 and the information processing device 300 are installed can, for example, allow a user to appropriately monitor data. Office etc.

Regarding Area, the example shown in FIG. 1 is an example, and even if the information processing device 300 is provided in Area 1, the storage device 200 is provided in Area 1, or the control device 100 is provided in Area 2. Good.

The information processing device 300 monitors each feature amount or each sensing data, and generates sound data or scoring data indicating the operating state of the device 10 by using at least the vibration waveform included in the sensing data. The sound data indicates the vibration sound of the device 10, and is generated in order to grasp the abnormal sound of the device 10. The scoring data represents the degree of abnormality based on the vibration of the device 10 as scoring data, and is generated so that anyone can grasp the abnormality of the device using an objective index.

For example, the sound data is sound data based on the displayed vibration waveform when the user presses a predetermined button (for example, a sound reproduction button) from the screen D10 displaying a graph showing the vibration waveform which is one of the sensing data. A10 is reproduced. As a result, the user can visually grasp the vibration waveform, and can also aurally grasp the vibration sound that has been conventionally used for determining the abnormality of the device 10. The vibration sound is generated by sound conversion from the vibration waveform.

For example, the scoring data is displayed in real time on the monitor screen D12, and the user can determine whether or not the current scoring data value is appropriate by looking at the monitor screen D12. Further, on the monitor screen D12, the judgment criteria of the scoring data, for example, 50 or more is appropriate, 40 or more and less than 50 is a forecast, and less than 40 is an abnormality, so that the user can change the value of the current scoring data. Based on this, the state of the device 10 can be easily grasped. Real-time means that the display ends within a predetermined time after the sensing data is acquired. In addition, the forecast indicates a state that is not a failure but requires attention.

The control device 100 is configured to calculate each feature amount that appropriately indicates the state of the device 10 based on each sensing data so that an abnormality of the device 10 can be predicted. As a result, the information processing device 300 can predict the abnormality of the device 10 by monitoring each feature amount and each sensing data. Further, the information processing device 300 is configured to generate and output confirmation data including sound data or scoring data for confirming an abnormality of the device 10. With this configuration, it is possible to present confirmation data capable of appropriately determining the abnormality of the device 10, so that unnecessary stoppage of the device 10 can be reduced and stable operation can be realized. Further, the user can confirm the sound data or the scoring data based on the vibration waveform indicating the state of the device 10 and appropriately determine the state of the device 10. Further, when an abnormality of the device 10 is detected based on a feature amount or the like, the user does not have to bother to go to the installation position of the device 10, which can reduce the time and effort of the user.

§2 Configuration example [Hardware configuration]
<Control device>
Next, an example of the hardware configuration of the control device 100 and the information processing device 300 according to the present embodiment will be described with reference to FIGS. 2 and 3. FIG. 2 schematically illustrates an example of the hardware configuration of the control device 100 according to the present embodiment.

With reference to FIG. 2, the control device 100 includes a processor 102 such as a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit), a chipset 104, a main storage device 106, a secondary storage device 108, and the like. It includes a network controller 110, a memory card interface 114, an internal bus controller 122, and an I / O unit 124.

The secondary storage device 108 is composed of, for example, a non-volatile storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The main storage device 106 is composed of a volatile storage device such as a DRAM (Dynamic Random Access Memory) or a SRAM (Static Random Access Memory).

The processor 102 reads various programs stored in the secondary storage device 108, expands them in the main storage device 106, and executes them to perform control according to the target of the device 10 and various processes as described later. Realize. For example, the receiving unit 152, the processing unit 154, the transmitting unit 156, and the like, which will be described later, can be realized as a program that is temporarily stored in the main storage device 106 and then operates mainly on the processor 102. That is, when the processor 102 interprets and executes the program temporarily stored in the main storage device 106, the functions of the receiving unit 152, the processing unit 154, and the transmitting unit 156 are realized.

The chipset 104 realizes the processing of the control device 100 as a whole by controlling the processor 102 and each component.

The secondary storage device 108 stores various programs such as user programs executed by the processor 102 and an internal database.

The network controller 110 controls the exchange of data with other devices via the network. The network controller 110 is typically realized by using a dedicated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array).

The memory card interface 114 is configured so that the memory card can be attached and detached, and it is possible to write data to the memory card and read various data (user program, trace data, etc.) from the memory card. The control device 100 may have a USB (Universal Serial Bus) controller, and the USB controller controls the exchange of data with the control device 100 via a USB connection. The USB controller is typically realized using a dedicated circuit such as an ASIC or FPGA.

The internal bus controller 122 is an interface for exchanging data with the I / O unit 124 mounted on the control device 100. The internal bus controller 122 is typically implemented using a dedicated circuit such as an ASIC or FPGA.

The various programs executed by the control device 100 of FIG. 2 may be installed via a recording medium such as a computer-readable memory card, but the secondary storage device 108 is downloaded from a server device or the like on the network. You may install it in. Further, the function provided by the control device 100 according to the present embodiment may be realized by using a part of the module provided by the OS (Operating System).

Further, in FIG. 2, a configuration example in which the necessary functions are provided by the processor 102 executing the above program is shown, but some or all of these provided functions are provided by a dedicated hardware circuit ( For example, it may be implemented using ASIC or FPGA). Alternatively, the main part of the control device 100 may be realized by using hardware that follows a general-purpose architecture (for example, an industrial personal computer based on a general-purpose personal computer). In this case, virtualization technology may be used to execute a plurality of OSs having different uses in parallel, and to execute necessary applications on each OS.

<Information processing device>
FIG. 3 schematically illustrates an example of the hardware configuration of the information processing apparatus 300 according to the present embodiment. As shown in FIG. 3, the information processing device 300 includes a processor 302, a memory 304, a storage device 306, an input I / F unit 308, a data I / F unit 310, a communication I / F unit 312, and a display device 314. ..

The processor 302 controls various processes in the information processing device 300 by executing a program stored in the memory 304. For example, the receiving unit 352, the monitoring unit 354, the generating unit 356, the output unit 358, and the like, which will be described later, can be realized as a program that is temporarily stored in the memory 304 and mainly operates on the processor 302. That is, when the processor 302 interprets and executes the program temporarily stored in the memory 304, the functions of the receiving unit 352, the monitoring unit 354, the generating unit 356, and the output unit 358 are realized.

The memory 304 is a storage medium such as a RAM (Random Access Memory). The memory 304 temporarily stores the program code of the program executed by the processor 302 and the data required when the program is executed.

The storage device 306 is a non-volatile storage medium such as a hard disk drive (HDD) or a flash memory. The storage device 306 stores an operating system and various programs for realizing each of the above configurations. In addition, the storage device 306 can also store data used for determining the state of the device 10. Such programs and data are referred to by the processor 302 by being loaded into the memory 304 as needed.

The input I / F unit 308 is a device for receiving input from the user. Specific examples of the input I / F unit 308 include a keyboard, a mouse, a touch panel, various sensors, a wearable device, and the like. The input I / F unit 308 may be connected to the information processing device 300 via an interface such as USB.

The data I / F unit 310 is a device for inputting data from the outside of the information processing device 300. Specific examples of the data I / F unit 310 include a drive device for reading data stored in various storage media. It is also conceivable that the data I / F unit 310 is provided outside the information processing apparatus 300. In that case, the data I / F unit 310 is connected to the information processing device 300 via an interface such as USB.

The communication I / F unit 312 is a device for performing data communication via the Internet with an external device of the information processing device 300 by wire or wirelessly. It is also conceivable that the communication I / F unit 312 is provided outside the information processing device 300. In that case, the communication I / F unit 312 is connected to the information processing device 300 via an interface such as USB.

The display device 314 is a device for displaying various information. Specific examples of the display device 314 include a liquid crystal display, an organic EL (Electro-Luminescence) display, a display of a wearable device, and the like. It may be provided outside the display device 314 and the information processing device 300. In that case, the display device 314 is connected to the information processing device 300 via, for example, a display cable or the like.

Here, the storage medium may be a semiconductor memory such as a flash memory in addition to a disc-type storage medium such as a CD or DVD.

Regarding the specific hardware configuration of the control device 100 and the information processing device 300, it is possible to omit, replace, or add components as appropriate according to the embodiment. For example, the control device 100 and the information processing device 300 may include a plurality of processors. Further, the information processing device 300 may be composed of a plurality of information processing devices. Further, as the information processing device 300, a general-purpose desktop PC (Personal Computer), a tablet PC, or the like may be used in addition to the information processing device designed exclusively for the provided service.

[Functional configuration]
<Control device>
Next, an example of the functional configuration of the control device 100 and the information processing device 300 according to the present embodiment will be described with reference to FIGS. 4 and 5. FIG. 4 schematically illustrates an example of the functional configuration of the control device 100 according to the present embodiment.

The control device 100 shown in FIG. 4 includes a receiving unit 152 that receives each sensing data provided in the device 10, a processing unit 154 that calculates a predetermined feature amount based on the sensing data, each sensing data, and each feature amount. 156 is a transmission unit that transmits the data to the storage device 200.

The function of the receiving unit 152 is realized by, for example, the processor 102, and various data are acquired from the network controller 110, the internal bus controller 122, and the like. For example, the receiving unit 152 acquires the sensing data measured by the sensors 20A to C. The sensing data is, for example, data showing a vibration waveform, a current, a temperature, a pressure, a heat flow, and the like.

The processing unit 154 realizes the function by, for example, the processor 102, and processes so as to convert it into a predetermined feature amount based on each sensing data received by the receiving unit 152. When the sensing data is a vibration waveform, the processing unit 154 calculates a peak amplitude value, an impact degree, a power spectrum after a fast Fourier transform (FFT), and the like as feature quantities. Further, when the sensing data is a current value or temperature, the processing unit 154 calculates an average value, a peak interval, or the like as a feature amount.

Further, it is assumed that when an abnormality is detected in the device 10, each sensing data and / or each feature amount is analyzed, and a new feature amount that makes it easy to detect the abnormality is found. For example, the frequency band of the calculated feature amount is changed. In this case, the processing unit 154 can add a program for calculating a new feature amount, and by executing the added program, the new feature amount is calculated from the predetermined sensing data. For example, when the control device 100 is a PLC, a new feature amount calculation program can be added to the control device as a function block.

As a result, a new feature amount calculation program can be added to the control device 100 so that a new feature amount corresponding to the abnormality content is calculated by analyzing the feature amount at the time of abnormality. As a result, a new feature amount suitable for detecting an abnormality is used, so that the abnormality determination can be made more appropriate.

The function of the transmission unit 156 is realized by, for example, the processor 102, and each sensing data acquired from the processing unit 154 and each feature amount are transmitted to the storage device 200 or the information processing device 300 via the network controller 110. The transmission unit 156 may transmit each sensing data used for calculating each feature amount in association with each feature amount. For example, it is possible to associate both data by associating the measurement time with each of the feature amount and the sensing data and transmitting them in a time series.

FIG. 5 schematically illustrates an example of the functional configuration of the information processing device 300 according to the present embodiment. The information processing device 300 shown in FIG. 5 includes a receiving unit 352 that receives sensing data or a feature amount from the storage device 200, a monitoring unit 354 that monitors the state of the device 10 based on the feature amount and / or the sensing data, and the device 10. It has a generation unit 356 that generates confirmation data that can objectively confirm the state of the above, and an output unit 358 that outputs confirmation data. The confirmation data includes at least one of sound data converted from the vibration waveform and scoring data calculated based on the feature amount.

The function of the receiving unit 352 is realized by, for example, the processor 302, and the feature amount and / or sensing data is acquired from the storage device 200 via the communication I / F unit 312 or the like. The feature quantity and / or sensing data may be acquired in real time or at regular timings regardless of the timing of acquisition.

The monitoring unit 354 monitors the feature amount and / or the sensing data acquired by the receiving unit 352, for example, the function is realized by the processor 302. For example, when a provisional reference threshold value is set for each feature amount, the monitoring unit 354 determines whether or not an abnormality has occurred in the device 10 based on the relationship between the feature amount and the threshold value. When the monitoring unit 354 determines that an abnormality has occurred, the monitoring unit 354 outputs an abnormality alarm to the user. The abnormality alarm is, for example, a voice indicating that it is abnormal, or is highlighted and output on a monitor. The output method may be any method, for example, it is possible to send to the registered user's e-mail address, output voice from the speaker, or emit a predetermined light.

The generation unit 356 realizes its function by, for example, the processor 302, and generates confirmation data including sound data or scoring data indicating the operating state of the device 10 based on the vibration waveform included in the sensing data. The sound data indicates the vibration sound of the device 10, and the scoring data is data that can be calculated by the vibration of the device 10 based on the vibration waveform. Further, the scoring data may be calculated from each feature amount (amplitude, power spectrum, inter-peak distance, etc.) of the vibration waveform by using a predetermined calculation algorithm, for example. Further, the scoring data may be calculated by using the feature amounts of other sensing data (current, temperature, etc.) according to the characteristics of the device 10 instead of the vibration waveform.

For example, the output unit 358 outputs sound data from a speaker provided in the information processing device 300, or outputs scoring data to the display device 314. As a result, the user can determine the abnormality of the device 10 by listening to the sound data and viewing the scoring data. In addition, by outputting objective confirmation data, it is possible to prevent unnecessary device stoppages and realize stable device operation.

Further, when an abnormality of the device 10 is detected based on each feature amount, the monitoring unit 354 may convert the vibration waveform within a predetermined time based on the time when the abnormality is detected into sound data. For example, the monitoring unit 354 may convert the vibration waveform within a predetermined time including the time when the abnormality is detected, or within the predetermined time immediately before or after the time when the abnormality is detected, into sound data.

As a result, when an abnormality is detected in the monitoring system 1, the user can check the sound data and scoring data of the vibration waveform based on the time when the abnormality is detected without going to the site. Further, since the sound data is not generated but the vibration waveform in the required section is converted into the sound data as needed, the processing load of the processor 302 can be reduced.

Further, the monitoring unit 354 may convert the vibration waveform of the section designated by the user among the vibration waveforms stored in the storage device 200 into sound data. For example, the monitoring unit 354 may display the past vibration waveform on the display device 314 and convert the vibration waveform in the section designated by the user into sound data.

This makes it possible to compare the past sound data at the time of normal with the sound data at the time of abnormality, so that the monitoring system 1 can more appropriately and more easily determine the abnormality of the device. Can be presented. As a result, the user can easily determine the abnormality of the device 10.

Further, the monitoring unit 354 is a comparison target with each feature amount, and each threshold value used for the abnormality determination may be adjusted based on the normality or abnormality determination result of the user. For example, the monitoring unit 354 adjusts the current threshold value so that it is difficult to determine an abnormality when the user gives feedback (input) that the abnormality is not abnormal when the abnormality determination is made based on the feature amount. .. Further, the monitoring unit 354 may or may not adjust the current threshold value so that it can be easily determined as abnormal when the user gives feedback that the abnormality has occurred. Regarding the adjustment, the monitoring unit 354 adds or subtracts a predetermined value from the threshold value based on the feedback result.

As a result, when an abnormality is determined by the system, the threshold value used for the abnormality determination can be adjusted to a more appropriate value by feeding back the normal or abnormal determination result by the user to the system. As a result, the monitoring system 1 can make an abnormality determination more appropriately.

Further, the output unit 358 may display the generated scoring data and an appropriate range for the scoring data on the display device 314. For example, when the scoring data is normalized to a value of 0 to 100 and calculated, the output unit 358 is analyzed together with the output of the scoring data if the appropriate range of the values of the scoring data is analyzed. The appropriate range (for example, 50 or more shown in D12 of FIG. 1) may be output.

As a result, by displaying the scoring data indicating the abnormality of the device and the appropriate range on the same screen or a screen that can be switched by a predetermined operation, even an unskilled user can visually check whether the device is normal or abnormal. Can be easily determined.

Note that the output unit 358 may output an appropriate range that differs depending on whether the device is operating or the device is being set up. During setup includes, for example, stopping the device for maintenance and manually operating certain parts. As a result, an appropriate range can be displayed in each operation.

§3 Operation example [Monitoring system 1]
Next, an operation example of the monitoring system 1 will be described with reference to FIG. FIG. 6 is a flowchart illustrating an example of the processing procedure of the monitoring system 1 according to the present embodiment. The processing procedure described below is only an example, and each processing may be changed as much as possible. Further, with respect to the processing procedure described below, steps can be omitted, replaced, and added as appropriate according to the embodiment.

(Step S102)
In step S102, the user activates the target device 10 installed at the production site and operates the device 10. Each feature amount is calculated from each sensing data during a period (for example, several days) in which the device 10 normally operates. The user sets a threshold value for each feature amount and sets a tentative reference by statistically analyzing the variation of the feature amount data. By setting a threshold value calculation algorithm in the monitoring unit 354, the standard deviation and variance of the data of each feature amount are obtained, and the threshold value determined to be abnormal is automatically set from these statistical data. You may.

(Step S104)
In step S104, the monitoring unit 354 generates time-series data of the feature amount (hereinafter, also referred to as “trend data”), and the generation unit 356 generates sound data and scoring data. The user analyzes whether the provisional standard is appropriate by viewing trend data, playing sound data, and checking scoring data, and gives feedback to the monitoring system 1. For example, when the monitoring system 1 determines that the abnormality is present, the information processing apparatus 300 is made to input the data determined to be abnormal and the confirmation result of the user for the threshold value. The monitoring unit 354 corrects each temporarily set threshold value based on the input confirmation result. An appropriate threshold value is set by repeating the correction of the threshold value. The specific processing content in step S104 will be described later with reference to FIG. 7.

(Step S106)
In step S106, when a failure occurs in the device 10 or when the device 10 has reached the end of its life, the user identifies the failure location and the failure content of the device 10 by overhaul or the like. The user analyzes each sensing data and each feature amount around the time when a failure or the like occurs, extracts an abnormal waveform, a feature component, and the like, and analyzes the time when the sign occurs.

(Step S108)
In step S108, the user reflects the analysis result on the monitoring unit 354, so that the monitoring system 1 can appropriately detect this abnormality from the next time onward. For example, the user specifies a frequency to be monitored, adds a calculation program to the control device 100 so as to calculate this frequency as a feature amount, or corrects a threshold value in the monitoring unit 354. As a result, when a similar abnormality occurs in the device 10 in the future, the monitoring system 1 can detect this abnormality at an appropriate time. It is preferable that feedback is appropriately provided by executing the process of step S104 after the process of step S108.

According to the monitoring system 1, since the data at the time of abnormality of the device 10 is stored in the storage device 200, the data can be analyzed. Further, based on the analysis result, feedback is given to the monitoring system 1 to specify the data to be monitored and the feature amount, and to change the threshold value. As a result, it is possible to construct an appropriate predictive monitoring system 1 by appropriately feeding back the analysis result at the time of abnormality.

FIG. 7 is a flowchart showing an example of the correction process of the provisional standard according to the present embodiment. In the example shown in FIG. 7, the feature amount based on the sensing data is monitored according to the provisional standard, and the confirmation data is output as appropriate. By grasping this confirmation data, the user can modify the provisional standard as necessary.

(Step S202)
In step S202, the receiving unit 352 acquires each sensing data and each feature amount calculated by the control device 100 and stored in the storage device 200. The receiving unit 352 may acquire both data from the control device 100 and then store the data in the storage device 200.

(Step S204)
In step S204, the monitoring unit 354 monitors the acquired feature amount and sensing data. For example, the monitoring unit 354 may display the acquired feature amount and sensing data on the display device 314 as trend data. This enables the user to monitor sensing data and features in real time.

(Step S206)
In step S206, the monitoring unit 354 determines whether or not the feature amount and the sensing data are abnormal based on the threshold value included in the set provisional reference. For example, the monitoring unit 354 determines that an abnormality occurs when the feature amount or the sensing data exceeds the threshold value or falls below the threshold value.

(Step S208)
In step S208, the generation unit 356 confirms that among the acquired sensing data, the generation unit 356 includes sound data or scoring data indicating the operating state of the device 10 based on the vibration waveform indicating the sensing data measured by the vibration sensor. Generate data.

(Step S210)
In step S210, the output unit 358 outputs the generated confirmation data. For example, the output unit 358 outputs the sound data from the speaker when the confirmation data includes the sound data. Further, when the confirmation data includes the scoring data, the output unit 358 displays the scoring data on the display device 314. The output unit 358 may switch between the output of sound data and the output of scoring data based on the user's operation. As a result, the user can determine whether or not the abnormality of the device 10 has actually occurred by checking the confirmation data, and can correct the provisional reference based on the determination result.

§4 Example Next, an embodiment of the present embodiment will be described. Hereinafter, a monitoring system when a CVD device, a labeler device, and a cutting device are applied as the target device 10 will be described.

[Example 1]
FIG. 8 is a schematic diagram showing an example of the monitoring system 2 according to the first embodiment. The monitoring system 2 shown in FIG. 8 includes devices 10A to E including a CVD device, vibration sensors (vibrometers) 20A-1 to 5, clamp ammeters 20C-1 to 5, IO slave 50, and a waveform measurement unit. It includes 60, a control device 100, a storage device 200, and an information processing device 300.

Further, the sensors 20A-1 to 5 indicate a vibration sensor (vibrometer), and the sensors 20C-1 to 5 indicate a clamp ammeter. In addition, a temperature sensor, a heat flow sensor, and the like may be provided in the devices 10A to E. Each sensor may be provided at an appropriate position on the device 10.

The IO slave 50 acquires data from, for example, an analog sensor provided in the device 10, for example, an ammeter 20C-1 to 5, a thermometer, a heat flow meter, and a pressure gauge, converts the analog data into digital data, and controls the device. Send to 100. Further, the waveform measurement unit 60 transmits each data acquired from the vibration sensors 20A-1 to 20 to the control device 100. Other devices have the same functions as the devices with the same reference numerals as described above.

In the case where the product gradually accumulates in the vacuum pump included in the CVD device as in the first embodiment, the sensing data changes even when the life of the vacuum pump is long. Therefore, the monitoring system 2 detects the sensing data and the amount of change in the feature amount, and seeks the judgment of a skilled user (expert), so that the expert determines whether or not the vacuum pump has reached the end of its life.

Conventionally, an expert diagnoses a failure or the like of a target device 10 by using an auscultation rod at the site, but in the monitoring system 2, the vibration sound of the device 10 can be heard as in the conventional case. In addition, it has a function of converting a vibration waveform into sound data and reproducing it.

For example, the user can listen to the sound of the device 10 at that time by moving the cursor to a predetermined position of the vibration waveform included in the trend data displayed by the output unit 358 and pressing the sound reproduction button.

In addition, the inventors provided vibrometers on the booster pump and the main pump in the device 10 and analyzed the sensing data measured from each vibrometer. As a result, it was confirmed that the abnormalities of the pumps of the main pump and booster pump can be grasped by vibration, the characteristics of waveform and frequency can be grasped, and the features can be quantified. In addition, the inventors specify an appropriate measurement position from a plurality of sensor position candidates selected in advance.

In addition, the monitoring system 2 not only measures and judges the pump alone, but also provides a mechanism for grasping the entire system and comprehensively judging the abnormality from each sensing data. For example, in the monitoring system 2, the algorithm for determining an abnormality is reviewed based on the analysis result after an actual failure or overhaul so that an abnormality can be detected for each abnormality element. The monitoring unit 354 of the information processing device 300 obtains data indicating whether the calculated feature amount is abnormal or normal, and the output unit 358 determines a plurality of abnormalities so that the state of the device 10 can be grasped at a glance. An overview summarizing the results may be displayed on the display device 314.

FIG. 9 is a diagram showing an example of the screen D20 including the overview according to the first embodiment. On the screen D20 shown in FIG. 9, whether or not it is normal is displayed for each measurement point of each sensor. For example, in the vibration sensor, the abnormality is detected at the measurement point # 1, and the forecast indicating that the abnormality is likely to occur is shown at the measurement point # 2. By looking at this overview screen, the user can easily grasp where and based on which data the abnormality is detected.

In addition, the user can confirm the time-series change of the data by pressing the area showing the determination result by the monitoring system 2. For example, when the user presses the area of the measurement point # 1 of the vibration sensor, the user can confirm the feature amount calculated from the sensing data measured at the measurement point # 1. For example, from the vibration sensor, a total of 35 types of feature quantities may be calculated from the time domain and the frequency domain (FFT). Further, the servo driver may calculate the feature amount calculated from the torque waveform and the speed waveform, the encoder temperature, and the motor load factor.

FIG. 10 is a diagram showing time-series changes in the feature amount of the sensing data according to the first embodiment. On the screen D22 shown in FIG. 10, a feature amount calculated from the vibration waveform of the vibration sensor is displayed, and a threshold value set for the feature amount is also displayed. As shown in FIG. 10, a plurality of threshold values, for example, an alarm upper limit value, a forecast upper limit value, a forecast lower limit value, and an alarm lower limit value may be set for one feature amount. In addition, these threshold values may be modified based on the feedback result after the user's actual abnormality judgment.

Further, the screen D22 shown in FIG. 10 includes a button B10 for displaying waveform analysis, a button for displaying an image, a button B12 for reproducing sound, and a button for rearranging graphs.

FIG. 11 is a diagram showing an example of sound reproduction according to the first embodiment. In FIG. 11, when the button B12 shown on the screen D22 is pressed by the user, the generation unit 356 converts the vibration waveform into sound data, and the output unit 358 outputs the sound data from the speaker. As a result, the user can easily confirm the sound of the portion determined to be abnormal.

FIG. 12 is a diagram showing an example of the screen D24 of the vibration waveform analysis according to the first embodiment. In FIG. 12, when the button B10 shown on the screen D22 is pressed by the user, the monitoring unit 354 acquires a vibration waveform (eg, sensing data), and the output unit 358 displays the vibration waveform on the display device 314. , Each calculated feature amount, for example, a power spectrum or the like is displayed.

FIG. 13 is a diagram showing an example of the screen D26 for displaying the monitoring data (feature amount) of the servo motor according to the first embodiment. In the example shown in FIG. 13, peak torque, motor temperature, and motor load factor are calculated as feature quantities as monitoring data. In addition, a plurality of threshold values are set for each feature amount as described above. Based on the analysis shown above, the inventors analyzed the following problems.

(Booster pump)
Regarding the detection of abnormal products in the booster pump, the pump that has reached half the life of the booster pump immediately after overhaul has a higher feature value due to the vibration waveform, and the pump that has reached the end of its life has a higher result. Has been confirmed. In particular, the pump that has reached the end of its life has a discontinuous shock damping waveform in the high frequency region, and can be clearly detected as an abnormality. Regarding the effective measurement position of each sensor, when the measurement result of each sensor is analyzed, a better result can be obtained by providing the vibration sensor on the motor side.

(Main pump)
Regarding the detection of abnormal products in the main pump, the value of the feature amount due to the vibration waveform is the highest in 1/2 life compared to the main pump, and it can be generally measured as an abnormal state. However, in a pump that has reached the end of its life, the vibration waveform, FFT, and feature value are small immediately after the overhaul, and it is difficult to distinguish by the magnitude of the vibration waveform. However, the life-long pump has a waveform in which normal rotational vibration is not generated even when compared with that immediately after the overhaul. For example, it is a vibration waveform in which the original vibration energy is lost. Therefore, it is possible to discriminate by the rule that the feature amount is small immediately after the overhaul.

As described above, according to the first embodiment, the overhaul timing can be determined at an appropriate timing by appropriately grasping the deteriorated state of the vacuum pump. In addition, by generating confirmation data and outputting it to the user, it is possible to visualize the deterioration state of the pump. As a result, maintenance costs can be reduced, pump replacement intervals can be lengthened, equipment can be prevented from sudden downfall, and at least one attempt is made to eliminate scrap generation. be able to.

[Example 2]
FIG. 14 is a schematic diagram showing an example of the monitoring system 3 according to the second embodiment. The monitoring system 3 shown in FIG. 14 includes a device 10F including a rotary cutter 12A and a cutter die 12B, a vibration sensor (vibrometer) 20A-1, a waveform measurement unit 60, a hub 70, a control device 100, and a storage device 200. And an information processing device 300 (not shown). In addition, although not shown, various sensors such as a temperature sensor and a servomotor may be provided as in the first embodiment. Further, the information processing device 300 may display the overview screen D30.

In the example shown in FIG. 14, conventionally, in the labeler device 10 such as a PET bottle, there was no clear index for measuring the degree of blade contact of the rotary cutter 12A. In addition, the conventional system has the following problems.
-The degree of blade contact is adjusted by a skilled worker.
・ Because the work relies on the operator's feeling, it takes time to adjust the degree of wing contact.
・ It takes time for newcomers to adjust this blade contact.
・ Adjustments are frequent due to blade wear and cutting board dents.

Further, there is a problem that the production line is frequently stopped due to the change in the degree of blade contact of the rotary cutter 12A, and the stop time is long. For example, the following specific problems can be mentioned.
・ Due to wear of the blade and dent of the cutting board, the label L cannot be cut and the line often stops.
・ The line stop time for adjusting the blade contact is long.
・ To adjust the blade contact, it is necessary to lift and lower the cutter unit and replace it in advance.
・ Even if the unit is replaced, it will stop immediately if the blade contact adjustment is not appropriate.

In response to the above problem, in the monitoring system 3 in the second embodiment, the impact (vibration) generated when the label L is cut is monitored by the vibration sensor 20A-1 to capture the change in the degree of blade contact of the cutter 12A. ..

FIG. 15 is a diagram showing an example of the vibration waveform and the feature amount according to the second embodiment. The data shown in FIG. 15 is the data measured by the vibration sensor 20A-1 provided near the cutter die 12B. FIG. 15A shows the data when the blade contact is insufficient, FIG. 15B shows the data when the blade contact is appropriate, and FIG. 15C shows the data when the blade rise is excessive.

The vibration waveforms shown in FIGS. 15A to 15C show the data of the sensed vibration waveform, the vibration waveform enlargement (80 msec) shows the data in which the vibration waveform is enlarged so that the characteristics can be easily shown, and the FFT (1Flame) is. The feature quantity after the fast Fourier transform is shown.

As shown in FIG. 15A, when the blade contact is insufficient, the amplitude of the vibration waveform is relatively small, and the spectrum after FFT is also small. On the other hand, as shown in FIG. 15C, when the blade hits too much, the amplitude of the vibration waveform is relatively large, and the spectrum after FFT is also large. On the other hand, as shown in FIG. 15B, when the blade contact is appropriate, the amplitude of the vibration waveform is medium and the spectrum is also medium. Therefore, in Example 2, the degree of blade contact can be obtained by using the amplitude of the vibration waveform or the magnitude of the spectrum.

For example, when the processing unit 154 of the control device 100 acquires the sensing data acquired from the vibration sensor 20A-1, FFT processing is executed and the spectrum data is calculated as a feature amount. The transmission unit 156 of the control device 100 stores the spectrum data and the vibration waveform in the storage device 200 or transmits them to the information processing device 300.

When the monitoring unit 354 of the information processing device 300 acquires the spectrum data, the degree of blade contact can be obtained by comparing the plurality of set threshold values with the spectrum data. The generation unit 356 of the information processing device 300 generates scoring data as a value of 0 to 100, for example, by normalizing the degree of blade contact, and the output unit 358 outputs the scoring data to the display device 314. The degree of blade contact may be determined using the amplitude of the vibration waveform.

Note that the generation unit 356 may generate sound data from the vibration waveform data, and the output unit 358 reproduces the sound data when the user accepts the sound reproduction operation. As a result, the user can confirm the vibration sound of the labeler device 10F.

FIG. 16A shows an example of the monitor screen D32 during blade contact adjustment according to the second embodiment, and FIG. 16B shows an example of the monitor screen D34 in which the labeler device 10F is operating. The screen D32 shown in FIG. 16A is a screen displayed while the labeler device 10F is stopped and the blade contact is being adjusted by the user. Here, the scoring data is calculated using the sensing data from the vibration sensor 20A-1 being adjusted. In the example shown in FIG. 16A, the appropriate range is 40 to 60, and the current scoring data is 75, so the monitoring system 3 determines that it is an over-hit.

If the scoring data is 40 or more and less than 60, it is judged to be appropriate, and if the scoring data is less than 40, it is judged to be insufficient. Since the user can adjust the blade contact while looking at the monitor screen D32, skill is not necessarily required, and the blade contact can be easily adjusted to an appropriate place.

The screen D34 shown in FIG. 16B is a screen in which the labeler device 10F is in operation and scoring data indicating the degree of blade contact during operation is displayed. Here, the scoring data is calculated using the sensing data from the vibration sensor 20A-1 in which the labeler device 10F is in operation. In the example shown in FIG. 16B, since the appropriate range is 50 or more and the current scoring data is 48, the monitoring system 3 determines that the forecast level is the stage before the abnormality.

If the scoring data is less than 40, it is determined that the blade contact is insufficient, and the user stops the labeler device 10F and adjusts the blade contact. As a result, the user can grasp at what timing the labeler device 10F should be stopped and the blade contact should be adjusted by checking the scoring data during operation. Moreover, since the appropriate range is displayed on the monitor screen, anyone can objectively judge the degree of blade contact.

Note that, in FIGS. 16A and 16B, the appropriate range for the scoring data may be changed depending on whether or not the labeler device 10F is in operation. This is because the degree of vibration when manually adjusting the blade contact while the labeler device 10F is stopped is different from the degree of vibration due to the blade contact during operation of the labeler device 10F.

[Example 3]
FIG. 17 is a schematic diagram showing an example of the monitoring system 4 according to the third embodiment. The monitoring system 4 shown in FIG. 17 includes a device 10G for cutting metal, a vibration sensor (not shown), a waveform measurement unit 60, a control device 100, an information processing device 300 including a storage device 200, and a display device 400. And. In addition, although not shown, various sensors such as a temperature sensor and a servomotor may be provided as in the first embodiment. The display device 400 is a monitor that monitors the state of the device 10G, and displays parameters and the like calculated by the control device 100.

In Example 3, the machining center is used as an example of the device 10G. Machining sensors manufacture copper electrodes for electric discharge machining used in the manufacture of electronic components such as relays and switches. High-precision machining is required, and machining is performed using a small end mill with a φ of 0.2 to 6 mm. The problem with this process is that the end mill may break depending on the machining conditions, and if the end mill is prevented from breaking, the machining time will increase.

On the other hand, if the machining resistance during cutting of the end mill can be measured and quantified, the feed rate of the machining sensor can be adjusted while checking the machining resistance during cutting of the end mill. You can save time.

Therefore, in the monitoring system 4, attention is paid to the sound when scraping metal, a vibration sensor is provided at a place considered to be the source of the sound, and vibration waveform data is acquired. The inventors calculated various features from the vibration waveform data and analyzed the features having a high affinity for processing resistance. As a result, the inventors have found that the maximum amplitude of the vibration waveform data is proportional to the machining resistance.

FIG. 18 is a diagram showing the relationship between the maximum amplitude of the vibration waveform and the machining resistance according to the third embodiment. As shown in FIG. 18, it can be seen that the maximum amplitude of the vibration waveform data is proportional to the machining resistance measured by using the dynamometer.

Therefore, the processing unit 154 of the control device 100 in the monitoring system 4 obtains the maximum amplitude of the vibration data, and the transmitting unit 156 transmits the data of the maximum amplitude to the information processing device 300. The monitoring unit 354 of the information processing apparatus 300 monitors the maximum amplitude proportional to the machining resistance. The generation unit 356 may generate sound data from the vibration waveform, and the output unit 358 may output the sound data from the speaker. Further, the generation unit 356 may calculate the scoring data from the maximum amplitude using a predetermined calculation algorithm, and the output unit 358 may display the scoring data on the monitor screen.

As a result, the feed rate is controlled according to the machining resistance proportional to the maximum amplitude of the vibration waveform, so that the machining sensor can be operated at an appropriate feed rate while preventing the end mill from breaking, and the machining time can be reduced.

It is also possible to apply the monitoring system 4 in the third embodiment to the grinding process. For example, in the grinding process, since the object is ground by grinding, vibration in a high frequency region appears in a wide range. Using this feature, the processing unit 154 of the control device 100 can visualize the machining state as described above by quantifying the start of the high frequency region.

§4 Modifications Although the embodiments of the present invention have been described in detail above, the above description is merely an example of the present invention in all respects. Needless to say, various improvements and modifications can be made without departing from the scope of the present invention. For example, the device 10 is not limited to the above-mentioned example, and can be applied as long as it is accompanied by vibration during operation of the device.

For example, the device 10 can be applied to a omelet manufacturing device, a device including a pump other than a vacuum pump, a molding machine, a press machine, a device including a bearing cylinder, and the like. The programs described in the embodiments and the respective examples of the present disclosure may be provided in a state of being stored in a computer-readable storage medium. The storage medium can store the program in a “non-temporary tangible medium”. Programs include, but are not limited to, software programs and computer programs as examples. Further, the scoring data is not limited to the vibration waveform, and may be calculated using other sensing data.

(Appendix 1)
A control device (100) that receives each sensing data from one or a plurality of sensors provided in a device including a power source and calculates one or a plurality of feature quantities from the respective sensing data.
A storage device (200) that stores each feature amount received from the control device in association with each of the sensing data, and
Information processing that monitors each of the feature quantities, generates sound data or scoring data indicating the operating state of the device based on the vibration waveform included in the sensing data, and outputs the sound data or the scoring data. Device (300) and
Surveillance system (1-4).
(Appendix 2)
When an abnormality of the device is detected based on the respective feature amounts, the information processing device (300) converts the vibration waveform within a predetermined time based on the time when the abnormality is detected into the sound data. The monitoring system (1-4) according to claim 1.
(Appendix 3)
The monitoring system (1) according to claim 1 or 2, wherein the information processing device (300) converts the vibration waveform of a section designated by the user among the vibration waveforms stored in the storage device into the sound data. ~ 4).
(Appendix 4)
The information processing device (300) is a comparison target with each of the feature quantities, and any of claims 1 to 3 which adjusts each threshold value used for abnormality determination based on the normality or abnormality determination result of the user. The monitoring system (1-4) according to item 1.
(Appendix 5)
The monitoring system (1 to 2) according to any one of claims 1 to 4, wherein the control device (100) can additionally calculate a feature amount according to an abnormality content of the device.
(Appendix 6)
The monitoring system (1, 3) according to claim 1, wherein the information processing device (300) displays the scoring data and an appropriate range for the scoring data on a display device.
(Appendix 7)
The monitoring system (1, 3) according to claim 6, wherein the information processing device (300) displays a comparison result between the scoring data and the appropriate range on the display device.
(Appendix 8)
A monitoring unit (354) that monitors each feature calculated based on each sensing data from one or more sensors provided in the device including the power source, and
A generation unit (356) that generates sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data.
An output unit (358) that outputs the sound data or the scoring data, and
(100).
(Appendix 9)
A monitoring step for monitoring each feature calculated based on each sensing data from one or more sensors provided in a device including a power source.
A generation step of generating sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data.
An output step that outputs the sound data or the scoring data, and
Is an information processing method executed by the information processing apparatus (300).
(Appendix 10)
A monitoring step for monitoring each feature calculated based on each sensing data from one or more sensors provided in a device including a power source.
A generation step of generating sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data.
An output step that outputs the sound data or the scoring data, and
Is executed by the information processing apparatus (300).

1, 2, 3, 4 ... Monitoring system,
20, 30, 40 ... Sensor,
50 ... IO slave,
60 ... Waveform measurement unit,
100 ... Control device,
102 ... Processor, 104 ... Chipset, 106 ... Main storage, 108 ... Secondary storage, 110 ... Network controller, 114 ... Memory card interface, 122 ... Internal bus controller, 124 ... I / O unit,
152 ... Receiver unit, 154 ... Processing unit, 156 ... Transmitter unit 200 ... Storage device,
300 ... Information processing device,
302 ... Processor, 304 ... Memory, 306 ... Storage device, 308 ... Input I / F section, 310 ... Data I / F section, 312 ... Communication I / F section, 314 ... Display device,
352 ... Receiver unit, 354 ... Monitoring unit, 356 ... Generation unit, 358 ... Output unit

Claims (9)

1. A control device that receives each sensing data from one or more sensors provided in a device including a power source and calculates one or more features from each of the sensing data.
   A storage device that stores each feature amount received from the control device in association with each of the sensing data,
   Information processing that monitors each of the feature quantities, generates sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data, and outputs the sound data or the scoring data. With the device
   A monitoring system equipped with.
2. The information processing device, when an abnormality of the device is detected based on each of the feature quantities, converts the vibration waveform within a predetermined time based on the time when the abnormality is detected into the sound data. The monitoring system described in.
3. The monitoring system according to claim 1 or 2, wherein the information processing device converts the vibration waveform of a section designated by the user among the vibration waveforms stored in the storage device into the sound data.
4. The information processing device is a comparison target with each of the feature quantities, and any one of claims 1 to 3 adjusts each threshold value used for abnormality determination based on the normality or abnormality determination result of the user. The monitoring system described in.
5. The monitoring system according to any one of claims 1 to 4, wherein the control device can additionally calculate a feature amount according to an abnormality content of the device.
6. The monitoring system according to claim 1, wherein the information processing device displays the scoring data and an appropriate range for the scoring data on a display device.
7. The monitoring system according to claim 6, wherein the information processing device displays a comparison result between the scoring data and the appropriate range on the display device.
8. A monitoring unit that monitors each feature calculated based on each sensing data from one or more sensors provided in the device including the power source.
   A generation unit that generates sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data.
   An output unit that outputs the sound data or the scoring data,
   Information processing device equipped with.
9. A monitoring step for monitoring each feature calculated based on each sensing data from one or more sensors provided in a device including a power source.
   A generation step of generating sound data or scoring data indicating the operating state of the device based on the vibration waveform included in each of the sensing data.
   An output step that outputs the sound data or the scoring data, and
   Information processing method that the information processing device executes.
   
   
   

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