Processing system, program, and processing method

Abstract

To provide a processing system and the like that can perform condition observation, quality control, or predictive maintenance of an object on the basis of vibration analysis using information on vibration of a plurality of channel.SOLUTION: A processing system 100 includes an acquisition unit 111, a calculation unit 112, and an output unit 114. The acquisition unit 111 acquires first vibration information of a first channel and second vibration information of a second channel related to vibration of an object. The calculation unit 112 calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and second vibration information. The output unit 114 outputs presentation information on at least one of condition observation, quality control, and predictive maintenance of the object on the basis of the spectrogram.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to a processing system, a program, a processing method, and the like.

Background Art

[0002] Patent Document 1 discloses an inspection method for inspecting an automotive part having an operating part such as a motor as an object to be inspected. In the inspection method, waveform data regarding the operating sound of the object to be inspected is acquired by a microphone arranged near the object to be inspected, a short-time Fourier transform is performed on the waveform data to generate a complex spectrogram, a predetermined phase feature amount is calculated based on the complex spectrogram, the phase feature amount is differentiated in the frequency direction to calculate a group delay, a smoothing filter process is performed on the group delay, and the intensity level of the abnormal sound component is calculated based on the group delay after the smoothing filter process.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, the waveform data of one channel acquired by a microphone is used for inspection. Patent Document 1 does not disclose performing state monitoring, quality control, or predictive maintenance of an object based on vibration analysis using vibration information of a plurality of channels.

Means for Solving the Problems

[0005] One aspect of the present disclosure relates to a processing system including an acquisition unit that acquires first vibration information of a first channel and second vibration information of a second channel regarding vibrations of an object, a calculation unit that calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information, and an output unit that outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram.

[0006] Another aspect of the present disclosure relates to a program that causes a computer to function as an acquisition unit that acquires first vibration information of a first channel and second vibration information of a second channel regarding vibrations of an object, a calculation unit that calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information, and an output unit that outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram.

[0007] Still another aspect of the present disclosure relates to a processing method that acquires first vibration information of a first channel and second vibration information of a second channel regarding vibrations of an object, calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information, and outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram.

Brief Description of the Drawings

[0008]

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Mode for Carrying Out the Invention

[0009] Hereinafter, preferred embodiments of the present disclosure will be described in detail. It should be noted that the embodiments described below do not unduly limit the content described in the claims, and not all of the configurations described in the embodiments are essential constituent elements.

[0010] 1. Processing system FIGS. 1 to 3 are explanatory diagrams of a sensor that detects vibrations of an object. As shown in FIG. 1, the object 10 includes, for example, a vibration source 11 that generates vibrations by mechanical operation. The sensor 140 detects the vibrations of the object 10 generated by the vibration source 11. The vibration source 11 is, as an example, a motor, an engine, a turbine, or the like. Further, the object 10 may not include the vibration source 11, vibrations may be applied from the outside of the object 10, and the sensor 140 may detect the vibrations.

[0011] The object 10 is, for example, the vibration source 11 itself, that is, a motor, an engine, a turbine, or the like. Alternatively, the object 10 is a machine, device, or apparatus including the vibration source 11, such as a home appliance or industrial equipment like a printer, an air conditioner, a robot, a pump, a belt conveyor, or a processing device, a moving body such as an automobile or an airplane, or industrial facilities such as a generator or a manufacturing plant. Alternatively, the object 10 may be a structure that vibrates due to an external force, such as a building, a road, or a bridge.

[0012] The sensor 140 detects acceleration, velocity, displacement, angular acceleration, angular velocity, or angle, and outputs a signal indicating the detected physical quantity as vibration information. The sensor 140 may be a sensor that detects one type of physical quantity, or a sensor that detects a plurality of types of physical quantities. Further, the sensor 140 may be a sensor that detects a physical quantity of one axis, or alternatively, a sensor that detects a physical quantity of two or more axes. The sensor 140 outputs vibration information from one or a plurality of channels. One channel means a channel that outputs a signal of one type of physical quantity on one axis.

[0013] FIG. 2 shows a first configuration example of a sensor having two channels. The sensor 140 includes a first vibration sensor 141, and the first vibration sensor 141 has a first channel CH1 and a second channel CH2. Note that the first vibration sensor 141 may have three or more channels.

[0014] FIG. 3 shows a second configuration example of a sensor having two channels. The sensor 140 includes a first vibration sensor 141 and a second vibration sensor 142. The first vibration sensor 141 has a first channel CH1, and the second vibration sensor 142 has a second channel CH2. Note that the sensor 140 may include three or more vibration sensors, and each vibration sensor may have two or more channels.

[0015] Hereinafter, each of the first vibration sensor 141 and the second vibration sensor 142 will also be simply referred to as a vibration sensor.

[0016] The vibration sensor is an acceleration sensor or a gyro sensor that uses a crystal oscillator as a detection element, or an acceleration sensor or a gyro sensor that uses MEMS as a detection element, etc. The vibration sensor may also be an IMU that combines an acceleration sensor and a gyro sensor into a unit. The vibration sensor may detect velocity or displacement by integrating the acceleration detected by the detection element, or may use a detection element that detects velocity or the like. The vibration sensor may detect angular acceleration or angle by differentiating or integrating the angular velocity detected by the detection element, or may use a detection element that detects angular acceleration or the like. An example of an acceleration sensor is a sensor that utilizes the change in vibration frequency according to the stress applied to a crystal oscillator and detects acceleration by measuring the vibration frequency. An example of a gyro sensor is a sensor that detects angular velocity by detecting the Coriolis force applied to a crystal oscillator. Another example of an acceleration sensor or a gyro sensor is a sensor that is configured with a mass part and electrodes by MEMS and detects acceleration or angular velocity by detecting the capacitance between the electrodes that changes according to the inertial force applied to the mass part.

[0017] Although the vibration sensor is assumed to be attached so as to contact the object 10, it is not limited thereto, and it is sufficient that vibration is transmitted from the object 10 to the vibration sensor. The first vibration sensor 141 and the second vibration sensor 142 are attached to different positions of the object 10. One vibration sensor is a sensor unit attached to a certain position of the object 10. However, one vibration sensor may be composed of a plurality of sensor units attached to substantially the same position of the object 10.

[0018] Figure 4 is a configuration example of a processing system. The processing system 100 infers the state of an object by analyzing the vibration information of the object. Details of the state will be described later. The processing system 100 includes a processing unit 110, a storage unit 120, a sensor 140, and a presentation unit 150. Note that the sensor 140 may be provided outside the processing system 100 and connected to the processing system 100 via a cable, a network, or the like.

[0019] The processing unit 110 includes an acquisition unit 111, a calculation unit 112, and an output unit 114.

[0020] The acquisition unit 111 acquires the vibration information of the object from the sensor 140 by receiving the signal of the physical quantity output by the sensor 140. The sensor 140 may output either an analog signal or digital data. When receiving an analog signal, the acquisition unit 111 may include an A / D converter that A / D-converts the analog signal into digital data. The acquisition unit 111 acquires at least the first vibration information of the first channel and the second vibration information of the second channel, and outputs them to the calculation unit 112. The vibration information is time-series vibration data indicating acceleration, velocity, displacement, angular acceleration, angular velocity, or angle detected by the sensor 140. Note that the acquisition unit 111 may acquire vibration information of three or more channels.

[0021] The calculation unit 112 calculates at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram from the first vibration information and the second vibration information. In addition to the above, the calculation unit 112 may calculate a spectrogram of amplitude, power, or phase from the first vibration information, or may calculate a spectrogram of amplitude, power, or phase from the second vibration information.

[0022] For a detailed example of the spectrogram, it will be described later with reference to FIGS. 9 to 22. Also, the detailed method for calculating various spectrograms will be described later. Here, the outline of the spectrogram will be explained. A spectrogram is obtained by successively obtaining spectra while shifting the cutout range of the time-series signal in the time direction, and represents the time change of the spectra. Generally, the horizontal axis represents time, the vertical axis represents frequency, and the signal intensity is often represented by color or shading. A spectrum is the distribution obtained by decomposing a time-series signal into components for each frequency according to a predetermined calculation rule such as Fourier transform and representing it as a function of frequency.

[0023] More specifically, a spectrogram is two-dimensional data in which data is arranged at each point on the time axis and the frequency axis. A column of data in the frequency axis direction at a certain time indicates the spectrum of the vibration at that time. By obtaining the spectra in a time series, a spectrogram is generated. For example, in the amplitude spectrogram, the data at each point is amplitude data, and in the phase spectrogram, the data at each point is phase data. When a plurality of spectrograms are obtained, for example, when using a multi-axis sensor, the plurality of spectrograms may be stacked in the depth direction to form three-dimensional data.

[0024] As spectrograms related to phase, there are a phase spectrogram, a cross-phase spectrogram, or a cross-power spectrogram. The phase spectrogram represents the frequency characteristics of the phase in the vibration data of one channel. The cross-phase spectrogram represents the frequency characteristics of the phase difference between channels of a plurality of channels as an angle. The cross-power spectrogram represents the frequency characteristics of the phase difference and magnitude (size) between channels of a plurality of channels. The cross-power spectrogram can be obtained by calculating the product of the Fourier transform of the vibration data of one channel and the complex conjugate of the Fourier transform of the vibration data of the other channel.

[0025] As spectrograms related to amplitude, there are amplitude spectrograms, power spectrograms, or cross - power spectrograms. The amplitude spectrogram represents the frequency characteristics of the amplitude in one - channel vibration data. The power spectrogram represents the frequency characteristics of the power in one - channel vibration data. The cross - power spectrogram is as described above.

[0026] The coherence spectrogram is obtained by normalizing the cross - power spectrogram with the product of the powers of the respective signals.

[0027] The calculation unit 112 converts the spectrogram into image data using a color map or the like, and outputs the image data to the output unit 114. In the spectrogram converted into image data, each point on the time axis and the frequency axis corresponds to a pixel. The color map is a map that associates the data values in the spectrogram with color data.

[0028] The number of pixels in the frequency direction of the spectrogram may be more than the number of pixels in the time direction. For example, the calculation unit 112 may generate a spectrogram in which the number of pixels in the frequency direction is the same as the number of pixels in the time direction, and compress - process the spectrogram in the time direction. Alternatively, the calculation unit 112 may generate a spectrogram in which the number of pixels in the frequency direction is more than the number of pixels in the time direction from the vibration data. It is assumed that there is more information on the vibration state in the frequency direction than in the time direction. Therefore, it is desirable that the resolution in the frequency direction of the spectrogram is higher than the resolution in the time direction.

[0029] Note that the arithmetic unit 112 may output the spectrogram itself to the output unit 114, regarding the spectrogram as image data without converting it into a color map. Further, the arithmetic unit 112 may convert the spectrogram related to the phase into image data using a non-cyclic color map. In the image data after conversion by the color map, each pixel generally has three elements. However, when the value of the spectrogram is a complex number, it may be converted regarding the values corresponding to the real part and the imaginary part as image data having two elements. Alternatively, two grayscale images each having a value corresponding to each of the real part and the imaginary part may be used. Since a complex number includes phase information, the phase can be handled without explicitly calculating the phase θ. Since the number of elements is reduced, memory usage is saved.

[0030] The output unit 114 outputs presentation information for the user to the presentation unit 150 based on the spectrogram from the arithmetic unit 112. The output unit 114 analyzes the vibration state from the spectrogram and generates presentation information based on the analysis result. The vibration state is a state related to at least one of state monitoring of an object, quality control, and predictive maintenance. That is, the presentation information is information related to at least one of state monitoring of an object, quality control, and predictive maintenance. Detailed examples of state monitoring, quality control, and predictive maintenance will be described later. The output unit 114 classifies, for example, to which of a plurality of vibration states the vibration state of the object belongs, or detects an abnormality or a failure of the object or the like. The classification result is a probability of each vibration state, a flag indicating which vibration state it is, or the like. The detection result is a flag indicating whether an abnormality or a failure has been detected or the like. The presentation information is information for presenting these to the user.

[0031] Various methods for analyzing the vibration state from a spectrogram are assumed. The output unit 114 classifies or detects the vibration state based on, for example, statistical information obtained from the spectrogram or its time change. The statistical information is an average value, a median value, a minimum value, a maximum value, a variance, a standard deviation, a histogram, or the like. These statistical information may be calculated from a data series arranged along the time direction or the frequency direction in the spectrogram, or may be calculated from the data of the whole or a partial region of the spectrogram. The output unit 114 classifies or detects the vibration state by using, for example, threshold processing, pattern matching, or AI recognition on the statistical information or its time change.

[0032] Alternatively, the output unit 114 classifies or detects the vibration state based on the time change of the spectrogram in a specific frequency range. The specific frequency range is a frequency range that is likely to change under the influence of the vibration state in the frequency characteristics of the vibration. The specific frequency range includes or is in the vicinity of the resonance frequency of the object, includes or is in the vicinity of the vibration frequency of the vibration source, or includes or is in the vicinity of the harmonic frequency of the vibration frequency of the vibration source, etc., but is not limited thereto. The time change of the spectrogram is the time change within one spectrogram obtained in a certain time range. Alternatively, the time change of the spectrogram means that when the first to nth spectrograms are obtained in the first to nth time ranges of the time series where n is an integer of 2 or more, it is the time change occurring in the first to nth spectrograms of the time series.

[0033] Alternatively, the output unit 114 may input the spectrogram into the learned model, and the learned model may output the above classification result or detection result through inference based on the spectrogram. In the learning stage, the learning system generates a learned model by pre-training the model using teacher data. The learning system is a computer or a cloud system in which a plurality of computers are connected by a network or the like. The teacher data includes a plurality of spectrograms and the correct label for each spectrogram. The correct label in the classifier is, for example, a flag indicating which of a plurality of vibration states it corresponds to. The correct label in the detector is, for example, a flag indicating whether the object is abnormal or faulty.

[0034] The learned model is a neural network for image recognition using deep learning. The neural network for image recognition is, for example, a CNN or a ViT. CNN is an abbreviation for Convolutional Neural Network. ViT is an abbreviation for Vision Transformer. Although Transformer is used in models in various fields, what uses it for image recognition is collectively referred to as ViT.

[0035] The presentation unit 150 presents the presentation information from the output unit 114 to the user. The presentation unit 150 is, for example, a display, a speaker, a lamp, a vibrator, or the like. The presentation information is what shows the above classification result or detection result by numerical values, characters, colors, images, sounds, lights, vibrations, or the like. Note that the output unit 114 may save the classification result of the vibration state, the detection result of the vibration state, or the presentation information generated therefrom to the memory or the storage. The memory or the storage may be common to the following storage unit 120.

[0036] The storage unit 120 stores a program 135 that describes the functions of each part of the processing unit 110. The processing unit 110 realizes the processing of the acquisition unit 111, the calculation unit 112, and the output unit 114 by executing the program 135 read from the storage unit 120. Note that the program 135 may include the above-mentioned learned model.

[0037] As the hardware configuration of the processing system 100, various configurations may be adopted. The processing system 100 is, for example, a computer, or a cloud system in which a plurality of computers are connected by a network or the like. The computer is not limited to a general-purpose one such as a personal computer, and may be a dedicated one for performing the vibration analysis of the present embodiment, or one incorporated in a specific device or the like.

[0038] The processing unit 110 is, as an example, a processor. The processor includes, for example, one or more of a CPU, a GPU, a microcomputer, a DSP, an ASIC, or an FPGA. CPU is the abbreviation of Central Processing Unit. GPU is the abbreviation of Graphics Processing Unit. DSP is the abbreviation of Digital Signal Processor. ASIC is the abbreviation of Application Specific Integrated Circuit. FPGA is the abbreviation of Field Programmable Gate Array. The storage unit 120 stores a program 135 that describes the functions of each part of the processing unit 110. The processor realizes the functions of each part of the processing unit 110 as processing by executing the program 135 stored in the storage unit 120.

[0039] The processing unit 110 is not limited to the software processing as described above, and may be a circuit in which the functions of each part are implemented in hardware. In that case, the storage unit 120 may not store a program.

[0040] The memory unit 120 is a memory or a register. The memory is a volatile memory such as a RAM, or a non-volatile memory such as an OTP memory or an EEPROM. RAM is the abbreviation of Random Access Memory. OTP is the abbreviation of One Time Programmable. EEPROM is the abbreviation of Electrically Erasable Programmable Read Only Memory.

[0041] Note that a non-temporary information storage medium, which is a computer-readable medium, may store the above program 135. The information storage medium is, for example, an optical disk, a memory card, a hard disk drive, or a non-volatile semiconductor memory.

[0042] 2. Processing Flow FIG. 5 is an example of a first flow of the process executed by the processing unit. In steps S31 and S32, the acquisition unit 111 acquires the first vibration information of the first channel and the second vibration information of the second channel from the sensor 140. The first vibration information and the second vibration information are, for example, vibration information at the same time, but this flow may be similarly applied to vibration information at different times.

[0043] In step S33, the calculation unit 112 calculates a cross-power spectrogram, a cross-phase spectrogram, or a coherence spectrogram from the first vibration information and the second vibration information.

[0044] In step S34, the output unit 114 analyzes the spectrogram output by the calculation unit 112 and outputs presentation information to the presentation unit 150 based on the result.

[0045] Note that the calculation unit 112 may obtain first to m-th hour spectrograms corresponding to the first to m-th hours. The output unit 114 may output presentation information based on the first to m-th hour spectrograms. Alternatively, the calculation unit 112 may obtain a reference spectrogram obtained by smoothing the first hour spectrogram in the time direction, and obtain first to m-th difference spectrograms obtained by subtracting the reference spectrogram from the first to m-th hour spectrograms. m is an integer of 1 or more. The output unit 114 may output presentation information based on the first to m-th difference spectrograms.

[0046] Note that the acquisition unit 111 may acquire vibration information of three or more channels. The calculation unit 112 may calculate a cross power spectrogram or the like from the vibration information of any two channels among the three channels.

[0047] FIG. 6 is a second flow example of the process executed by the processing unit. In steps S41 and S42, the acquisition unit 111 acquires first vibration information of the first channel and second vibration information of the second channel from the sensor 140.

[0048] In step S43, the calculation unit 112 calculates a first type of spectrogram among a cross power spectrogram, a cross phase spectrogram, or a coherence spectrogram from the first vibration information and the second vibration information. This is set as the first spectrogram.

[0049] In step S44, the calculation unit 112 calculates a second type of spectrogram different from the first type among a cross power spectrogram, a cross phase spectrogram, or a coherence spectrogram from the first vibration information and the second vibration information. This is set as the second spectrogram.

[0050] In step S45, the arithmetic operation unit 112 performs an arithmetic operation on the first spectrogram and the second spectrogram. The arithmetic operation is an addition, subtraction, multiplication, division, or a combination thereof of the first spectrogram and the second spectrogram at the same time. The arithmetic operation unit 112 performs an arithmetic operation on, for example, the spectrogram before conversion by the color map. That is, the arithmetic operation unit 112 performs the above arithmetic operation on the spectrogram value corresponding to the pixel of the first spectrogram and the spectrogram value corresponding to the pixel of the second spectrogram at the same position, and executes it for each pixel. Note that the arithmetic operation unit 112 may perform an arithmetic operation on the spectrogram after conversion by the color map.

[0051] In step S46, the output unit 114 analyzes the spectrogram after the arithmetic operation output by the arithmetic operation unit 112, and outputs presentation information to the presentation unit 150 based on the result.

[0052] Note that the acquisition unit 111 may acquire vibration information of three or more channels. The arithmetic operation unit 112 may calculate the first spectrogram and the second spectrogram from the vibration information of any two channels among the three channels.

[0053] FIG. 7 is a third flow example of the process executed by the processing unit. In steps S51 to S54, the acquisition unit 111 acquires the first vibration information of the first channel, the second vibration information of the second channel, the third vibration information of the third channel, and the fourth vibration information of the fourth channel from the sensor 140.

[0054] In step S56, the arithmetic operation unit 112 calculates a first type of spectrogram among the cross-power spectrogram, the cross-phase spectrogram, or the coherence spectrogram from the first vibration information and the second vibration information. This is set as the first spectrogram.

[0055] In step S57, the arithmetic unit 112 calculates a spectrogram of the same type as the first type from the third vibration information and the fourth vibration information, which is a cross-power spectrogram, a cross-phase spectrogram, or a coherence spectrogram. This is defined as the second spectrogram.

[0056] In step S58, the arithmetic unit 112 performs an arithmetic operation on the first spectrogram and the second spectrogram.

[0057] In step S59, the output unit 114 analyzes the spectrogram after the arithmetic operation output by the arithmetic unit 112, and outputs presentation information to the presentation unit 150 based on the result.

[0058] 3. Vibration analysis example Hereinafter, a specific example of vibration analysis using the above-described method will be described.

[0059] In conventional vibration analysis, it is premised that a change occurs in the amplitude intensity or the frequency peak, and there are few detection methods focusing on the phase change. Further, even when focusing on the phase change, a single-channel sensor is used as in Patent Document 1 described above.

[0060] In the present embodiment, time-series data of vibration is acquired using a plurality of channels of sensors. Then, from the time-series data of vibration, not only an amplitude spectrogram but also a cross spectrogram, a cross-phase spectrogram, a coherence spectrogram, or a spectrogram obtained by an arithmetic operation of these is obtained and analyzed. Since sensor data needs to be synchronized with each other between multiple axes or at different measurement points, a sensor with excellent synchronization performance is used. For example, a unitized sensor such as an IMU is used, but it is not limited thereto.

[0061] The processing system 100 of this embodiment uses vibration data of multiple channels, for example, vibration data of multiple channels with different azimuths at the same position of the object. The processing system 100 calculates a spectrogram related to at least one of amplitude, power, cross, cross-phase, and coherence from the vibration data. The processing system 100 performs weighting of information using the coherence of the vibration data. The processing system 100 uses the spectrogram for state monitoring, quality control, predictive maintenance, etc. of the object. The processing system 100 uses statistical information such as the average value or variance value obtained from the spectrogram as an index, or uses the change in cross-phase or coherence in a specific frequency range as an index. According to this embodiment, since the device vibration is directly used, there is no need to sweep the vibration frequency, and even a slight change in the mass, spring constant, or damper coefficient of the object can be captured without omission.

[0062] The processing system 100 of this embodiment may also use a spectrogram obtained by performing arithmetic operations on two or more spectrograms obtained at different positions of the object among the spectrograms related to amplitude, cross, cross-phase, and coherence. In this way, even if the data is not synchronized with each other in measurements at different positions, they can be compared.

[0063] Also, the processing system 100 of this embodiment may use vibration data of multiple channels with different azimuths at the same position of the object. In this way, even when the vibration intensity does not change but the phase relationship between the vibration direction or azimuth changes, it can be captured as a clear change.

[0064] Also, the processing system 100 of this embodiment may detect the vibration state using the average value or variance value of the spectrogram as an index. In this way, even a slight state change can be detected with high precision.

[0065] An example of vibration analysis is shown below. FIG. 8 is a configuration example of an experimental apparatus. A flask 230 containing 250 of glycerin is placed on a hot plate 260, and the glycerin 250 is heated by the hot plate 260. A stirring rod is attached to a motor 210. The blades 240 of the stirring rod are inserted into the glycerin 250 and stir the glycerin 250 by the rotation of the motor 210. A controller 220 is attached to the motor 210 and controls the rotation of the motor 210.

[0066] The first vibration sensor SENA is attached to the wall surface of the flask 230, and the second vibration sensor SENB is attached to the wall surface of the controller 220. Each vibration sensor is a three-axis velocity sensor. xa, ya, and za are the detection axes of the first vibration sensor SENA, corresponding to the x-axis, y-axis, and z-axis respectively, and are orthogonal to each other. xb, yb, and zb are the detection axes of the second vibration sensor SENB, corresponding to the x-axis, y-axis, and z-axis respectively, and are orthogonal to each other.

[0067] The viscosity of glycerin 250 changes according to the temperature. It is known that its viscosity is about 100 mPa·s at 40 degrees Celsius and about 10 mPa·s at 70 degrees Celsius.

[0068] The measurement procedure is as follows. First, insert the stirring rod into the flask 230. Pour 200 ml of glycerin into the flask 230. The flask 230 is a separable flask, and its upper and lower parts are fixed together with a coupling clamp. Set the motor 210, which is the main body of the stirrer, etc. on the flask 230, and place the flask 230 on the hot plate 260. Fix the first vibration sensor SENA and the second vibration sensor SENB to the apparatus with double-sided tape.

[0069] Set the hot plate 260 to 40 degrees Celsius and heat glycerin 250 on the hot plate 260. Set the stirring speed to 256 rpm and start stirring. Gradually raise the temperature of the hot plate 260 to 70 degrees Celsius over 1 hour, and measure the vibration associated with stirring during the temperature increase using the first vibration sensor SENA and the second vibration sensor SENB. The stirrer was temporarily stopped at the 45-minute mark to measure the temperature midway. The stirring speed during re-stirring was 250 rpm, which shifted slightly to the lower speed side compared to before stopping.

[0070] It was also confirmed visually from the state of the liquid surface during stirring that as the temperature increased, the viscosity of glycerin 250 clearly decreased.

[0071] The first vibration sensor SENA and the second vibration sensor SENB are 3-axis digital output crystal vibration sensors, and the vibration band is 10 - 1000 Hz. Double-sided tape that was confirmed to have no effect on the measurement band was used to fix the vibration sensors. The sampling rate of the measurement is 3000 samples / second.

[0072] In the forced vibration frequency response model of the degree-of-freedom viscous damping system, it is known that when the elastic coefficient or the damper coefficient changes, the vibration amplitude or the phase changes. By sensing the vibration as the response of the forced vibration by the stirrer and confirming the change over time of the relative phase in the time-series data, it is expected that changes in viscoelasticity can be detected. It is difficult to measure the absolute phase of vibration, but the change in the relative phase between two vibration data can be measured. The relative phase is considered to contain information corresponding to the state of the rotating equipment, and the relative phase itself can be an index representing the state of the analysis target. However, the object to which the vibration analysis method of the present embodiment can be applied is not limited to the degree-of-freedom viscous damping system, and may be, for example, a device composed only of solids.

[0073] Hereinafter, an example of a spectrogram obtained by the apparatus of FIG. 8 is shown. Since the vibration energy is concentrated in a relatively low frequency band, the spectrogram in the frequency range of 0 - 200 Hz is illustrated.

[0074] Figures 9 to 11 are examples of spectrograms obtained from the vibration data output by the first vibration sensor. The "x-y axis" indicates that the relative phase difference between the vibration data on the x-axis and the vibration data on the y-axis is used. The same applies to the "y-z axis" and "z-x axis".

[0075] The amplitude spectrogram is obtained by using a rectangular window function with a width of 4 seconds and shifting it in the time direction while overlapping the window function by 2 seconds each time. The relative phase spectrogram is a plot of the phase difference between the target channels as the relative phase for the phase of the complex number when calculating the amplitude spectrogram. The coherence spectrogram is obtained by preparing two channels of time-series data with a width of 4 seconds cut out by a rectangular window function, calculating the coherence thereof, and repeating it with an overlap of 2 seconds of the window function. A color map is shown on the right side of each spectrogram. The amplitude is in dB value. The cross phase is shown numerically from -π to +π radians. The coherence is a numerical value in the range of 0 to 1.

[0076] Figures 9 to 11 show spectrograms calculated from 5-minute time-series data cut out from the vibration data of the first vibration sensor SENA. By comparing the amplitude spectrogram and the cross phase spectrogram with the coherence spectrogram, an estimate can be made of which vibration frequency components have a large correlation.

[0077] Frequencies at which the coherence spectrogram is dark indicate low inter-channel correlation at those frequencies, while frequencies at which the coherence spectrogram is bright indicate high inter-channel correlation at those frequencies. For example, between 150 and 200 Hz, the inter-channel correlation is low. At frequencies with low inter-channel correlation, the relationship of the relative phase of the vibration components is unstable. Therefore, in the cross-phase spectrogram, the values become random, and thus the color becomes random. When the state of vibration changes, the color or distribution of the spectrogram changes. Since the stripe pattern in the horizontal axis direction is stable, in this specific example, it can be seen that it is a steady vibration if it is about 5 minutes.

[0078] Figures 12 and 13 show the spectrograms of the first vibration sensor immediately after the start of measurement, 15 minutes later, 30 minutes later, and 60 minutes later. Here, the y-axis amplitude spectrogram, the y-x axis cross-phase spectrogram, and the y-x coherence spectrogram are shown. Similar considerations are also possible for the x-axis and z-axis.

[0079] 15 minutes later: A slight change in the peak intensity distribution can be confirmed in the amplitude spectrogram. In the relative phase spectrogram and the coherence spectrogram, the changes are clearly captured. For example, in the cross-phase spectrogram, the stripe pattern between 100 and 150 Hz has changed. Also, in the coherence spectrogram, the bright stripe pattern around 75 Hz has changed to a thicker and brighter stripe pattern.

[0080] 30 minutes later: There is an impression that the intensity values have generally increased in the amplitude spectrogram. Since the impressions of the cross-phase spectrogram and the coherence spectrogram do not change, it can be seen that there are few changes from the perspective of viscoelasticity.

[0081] After 60 minutes: Clear changes can be confirmed in each of the amplitude spectrogram, cross-phase spectrogram, and coherence spectrogram. For example, the frequency or density of the striped pattern changes in the cross-phase spectrogram and coherence spectrogram. From this, it can be read that the viscosity of glycerin 250 has decreased and the state of vibration has changed.

[0082] As described above, it can be seen that overall, the cross-phase spectrogram and coherence spectrogram have larger changes than the amplitude spectrogram and are more sensitive to changes in the vibration state. Also, for example, changes have occurred in the amplitude spectrogram after 60 minutes, and it can be seen that the sensitivity is further improved by combining the amplitude spectrograms.

[0083] Figures 14 and 15 show the differences between the spectrogram of the first vibration sensor and the reference spectrogram immediately after the start of measurement, after 15 minutes, after 30 minutes, and after 60 minutes.

[0084] The reference spectrogram of the amplitude spectrogram is the average of the amplitude spectrograms immediately after the start of measurement in the time axis direction. The same applies to the reference spectrograms of the cross-phase spectrogram and coherence spectrogram. By subtracting the reference spectrogram from the spectrogram at each time, it becomes easier to capture the changes from the reference spectrogram.

[0085] Immediately after the start of measurement: Since the reference spectrogram is subtracted, the value approaches 0 in the band where the value is stable. When the value fluctuates, the distribution has an average value of 0 and gives a rough impression. The greater the fluctuation, the stronger the color.

[0086] After 15 minutes: A slight increase in the peak intensity distribution can be confirmed in the amplitude spectrogram. In the cross-phase spectrogram and coherence spectrogram, changes in the vibration state are captured, and the change in the coherence spectrogram is particularly large.

[0087] After 30 minutes: It can be confirmed that the intensity of the amplitude spectrogram has increased overall. The impression of the cross-phase spectrogram remains unchanged. The shading of the coherence spectrogram has changed. Specifically, in the coherence spectrogram, vibrations with low correlation become even less correlated, and vibrations with high correlation become even more correlated. There are few changes from the perspective of viscoelasticity.

[0088] After 60 minutes: Clear changes can be confirmed in each of the three spectrograms. However, this change is also due to a slight change in the stirring speed, and the frequency shift is also emphasized. From the perspective of capturing the change due to the decrease in viscosity, it is desirable to be able to distinguish it from the change due to a slight change in the stirring speed.

[0089] Figures 16 to 18 are examples of spectrograms obtained from the vibration data output by the second vibration sensor. The creation method of each spectrogram is the same as that in Figures 9 to 11. The mounting positions of the first vibration sensor SENA and the second vibration sensor SENB are different. Comparing the spectrograms in Figures 16 to 18 with the spectrograms in Figures 9 to 11, it can be seen that the vibration states are different due to the difference in the measurement positions.

[0090] Figures 19 and 20 show the spectrograms of the second vibration sensor immediately after the start of measurement, 15 minutes later, 30 minutes later, and 60 minutes later. Here, the y-axis amplitude spectrogram, the y-x axis cross-phase spectrogram, and the y-x coherence spectrogram are shown. Similar considerations are possible for the x-axis and z-axis as well.

[0091] After 15 minutes: The impression of the three spectrograms has not changed significantly since immediately after the start of measurement.

[0092] After 30 minutes: There is an impression that the intensity values in the amplitude spectrogram have increased overall. In the cross-phase spectrogram and the coherence spectrogram, the change in the vibration state is clearly captured.

[0093] After 60 minutes: In response to the decrease in viscosity, distinct changes can be confirmed in each of the three spectrograms.

[0094] Figures 21 and 22 show the differences between the spectrogram of the first vibration sensor and the spectrogram of the second vibration sensor immediately after the start of measurement, after 15 minutes, after 30 minutes, and after 60 minutes. At each of immediately after the start of measurement, after 15 minutes, after 30 minutes, and after 60 minutes, the spectrogram of the first vibration sensor is averaged in the time axis direction, and the difference between the average spectrogram and the spectrogram of the second vibration sensor is shown.

[0095] Immediately after the start of measurement: In each spectrogram, the band where the value is stable approaches 0. When the value fluctuates, the distribution has an average value of 0, giving a rough impression. The greater the fluctuation, the stronger the color.

[0096] After 15 minutes: The impressions of the three spectrograms do not change significantly from immediately after the start of measurement. However, in the coherence spectrogram, changes can be confirmed in the region below 70 Hz.

[0097] After 30 minutes: The intensity values in the amplitude spectrogram are generally increasing. In the cross-phase spectrogram and the coherence spectrogram, changes in the vibration state are clearly captured.

[0098] After 60 minutes: In response to the decrease in viscosity, distinct changes can be confirmed in each of the three spectrograms. The rotational frequency of the stirrer changes from 256 rpm to 250 rpm 45 minutes after the start of measurement. By taking the difference in the spectrograms between the two vibration sensors, the influence of the rotational frequency of the stirrer can be canceled. As a result, the changes due to the decrease in viscosity can be separated from the changes due to a slight change in the stirring speed, and the vibration state can be detected more accurately.

[0099] Note that in the above description, the average value of the spectrogram in the time axis direction is obtained for each frequency and used as the reference spectrum, but the method for creating the reference spectrum is not limited to this. For example, without taking the average value, the difference between the spectrograms of the vibration sensors may be calculated using an arbitrary spectrogram itself as the reference.

[0100] 4. Examples of methods for creating presentation information from spectrograms The output unit 114 extracts characteristic frequencies from the entire spectrogram. The characteristic frequencies are, for example, the peak frequency or the frequency at which the intensity distribution is stable. The output unit 114 represents, as a graph or the like, the change in the target information amount at the extracted frequencies as a function of time. The target information amount is the intensity value, the relative phase, or the like. The function may be any that shows the temporal change, such as a mathematical formula or the time-series data of the target information amount. The output unit 114 obtains the statistic of the target information amount in the steady state using the above function. The statistic is the average value, the variance, or the like of the above function. The output unit 114 sets a threshold for the statistic and causes the warning presentation unit 150 to output a warning when the statistic exceeds the threshold.

[0101] FIG. 23 shows a first example of the presentation information. Regarding the viscosity change of glycerin due to temperature rise, the vibration generated during stirring was measured, and an amplitude spectrogram, a cross-phase spectrogram, and a coherence spectrogram were obtained.

[0102] Attention was paid to 60.5 Hz as the characteristic frequency. The upper part of FIG. 23 shows a time-series plot of the amplitude value at 60.5 Hz of the y-axis vibration data. The middle part of FIG. 23 shows a time-series plot of the cross-phase at 60.5 Hz of the y-axis and z-axis vibration data. Regarding the cross-phase plot, a 60-second moving average is plotted as a thick black dot for ease of viewing. The lower part of FIG. 23 shows a time-series plot of the coherence at 60.5 Hz of the y-axis and z-axis vibration data.

[0103] Although no clear change over time can be confirmed from the amplitude plot and the coherence plot, a phase change correlated with the viscosity change can be extracted from the cross-phase plot. By using this as an index, it can be utilized, for example, in quality control during the material manufacturing process.

[0104] Figures 24 and 25 are the second example of the presented information. In a measurement different from that of Figure 23, the viscosity change of glycerin was measured while raising the temperature up to 80 degrees Celsius. Regarding the viscosity change of glycerin due to the temperature rise, the vibration generated during stirring was measured, and an amplitude spectrogram, a cross-phase spectrogram, and a coherence spectrogram were obtained.

[0105] As a characteristic frequency, attention was paid to 108.5 Hz, which is one of the peaks of the amplitude spectrum. The upper part of Figure 24 shows a plot of the amplitude values at 108.5 Hz of the z-axis vibration data in time series. The middle part of Figure 24 shows a plot of the cross-phase at 108.5 Hz of the vibration data of the z-axis and the x-axis in time series. The lower part of Figure 24 shows a plot of the coherence at 108.5 Hz of the vibration data of the z-axis and the x-axis in time series. Incidentally, the jumps in the values that are sometimes observed at 700 seconds, 1600 seconds, 2800 seconds, etc. are vibration noises associated with the operation of the equipment.

[0106] Figure 25 shows the time-series change in the variance in the cross-phase plot. Values were extracted from the cross-phase plot using a 60-second rectangular window function, the variance of the extracted values was obtained, and the variance was obtained one by one while shifting the start point of the rectangular window function by 1 second, and the time-series data was plotted.

[0107] In the second example, the values from 107.0 Hz to 110.0 Hz centered on 108.5 Hz were summed up at each time and the averaged value was used. Thereby, the influence due to the fluctuation of the vibration, that is, due to the peak fluctuation, can be mitigated.

[0108] As shown in the middle part of Figure 24, regarding the viscosity change due to the temperature rise, the cross-phase changes when the viscosity decreases.

[0109] As shown in Fig. 25, in the steady state, the variance of the cross-phase is less than 0.1. Also, the noise associated with the equipment operation does not exceed 0.3. Based on these facts, 0.4 was set as the threshold value, and it was decided to determine an abnormality when this value is exceeded.

[0110] As shown in Fig. 25, at the 6400-second mark, a change that seems to be some kind of phase transition occurred, and since the variance of the cross-phase exceeded the threshold value of 0.4, the system detected an abnormal state and output an alarm. The operator noticed the alarm and then ended the experiment within 30 minutes.

[0111] Note that the method for detecting system abnormalities is not limited to the above. For example, by calculating the moving average of the coherence and predicting the time when the coherence drops below 0.5 from its slope, the time until system abnormality can be estimated.

[0112] As shown in Fig. 24, since no sign of viscosity change clearly appears in the amplitude plot, it is difficult to detect the sign of viscosity change from the amplitude plot. In contrast, signs of viscosity change clearly appear in the cross-phase plot and the coherence plot, and by using these plots, the sensitivity for detecting signs of viscosity change can be improved.

[0113] The processing system 100 of the present embodiment described above includes an acquisition unit 111, a calculation unit 112, and an output unit 114. The acquisition unit 111 acquires first vibration information of a first channel regarding the vibration of the object and second vibration information of a second channel. The calculation unit 112 calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information. The output unit 114 outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram.

[0114] According to this embodiment, it is possible to perform state monitoring, quality control, or predictive maintenance of an object based on vibration analysis using vibration information of a plurality of channels. Even a minute change in the vibration state that is difficult to appear in the amplitude spectrogram of one channel or the like can be detected by using the relative spectrograms of a plurality of channels. For example, even when the change in the intensity value or the like of the amplitude spectrogram is small, a change may occur in the cross phase or coherence between a plurality of channels. By using these spectrograms, the detection sensitivity of the vibration state can be improved.

[0115] Also, in this embodiment, the first vibration information may be vibration information of a first axis detected by a first vibration sensor. The second vibration information may be vibration information of a second axis detected by the first vibration sensor.

[0116] For example, in FIG. 9, the first vibration information is vibration information of the x-axis detected by the first vibration sensor SENA, and the second vibration information is vibration information of the y-axis detected by the first vibration sensor SENA.

[0117] According to this embodiment, at least one spectrogram including a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram can be calculated from the vibration information of the first axis and the vibration information of the second axis at the same position of the object. In this way, by evaluating the correlation of vibrations between a plurality of axes at the same position, a change in the vibration state can be detected. For example, in the case of linear vibration and elliptical vibration, or in the case where the axis of the elliptical vibration is stationary and rotating, the phase correlation changes, and a change occurs in each spectrogram. By detecting these, a minute change in the vibration state can be detected.

[0118] Also, in this embodiment, the first vibration information may be vibration information of a first axis detected by a first vibration sensor. The second vibration information may be vibration information of the first axis or the second axis detected by a second vibration sensor arranged at a position different from the first vibration sensor.

[0119] According to the present embodiment, at least one spectrogram including a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram can be calculated from the vibration information of the first axis at different positions of the object and the vibration information of the first axis or the second axis. The path through which vibration is transmitted from the vibration source to the first vibration sensor is different from the path through which vibration is transmitted from the vibration source to the second vibration sensor. By evaluating the correlation of vibrations at such different positions, a change in the vibration state can be detected.

[0120] Also, in the present embodiment, the first vibration information may be a first physical quantity that is the acceleration, velocity, displacement, angular acceleration, angular velocity, or angle of the first axis among the x-axis, y-axis, and z-axis. The second vibration information may be the first physical quantity of a second axis different from the first axis among the x-axis, y-axis, and z-axis.

[0121] For example, in FIG. 9, the first physical quantity is velocity, the first vibration information is the velocity of the x-axis, and the second vibration information is the velocity of the y-axis.

[0122] Also, in the present embodiment, the first vibration information may be a first physical quantity that is the acceleration, velocity, displacement, angular acceleration, angular velocity, or angle of the first axis among the x-axis, y-axis, and z-axis. The second vibration information may be a second physical quantity different from the first physical quantity among the acceleration, velocity, displacement, angular acceleration, angular velocity, and angle of the first axis.

[0123] When the object vibrates, the acceleration, velocity, displacement, angular acceleration, angular velocity, or angle changes. That is, the vibration state can be estimated by creating a spectrogram from these physical quantities and analyzing the spectrogram.

[0124] Also, in the present embodiment, the output unit 114 may output presentation information based on the statistical information about the spectrogram.

[0125] When the vibration state changes, the statistical information of the spectrogram changes. In the example of FIG. 25, due to the change in the viscosity of glycerin, the dispersion of the cross-phase changes. By utilizing this, the vibration state can be estimated from the statistical information of the spectrogram, and presentation information regarding the vibration state can be output.

[0126] Also, in the present embodiment, the output unit 114 may output presentation information based on the temporal change of the spectrogram in a specific frequency or a specific frequency range.

[0127] In the example of FIG. 23, the specific frequency is 60.5 Hz. In the examples of FIGS. 24 and 25, the specific frequency range is the range of 107.0 Hz to 110.0 Hz centered on 108.5 Hz.

[0128] According to the present embodiment, there is a specific frequency or a specific frequency range in which the influence of the change in the vibration state appears easily in the spectrogram. By analyzing the temporal change of the spectrogram in the specific frequency or the specific frequency range, the vibration state can be estimated, and presentation information regarding the vibration state can be output.

[0129] Also, in the present embodiment, the calculation unit 112 may obtain a reference spectrogram obtained by smoothing the spectrogram in the time direction, and obtain a difference spectrogram obtained by subtracting the reference spectrogram from the spectrogram. The output unit 114 may output presentation information based on the difference spectrogram.

[0130] In the examples of FIGS. 14 and 15, the reference spectrogram is obtained by smoothing each spectrogram immediately after the start of measurement in the time direction. The difference spectrogram is obtained by subtracting the reference spectrogram from each spectrogram immediately after the start of measurement, 15 minutes later, 30 minutes later, and 60 minutes later.

[0131] By taking the difference from the reference spectrogram, the unchanged parts from the reference spectrogram are canceled out, so the changes from the reference spectrogram are emphasized. By using such a difference spectrogram, the sensitivity for detecting changes in the vibration state is improved.

[0132] Also, according to the present embodiment, the arithmetic operation unit 112 may perform an arithmetic operation between a first spectrogram of a first type among three types of cross-power spectrogram, cross-phase spectrogram, and coherence spectrogram of the first vibration information and the second vibration information, and a second spectrogram of a second type different from the first type among the three types. The output unit 114 may output presentation information based on the result of the arithmetic operation.

[0133] Also, in the present embodiment, the acquisition unit 111 may acquire third vibration information of a third channel and fourth vibration information of a fourth channel regarding the vibration of the object. The arithmetic operation unit 112 may perform an arithmetic operation between the first spectrogram and the second spectrogram. The first spectrogram is a spectrogram of a first type among three types of cross-power spectrogram, cross-phase spectrogram, and coherence spectrogram of the first vibration information and the second vibration information. The second spectrogram is a spectrogram of the first type or a second type different from the first type among three types of cross-power spectrogram, cross-phase spectrogram, and coherence spectrogram of the third vibration information and the fourth vibration information. The output unit 114 may output presentation information based on the result of the arithmetic operation.

[0134] According to this embodiment, by performing arithmetic operations on two spectrograms, the spectrogram can be processed so that changes in the vibration state are likely to appear. As a result, the sensitivity for detecting changes in the vibration state is improved. An example of the arithmetic operation is the multiplication of the cross-phase spectrogram and the coherence spectrogram. In the coherence spectrogram, the coherence value in a band with low correlation is small. When the coherence spectrogram is multiplied by the cross-phase spectrogram, the value of the cross-phase spectrogram is multiplied by the band portion where the value of the coherence spectrogram is small in the random band portion. As a result, in the cross-phase spectrogram, the band where the cross-phase is not random but characteristic is emphasized. By using such an emphasized spectrogram, the sensitivity for detecting changes in the vibration state is improved. Note that, as described with reference to FIG. 6 and the like, the object of the arithmetic operation or the content of the operation may be various.

[0135] Further, this embodiment may be implemented as a computer-readable program. The program causes a computer to function as an acquisition unit 111, an arithmetic unit 112, and an output unit 114. The acquisition unit 111 acquires first vibration information of a first channel and second vibration information of a second channel regarding the vibration of an object. The arithmetic unit 112 calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information. The output unit 114 outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram.

[0136] Moreover, this embodiment may be implemented as a processing method. The processing method acquires first vibration information of a first channel and second vibration information of a second channel regarding the vibration of an object. The processing method calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information. The processing method outputs presentation information regarding at least one of condition monitoring, quality control, and predictive maintenance of the object based on the spectrogram. The processing method causes a computer to perform these steps, for example.

[0137] 5. Examples of Vibration Analysis for Condition Monitoring, Quality Control, and Predictive Maintenance Hereinafter, examples of vibration analysis related to condition monitoring, quality control, and predictive maintenance will be shown as examples to which the processing system 100 of this embodiment can be applied.

[0138] Condition Monitoring refers to a technique for continuously or periodically monitoring the current operating state or performance of a machine or equipment. The main purpose of condition monitoring is to monitor specific parameters such as vibration, sound, temperature, or pressure and evaluate the soundness of a machine or equipment. Examples of systems for performing condition monitoring include the following (a) to (f).

[0139] (a) A system that attaches sensors to industrial motors and issues an alarm when abnormal vibration or a temperature rise is detected.

[0140] (b) A system that installs vibration sensors on each part of a building and monitors the vibration during an earthquake or strong wind to monitor the soundness of the building structure.

[0141] (c) A system that has vibration sensors attached to monitor the performance of a gas turbine and warns an operator when abnormal vibration is detected.

[0142] (d) A system in which vibration sensors are attached to monitor the soundness of heavy machinery in mines or quarries, assisting in the early detection of wear or malfunctions.

[0143] (e) A system in which vibration sensors are attached to monitor the soundness of each machine on a factory production line, issuing an alarm when abnormal vibrations are detected.

[0144] (f) A system that utilizes vibration sensors attached to the blades or gearboxes of wind turbines to detect whether abnormal wear or damage has occurred.

[0145] Quality Control refers to the process of verifying whether a product or service meets the defined quality standards or requirements. Examples of systems for performing quality control include the following (g) to (k).

[0146] (g) A system that uses cameras or sensors on a production line to verify the quality of a product in real time, such as its dimensions, color, or shape, and automatically rejects products that deviate from the standards.

[0147] (h) A system that uses a vibration sensor to check the vibration pattern when a product is operated after the assembly process of a product composed of multiple parts. If abnormal vibrations are detected, assembly defects or component malfunctions are suspected.

[0148] (i) A system that operates a motor or generator after manufacturing and measures its vibration during operation using a vibration sensor. If vibrations exceeding specific standards are detected, internal imbalance or damage is suspected.

[0149] (j) A system that installs an electronic device on a vibration test bench and uses a vibration sensor to monitor the impact of vibration in order to verify whether a newly manufactured electronic device has the set vibration resistance.

[0150] (k) A system that monitors vibrations during operation with vibration sensors to confirm whether a new railway vehicle or aircraft has the designed operating performance. If abnormal vibrations are detected, identify the cause and use it to improve quality.

[0151] Predictive Maintenance refers to an approach that collects and analyzes operation data or status data of equipment or machinery. The purpose of predictive maintenance is to predict the risk of future failures or performance degradation. Examples of systems for performing predictive maintenance include the following (l) to (q).

[0152] (l) A system that attaches sensors to industrial robots, analyzes sensor data when the industrial robots are in operation and sensor data when they failed in the past, detects signs that specific parts are precursors to failure, and predictively schedules the replacement of those parts.

[0153] (m) A system that uses sensors attached to the wheels of railway vehicles to monitor the degree of wear and predicts the replacement time of the wheels based on data indicating excessive wear.

[0154] (n) A system that monitors the condition of pipes or valves in oil plants with sensors and predicts the possibility of future leaks.

[0155] (o) A system that analyzes sensor data when elevators or escalators are in operation and predicts the risk of failure before parts need to be replaced.

[0156] (p) A system that monitors the efficiency of industrial cooling devices or air conditioners based on sensor data and predicts component wear or failure.

[0157] (q) A system that collects and analyzes sensor data when agricultural machinery is in operation, predicts component wear or failure, and supports scheduling appropriate maintenance activities.

[0158] 6. Calculation method of spectrogram As a first method, calculation methods of various spectrograms using Fourier transform are shown. Hereinafter, a method of calculating a spectrum from vibration data within a window is shown. A spectrogram is obtained by acquiring spectra in time series while moving the window in the time direction. For example, short-time Fourier transform (STFT) using a window with a fixed width is used.

[0159] The power spectrum PWxy(f) is shown in the following equation (1). t is time, x(t) is a signal as vibration information. f is frequency, and X(f) is the Fourier transform of x(t).

[0160]

Equation

[0161] The cross-power spectrum CRxy(f) is shown in the following equation (2). x(t) is a signal as the first vibration information, and y(t) is a signal as the second vibration information. X(f) is the Fourier transform of x(t), and Y(f) is the Fourier transform of y(t). * indicates complex conjugate.

[0162]

Equation

[0163] The above equation (2) can be rewritten as the following equation (3). The phase angle θ(f) of CRxy(f) represents the cross-phase spectrum. θ(f) is the phase difference between the signals x(t) and y(t) at the frequency f. j is the imaginary unit.

[0164]

Equation

[0165] The coherence spectrum CHxy(f) is shown in the following equation (4). <> represents an appropriate smoothing operation, for example, averaging in the time direction, frequency direction, or both time and frequency directions.

[0166]

Equation

[0167] As a second method, an operation method of various spectrograms using wavelet transform is shown.

[0168] The wavelet transform of the signal x(t) is shown in the following equation (5). Wx(a,b) represents the wavelet transform of the signal x(t) at the scale a and the time point b. Ψ(t) represents the Morlet wavelet function. Ψ* represents the complex conjugate of the wavelet function. a is a scale parameter or dilation parameter, which controls the stretching and shrinking of the wavelet and corresponds to the frequency. b is a transformation position parameter or transformation parameter, which controls the position of the wavelet and corresponds to the time.

[0169]

Equation

[0170] The Morlet wavelet function Ψ(t) is shown in the following equation (6). ω0 specifies the center frequency. As an example, ω0 = 6, but it is not limited thereto. Note that various functions such as the Haar wavelet function or Daubechies wavelet function may be used as the wavelet function.

[0171]

Equation

[0172] The arithmetic expression of the wavelet power spectrogram WPWx(a,b) corresponding to the "power spectrogram" is shown in the following equation (7).

[0173]

Number

[0174] The following equation (8) shows the formula for the cross - wavelet spectrum WCRxy(a,b) corresponding to the "cross - power spectrogram". Wy(a,b) represents the wavelet transform of the signal y(t) at scale a and time point b.

[0175]

Number

[0176] The above equation (8) can be rewritten as the following equation (9). The phase angle θ(a,b) of WCRxy(a,b) represents the cross - phase spectrum. θ(a,b) is the phase difference between the signals x(t) and y(t) at scale a and time point b.

[0177]

Number

[0178] The following equation (10) shows the formula for the wavelet coherence spectrogram WCH(a,b) corresponding to the "coherence spectrogram".

[0179]

Number

[0180] Although the present embodiment has been described in detail as above, those skilled in the art will easily understand that many modifications can be made without substantially departing from the novel matters and effects of the present disclosure. Therefore, all such modifications are intended to be included within the scope of the present disclosure. For example, in the specification or drawings, a term described at least once together with a broader or synonymous different term can be replaced with that different term anywhere in the specification or drawings. Also, all combinations of the present embodiment and the modifications are included within the scope of the present disclosure. Further, the configurations or operations such as the processing unit, the storage unit, the learned model, the sensor, the processing system, the object, the vibration information, and the spectrogram are not limited to those described in the present embodiment, and various modified implementations are possible.

Explanation of Reference Numerals

[0181] 10… Object, 11… Vibration source, 100… Processing system, 110… Processing unit, 111… Acquisition unit, 112… Arithmetic unit, 114… Output unit, 120… Storage unit, 135… Program, 140… Sensor, 141… First vibration sensor, 142… Second vibration sensor, 150… Presentation unit, 210… Motor, 220… Controller, 230… Flask, 240… Stirrer blade, 250… Glycerin, 260… Hot plate, CH1… First channel, CH2… Second channel

Claims

1. An acquisition unit that acquires first vibration information of a first channel and second vibration information of a second channel regarding vibration of an object; An arithmetic unit that calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information; An output unit that outputs presentation information regarding at least one of state monitoring, quality control, and predictive maintenance of the object based on the spectrogram; A processing system characterized by including the above.

2. In the processing system according to Claim 1, The first vibration information is vibration information of a first axis detected by a first vibration sensor, The second vibration information is vibration information of a second axis detected by the first vibration sensor, and a processing system characterized by this.

3. In the processing system according to Claim 1, The first vibration information is vibration information of a first axis detected by a first vibration sensor, The second vibration information is vibration information of the first axis or the second axis detected by a second vibration sensor arranged at a position different from the first vibration sensor, and a processing system characterized by this.

4. In the processing system according to Claim 1, The first vibration information is a first physical quantity that is acceleration, velocity, displacement, angular acceleration, angular velocity, or angle of a first axis among the x-axis, y-axis, and z-axis, The second vibration information is the first physical quantity of a second axis different from the first axis among the x-axis, the y-axis, and the z-axis, and a processing system characterized by this.

5. In the processing system according to Claim 1, The first vibration information is a first physical quantity that is acceleration, velocity, displacement, angular acceleration, angular velocity, or angle of a first axis among the x-axis, y-axis, and z-axis, The second vibration information is a second physical quantity different from the first physical quantity among acceleration, velocity, displacement, angular acceleration, angular velocity, and angle of the first axis, and a processing system characterized by this.

6. In the processing system according to Claim 1, The output unit outputs the presentation information based on statistical information about the spectrogram, and a processing system characterized by this.

7. In the processing system according to Claim 1, The output unit outputs the presentation information based on the temporal change of the spectrogram in a specific frequency or a specific frequency range. A processing system characterized by this.

8. In the processing system according to claim 1, The arithmetic unit obtains a reference spectrogram obtained by smoothing the spectrogram in the time direction, obtains a difference spectrogram obtained by subtracting the reference spectrogram from the spectrogram, The output unit outputs the presentation information based on the difference spectrogram. A processing system characterized by this.

9. In the processing system according to claim 1, the arithmetic unit performs an arithmetic operation between a first type of first spectrogram among the three types of the cross-power spectrogram, the cross-phase spectrogram, and the coherence spectrogram of the first vibration information and the second vibration information, and a second type of second spectrogram different from the first type among the three types, The output unit outputs the presentation information based on the result of the arithmetic operation. A processing system characterized by this.

10. In the processing system according to claim 1, the acquisition unit acquires third vibration information of a third channel and fourth vibration information of a fourth channel regarding the vibration of the object, The arithmetic unit performs an arithmetic operation between a first type of first spectrogram among the three types of the cross-power spectrogram, the cross-phase spectrogram, and the coherence spectrogram of the first vibration information and the second vibration information, and a first type or a second type of second spectrogram different from the first type among the three types of the cross-power spectrogram, the cross-phase spectrogram, and the coherence spectrogram of the third vibration information and the fourth vibration information, The output unit outputs the presentation information based on the result of the arithmetic operation. A processing system characterized by this.

11. An acquisition unit that acquires first vibration information of a first channel and second vibration information of a second channel regarding the vibration of an object, An arithmetic unit that calculates a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram of the first vibration information and the second vibration information An output unit that outputs presentation information regarding at least one of condition monitoring, quality control, and predictive maintenance for the object based on the spectrogram; A program that functions as a computer.

12. Obtaining first vibration information of a first channel and second vibration information of a second channel regarding the vibration of the object, Calculating a spectrogram including at least one of a cross-power spectrogram, a cross-phase spectrogram, and a coherence spectrogram between the first vibration information and the second vibration information, Outputting presentation information regarding at least one of condition monitoring, quality control, and predictive maintenance for the object based on the spectrogram A processing method characterized by the above.

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