Analysis device, analysis system, and analysis method

Abstract

To appropriately reduce the number of points in order to perform energy-saving and highly accurate arithmetic processing.SOLUTION: An analyzer includes: a vibration sensor that detects vibration of an apparatus; an arithmetic unit that calculates an average value in each section obtained by dividing detected data of the vibration sensor for each predetermined cycle, converts a plurality of points included in each section into one point of the average value, and thereby performs vibration analysis with a reduced number of arithmetic points; and a wireless communication device that transmits processed data output by the vibration analysis by the arithmetic unit.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to an analysis device, an analysis system, and an analysis method. [Background technology]

[0002] There is known a technology that uses a vibration sensor to detect vibrations that occur during the operation of equipment in order to diagnose the presence or absence of abnormality in the equipment. Patent Document 1 discloses a technology that uses a moving average of a waveform as a variable low-pass filter (LPF) for continuously acquired vibration data for envelope processing when frequency analyzing an original impulse response waveform. Patent Document 2 discloses a technology that analyzes vibration data of a vehicle bearing to diagnose abnormalities by reducing the number of data points through decimation processing that converts the sampling frequency to a lower frequency, and then performs envelope analysis. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2005-341534 A [Patent Document 2] JP 2007-170815 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, since analysis that processes a large amount of data requires a large amount of energy, it has been difficult to perform energy-saving and highly accurate calculations. For example, in the method using a moving average as in Patent Document 1, the number of measurement points cannot be reduced, so the power required for calculations cannot be reduced. When the number of points is reduced by decimation processing and the sampling frequency is converted as in Patent Document 2, the original information obtained by high sampling is also lost.

[0005] The present disclosure aims to appropriately reduce the number of points in order to perform energy-saving and highly accurate calculation processing. [Means for solving the problem]

[0006] According to the present disclosure, an analysis device is provided that includes a vibration sensor that detects vibrations of an equipment, a calculation unit that calculates an average value for each interval divided at a predetermined period for data detected by the vibration sensor and performs vibration analysis with a reduced number of calculation points by converting multiple points included in each interval into a single point of the average value, and a wireless communication device that transmits processed data output by the vibration analysis by the calculation unit. Effect of the Invention

[0007] According to the present disclosure, it is possible to appropriately reduce the number of points to be subjected to arithmetic processing while retaining information measured at a high sampling rate. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a cross-sectional view that illustrates a schematic diagram of an analysis device according to a first embodiment. [Diagram 2] FIG. 2 is a perspective view that illustrates a schematic diagram of the thermoelectric power generation module according to the first embodiment. [Diagram 3] FIG. 3 is a block diagram showing the analysis device according to the first embodiment. [Figure 4] FIG. 4 is a flowchart showing the analysis method according to the first embodiment. [Diagram 5] FIG. 5 is a diagram showing an example of absolute value processing correction data in the analysis method according to the first embodiment. [Figure 6] FIG. 6 is a diagram showing an example of section average corrected data in the analysis method according to the first embodiment. [Figure 7] FIG. 7 is a diagram showing an example of processing data in the analysis method according to the first embodiment. [Figure 8] FIG. 8 is a flowchart showing the analysis method according to the second embodiment. [Figure 9] FIG. 9 is a diagram showing an example of processing data in the analysis method according to the second embodiment. [Figure 10] FIG. 10 is a diagram illustrating an analysis system according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings, but the present disclosure is not limited thereto. The components of the embodiments described below can be appropriately combined. In addition, some components may not be used.

[0010] In the embodiment, an XYZ orthogonal coordinate system is set, and the positional relationship of each part will be described with reference to this XYZ orthogonal coordinate system. The direction parallel to the X axis in a predetermined plane is defined as the X axis direction, the direction parallel to the Y axis perpendicular to the X axis in the predetermined plane is defined as the Y axis direction, and the direction parallel to the Z axis perpendicular to the predetermined plane is defined as the Z axis direction. The XY plane including the X axis and the Y axis is parallel to the predetermined plane.

[0011] (First embodiment) [Analysis equipment] 1 is a cross-sectional view showing a schematic diagram of an analysis device 1 according to the present embodiment. The analysis device 1 is installed in a device B. The device B is provided in an industrial facility such as a factory. An example of the device B is a rotating machine. An example of the rotating machine is a motor that operates a pump.

[0012] As shown in FIG. 1, the analysis device 1 includes a heat receiving section 2, a heat dissipation section 3, a peripheral wall section 4, a thermoelectric power generation module 5, a vibration sensor 6, a microcomputer 8, a wireless communication device 9, a heat transfer member 10, a substrate 11, and a power storage section 14.

[0013] The heat receiving part 2 is installed in the device B. The heat receiving part 2 is a plate-shaped member. The heat receiving part 2 is formed of a metal material such as aluminum or copper. The heat receiving part 2 receives heat from the device B. The heat of the heat receiving part 2 is transferred to the thermoelectric power generation module 5 via the heat transfer member 10.

[0014] The heat dissipation unit 3 faces the heat receiving unit 2 with a gap therebetween. The heat dissipation unit 3 is a plate-shaped member. The heat dissipation unit 3 is made of a metal material such as aluminum or copper. The heat dissipation unit 3 receives heat from the thermoelectric power generation module 5. The heat from the heat dissipation unit 3 is released into the atmospheric space surrounding the analysis device 1.

[0015] The heat receiving section 2 has a heat receiving surface 2A facing the surface of the equipment B, and an inner surface 2B facing in the opposite direction to the heat receiving surface 2A. The heat receiving surface 2A faces the -Z direction. The inner surface 2B faces the +Z direction. The heat receiving surface 2A and the inner surface 2B are each flat. The heat receiving surface 2A and the inner surface 2B are each parallel to the XY plane. Within the XY plane, the outer shape of the heat receiving section 2 is substantially rectangular. However, the outer shape of the heat receiving section 2 does not have to be rectangular. The outer shape of the heat receiving section 2 may be circular, elliptical, or any polygonal shape.

[0016] The heat dissipation section 3 has a heat dissipation surface 3A facing the atmospheric space, and an inner surface 3B facing in the opposite direction to the heat dissipation surface 3A. The heat dissipation surface 3A faces the +Z direction. The inner surface 3B faces the -Z direction. Each of the heat dissipation surface 3A and the inner surface 3B is flat. Each of the heat dissipation surface 3A and the inner surface 3B is parallel to the XY plane. In the XY plane, the outer shape of the heat dissipation section 3 is substantially rectangular. Note that the outer shape of the heat dissipation section 3 does not have to be rectangular. The outer shape of the heat dissipation section 3 may be circular, elliptical, or any polygonal shape.

[0017] In the XY plane, the outer shape and dimensions of the heat receiving section 2 are substantially equal to those of the heat dissipating section 3. However, the outer shape and dimensions of the heat receiving section 2 and the heat dissipating section 3 may be different from each other.

[0018] The peripheral wall portion 4 is disposed between the peripheral edge of the inner surface 2B of the heat receiving portion 2 and the peripheral edge of the inner surface 3B of the heat dissipating portion 3. The peripheral wall portion 4 connects the heat receiving portion 2 and the heat dissipating portion 3. The peripheral wall portion 4 is formed of a synthetic resin.

[0019] In the XY plane, the peripheral wall portion 4 is annular. In the XY plane, the outer shape of the peripheral wall portion 4 is substantially rectangular. The heat receiving portion 2, the heat dissipating portion 3, and the peripheral wall portion 4 define an internal space 12 of the analysis device 1. The peripheral wall portion 4 has an inner surface 4B facing the internal space 12. The inner surface 2B of the heat receiving portion 2 faces the internal space 12. The inner surface 3B of the heat dissipating portion 3 faces the internal space 12. The external space of the analysis device 1 is the atmospheric space surrounding the analysis device 1.

[0020] The heat receiving section 2, the heat dissipating section 3, and the peripheral wall section 4 function as a housing of the analysis device 1 that defines the internal space 12. In the following description, the heat receiving section 2, the heat dissipating section 3, and the peripheral wall section 4 will be collectively referred to as a housing 20 as appropriate.

[0021] A seal member 13A is disposed between the peripheral portion of the inner surface 2B of the heat receiving portion 2 and the end face on the -Z side of the peripheral wall portion 4. A seal member 13B is disposed between the peripheral portion of the inner surface 3B of the heat dissipation portion 3 and the end face on the +Z side of the peripheral wall portion 4. Each of the seal member 13A and the seal member 13B includes, for example, an O-ring. The seal member 13A is disposed in a recess provided in the peripheral portion of the inner surface 2B. The seal member 13B is disposed in a recess provided in the peripheral portion of the inner surface 3B. The seal member 13A and the seal member 13B prevent foreign matter in the external space of the analysis device 1 from entering the internal space 12.

[0022] The thermoelectric power generation module 5 generates electric power by utilizing the Seebeck effect. The device B functions as a heat source for the thermoelectric power generation module 5. The thermoelectric power generation module 5 is disposed between the heat receiving section 2 and the heat dissipating section 3. The end face 51 on the -Z side of the thermoelectric power generation module 5 is heated, and a temperature difference is provided between the end face 51 on the -Z side and the end face 52 on the +Z side of the thermoelectric power generation module 5, causing the thermoelectric power generation module 5 to generate electric power.

[0023] The end face 51 faces the -Z direction. The end face 52 faces the +Z direction. Each of the end faces 51 and 52 is flat. Each of the end faces 51 and 52 is parallel to the XY plane. In the XY plane, the outer shape of the thermoelectric power generation module 5 is substantially rectangular.

[0024] The end face 52 faces the inner surface 3B of the heat dissipation section 3. The thermoelectric power generation module 5 is fixed to the heat dissipation section 3. The heat dissipation section 3 and the thermoelectric power generation module 5 are bonded together by, for example, an adhesive.

[0025] In the example shown in FIG. 1, the thermoelectric power generation module 5 is in contact with the heat dissipation section 3, but it may be in contact with the heat receiving section 2 instead.

[0026] The vibration sensor 6 detects vibration of the device B. The vibration sensor 6 is driven by power generated by the thermoelectric power generation module 5. The vibration sensor 6 is disposed in the internal space 12. In this embodiment, the vibration sensor 6 is supported by the inner surface 2B of the heat receiving section 2.

[0027] An acceleration sensor is exemplified as the vibration sensor 6. The vibration sensor 6 may be a velocity sensor or a displacement sensor. In this embodiment, the vibration sensor 6 can detect vibration of the device B in three directions, that is, the X-axis direction, the Y-axis direction, and the Z-axis direction.

[0028] The microcomputer 8 controls the analysis device 1. The microcomputer 8 is driven by the power generated by the thermoelectric power generation module 5. The microcomputer 8 is disposed in the internal space 12. In this embodiment, the microcomputer 8 is supported by a substrate 11.

[0029] The wireless communication device 9 communicates with a management computer 100 (see FIG. 3 etc.) that is present outside the analysis device 1. The wireless communication device 9 is driven by power generated by the thermoelectric power generation module 5. The wireless communication device 9 is disposed in the internal space 12. In this embodiment, the wireless communication device 9 is supported by a substrate 11.

[0030] The heat transfer member 10 connects the heat receiving portion 2 and the thermoelectric power generation module 5. The heat transfer member 10 transfers heat from the heat receiving portion 2 to the thermoelectric power generation module 5. The heat transfer member 10 is formed of a metal material such as aluminum or copper. The heat transfer member 10 is a rod-shaped member that is long in the Z-axis direction. The heat transfer member 10 is disposed in the internal space 12.

[0031] The substrate 11 includes a control substrate. The substrate 11 is disposed in the internal space 12. The substrate 11 is connected to the heat receiving section 2 via a support member 11A. The substrate 11 is connected to the heat dissipation section 3 via a support member 11B. The substrate 11 is supported by the support members 11A and 11B so as to be spaced apart from the heat receiving section 2 and the heat dissipation section 3, respectively.

[0032] The power storage unit 14 stores the power generated by the thermoelectric power generation module 5. Examples of the power storage unit 14 include a capacitor or a secondary battery.

[0033] [Thermoelectric power generation module] FIG. 2 is a perspective view that shows a schematic diagram of a thermoelectric power generation module 5 according to this embodiment. As shown in FIG. 2, the thermoelectric power generation module 5 has a p-type thermoelectric semiconductor element 5P, an n-type thermoelectric semiconductor element 5N, a first electrode 53, a second electrode 54, a first substrate 51S, and a second substrate 52S. In the XY plane, the p-type thermoelectric semiconductor elements 5P and the n-type thermoelectric semiconductor elements 5N are alternately arranged. The first electrode 53 is connected to each of the p-type thermoelectric semiconductor elements 5P and the n-type thermoelectric semiconductor elements 5N. The second electrode 54 is connected to each of the p-type thermoelectric semiconductor elements 5P and the n-type thermoelectric semiconductor elements 5N. The lower surface of the p-type thermoelectric semiconductor element 5P and the lower surface of the n-type thermoelectric semiconductor element 5N are connected to the first electrode 53. The upper surface of the p-type thermoelectric semiconductor element 5P and the upper surface of the n-type thermoelectric semiconductor element 5N are connected to the second electrode 54. The first electrode 53 is connected to the first substrate 51S. The second electrode 54 is connected to the second substrate 52S.

[0034] Each of the p-type thermoelectric semiconductor element 5P and the n-type thermoelectric semiconductor element 5N includes, for example, a BiTe-based thermoelectric material. Each of the first substrate 51S and the second substrate 52S is formed of an electrically insulating material such as ceramics or polyimide.

[0035] The first substrate 51S has an end surface 51. The second substrate 52S has an end surface 52. When the first substrate 51S is heated, a temperature difference is provided between the +Z side end and the -Z side end of each of the p-type thermoelectric semiconductor element 5P and the n-type thermoelectric semiconductor element 5N. When a temperature difference is provided between the +Z side end and the -Z side end of the p-type thermoelectric semiconductor element 5P, holes move in the p-type thermoelectric semiconductor element 5P. When a temperature difference is provided between the +Z side end and the -Z side end of the n-type thermoelectric semiconductor element 5N, electrons move in the n-type thermoelectric semiconductor element 5N. The p-type thermoelectric semiconductor element 5P and the n-type thermoelectric semiconductor element 5N are connected via a first electrode 53 and a second electrode 54. A potential difference is generated between the first electrode 53 and the second electrode 54 by the holes and electrons. When a potential difference is generated between the first electrode 53 and the second electrode 54, the thermoelectric power generation module 5 generates power. A lead wire 55 is connected to the first electrode 53. The thermoelectric power generation module 5 outputs power via lead wires 55 .

[0036] [Microcomputer] Fig. 3 is a block diagram showing the analysis device 1 according to this embodiment. As shown in Fig. 3, the thermoelectric power generation module 5, the power storage unit 14, the vibration sensor 6, the microcomputer 8, and the wireless communication device 9 are contained in one housing 20.

[0037] The microcomputer 8 includes a setting unit 81, a detection data acquisition unit 82, a calculation unit 83, and a communication control unit 84.

[0038] The setting unit 81 sets a measurement time for measuring the vibration of the device B by the vibration sensor 6. The measurement time may be set by an operator via wireless communication from the management computer 100, for example. Note that the sampling frequency may be set by an operator via wireless communication from the management computer 100, and in this case, the setting unit 81 sets the measurement time based on the sampling frequency.

[0039] The detection data acquisition unit 82 acquires detection data of the vibration sensor 6 at the measurement time and sampling frequency set in the setting unit 81. The detection data of the vibration sensor 6 includes a vibration waveform. The detection data acquisition unit 82 acquires detection data at the measurement time and sampling frequency set by the setting unit 81.

[0040] The calculation unit 83 controls the microcomputer 8 to execute a program stored in advance. The calculation unit 83 performs calculation processing based on the detection data of the vibration sensor 6 acquired by the detection data acquisition unit 82, and outputs the processed data. The processed data refers to data generated by processing the detection data. The calculation unit 83 can process the detection data of the vibration sensor 6 based on a vibration analysis method such as a fast Fourier transform (FFT), and output the processed data.

[0041] The calculation unit 83 performs absolute value processing on the vibration waveform (acceleration data) acquired by the detection data acquisition unit 82 to convert each point into an absolute value, and generates absolute value processing correction data. The absolute value processing refers to processing of squaring the value of each point and calculating the square root. The absolute value processing may be processing of only calculating the square of the value of each point. Before performing the absolute value processing, the calculation unit 83 may perform, for example, high pass filter (HPF) processing as a band pass filter (BPF).

[0042] The number of calculation points after reduction may be set by an operator via wireless communication from the management computer 100. Note that the maximum value of the necessary frequency bandwidth or the sampling frequency after the point reduction may be set by an operator via wireless communication from the management computer 100, and in this case, the setting unit 81 sets the number of calculation points after reduction based on the maximum value of the necessary frequency bandwidth or the sampling frequency after the point reduction.

[0043] The calculation unit 83 divides the absolute value processing correction data into intervals for each predetermined period based on the set number of calculation points after reduction. The calculation unit 83 calculates the average value in each interval for the absolute value processing correction data, performs interval averaging processing to convert multiple points included in each interval into a single point of the average value, and generates interval average correction data. The calculation unit 83 performs fast Fourier transform analysis on the interval average correction data, and calculates the power spectral density [(m / s 2 ) 2 The calculation unit 83 may further convert the power spectral density into decibels and output the sensitivity [dB] for each frequency [Hz] as the processed data.

[0044] The processing data generated by the calculation unit 83 may include at least one of the peak value, the effective value, and the vibration frequency of the device B calculated from the detection data of the vibration sensor 6, for example.

[0045] The calculation unit 83 may process the detection data of the vibration sensor 6 to calculate the peak value of the vibration of the device B. The peak value of the vibration includes a maximum value and a minimum value of the vibration. The peak value of the vibration may be a peak value in the entire range of the vibration waveform, or may be a peak value in each of a plurality of frequency ranges. The peak value of the vibration may be a peak value of acceleration, a peak value of velocity, or a peak value of displacement.

[0046] The calculation unit 83 may process the detection data of the vibration sensor 6 to calculate the root mean square value (RMS) of the vibration of the device B. The calculation unit 83 may also divide the entire range of the vibration waveform detected by the vibration sensor 6 into a plurality of frequency ranges and calculate the effective value for each of the plurality of frequency ranges. The effective value of the vibration may be the effective value of the acceleration, the effective value of the velocity, or the effective value of the displacement.

[0047] The calculation unit 83 may process the detection data of the vibration sensor 6 to calculate the vibration frequency of the device B. The calculation unit 83 may process the detection data of the vibration sensor 6 to calculate an overall value of the vibration. The overall value refers to the sum of the power spectrum of the entire range of frequencies that are the subject of the fast Fourier transform analysis.

[0048] The calculation unit 83 may process the detection data of the vibration sensor 6 to calculate a crest factor (CF) of the device B. The crest factor is the ratio of the peak value to the effective value (peak value / effective value).

[0049] The communication control unit 84 controls the wireless communication device 9 to communicate with the management computer 100. When the wireless communication device 9 receives setting data for setting the measurement time, sampling frequency, number of calculation points after reduction, maximum value of necessary frequency bandwidth, sampling frequency after point reduction, etc. from the management computer 100, the communication control unit 84 outputs the received setting data to the calculation unit 83. The calculation unit 83 causes the setting unit 81 to set the measurement time and sampling frequency based on the acquired setting data of the measurement time or sampling frequency. The calculation unit 83 also sets the number of calculation points after reduction based on the setting data of the number of calculation points after reduction, maximum value of necessary frequency bandwidth, or sampling frequency after point reduction.

[0050] Furthermore, the communication control unit 84 controls the wireless communication device 9 so that the detection data of the vibration sensor 6 acquired by the detection data acquisition unit 82 is transmitted to the management computer 100. The wireless communication device 9 transmits the detection data of the vibration sensor 6 acquired by the detection data acquisition unit 82 to the management computer 100.

[0051] Furthermore, when the calculation unit 83 outputs the processing data, the communication control unit 84 controls the wireless communication device 9 so that the processing data is transmitted to the management computer 100. The wireless communication device 9 transmits the processing data calculated by the calculation unit 83 to the management computer 100.

[0052] [Analysis method] FIG. 4 is a flowchart showing the analysis method according to this embodiment. In this embodiment, the equipment B in which the analysis device 1 is installed is a motor, which is a type of rotating machine. The motor operates a pump. In the analysis method according to this embodiment, in order to diagnose the presence or absence of damage to the motor bearings, the power spectrum density [(m / s 2 ) 2 / Hz] is output as processed data.

[0053] In the analysis device 1, the setting unit 81 sets a measurement time for measuring the vibration of the device B by the vibration sensor 6 based on setting data set, for example, via wireless communication from the management computer 100. The setting unit 81 sets a sampling frequency based on the number of sampling points determined by the memory capacity of the microcomputer 8 and the set measurement time (step S11).

[0054] The detection data acquisition unit 82 acquires, as detection data, acceleration data for the number of sampling points of the measurement time and sampling frequency (ODR) set by the setting unit 81 from the vibration sensor 6, that is, raw data of the vibration waveform (step S12).

[0055] The calculation unit 83 calculates the absolute value of each point of the acceleration data acquired by the detection data acquisition unit 82 in step S12, and performs absolute value processing to convert each point of the acceleration data into an absolute value (step S13). The calculation unit 83 generates absolute value processing correction data by the absolute value processing.

[0056] 5 is a diagram showing an example of absolute value processing correction data in the analysis method according to the present embodiment. The vertical axis of FIG. 5 is the acceleration [m / s 2 ], and the horizontal axis represents time [msec].

[0057] As shown in Fig. 5, the value of each point of the acceleration data acquired in step S12 shown in Fig. 4 is converted to an absolute value by absolute value processing. In the example shown in Fig. 5, in the absolute value processing by the calculation unit 83, the value of each point of the acceleration data acquired in step S12 shown in Fig. 4 is squared to calculate the square root. This allows the calculation unit 83 to generate absolute value processed correction data of the vibration waveform as shown by line L1a in Fig. 5.

[0058] For example, based on the setting data set via wireless communication from the management computer 100, the calculation unit 83 sets the number of calculation points after reduction to be reduced before performing the FFT analysis (step S14). In this embodiment, for example, the number of calculation points is set to 1024 points.

[0059] The calculation unit 83 divides the absolute value processing correction data generated in step S13 into intervals of a predetermined period based on the number of calculation points after reduction set in step S14. In this embodiment, the number of sampling points during measurement is 8192 points, and the number of calculation points after reduction is 1024 points, so the data is divided into intervals of 8 points.

[0060] The calculation unit 83 calculates twice the average value in each section divided for each predetermined period for the absolute value processing correction data generated in step S13, and performs section averaging processing to convert multiple points included in each section into the average value of one point (step S15). The calculation unit 83 generates section average correction data by the section averaging processing.

[0061] That is, in this embodiment, first, the average value of eight points in each section is calculated. Next, section average correction data is generated, which is a waveform in which the average value is associated with the time corresponding to the section. The time corresponding to the section is, for example, the time corresponding to the first point among multiple points included in the section, or the time at the center of the section. This generates section average correction data in which the number of points is reduced to 1 / 8 of the absolute value processing correction data.

[0062] 6 is a diagram showing an example of section average correction data in the analysis method according to the present embodiment. The vertical axis of FIG. 6 represents acceleration [m / s 2 ], and the horizontal axis represents time [msec].

[0063] As shown by line L2a in Fig. 6, each point of the absolute value processing correction data generated in step S13 shown in Fig. 4 is converted into one point averaged over each section divided for each predetermined period. This allows the calculation unit 83 to generate section average correction data of the vibration waveform as shown by line L2a in Fig. 6. That is, the number of points of the section average correction data is (1 point) / (original number of points included in each section) times the number of calculation points of the acceleration data and the absolute value processing correction data, and in this embodiment, it is 1 / 8 times.

[0064] Line L2b in Fig. 6 is comparison data generated by performing finite impulse response (FIR) filter processing as low-pass filter processing on the absolute value processing correction data instead of steps S14 and S15 shown in Fig. 4. Note that the number of calculation points of the comparison data is not reduced from the acceleration data and the absolute value processing correction data.

[0065] As shown in FIG. 6, line L2a of the section average corrected data of this embodiment in which the number of calculation points is reduced can reproduce the waveform characteristics of line L2b of the comparison data obtained by low-pass filtering without reducing the number of calculation points.

[0066] The calculation unit 83 performs an FFT analysis on the section average correction data generated in step S15 (step S16). The calculation unit 83 calculates the power spectrum density [(m / s 2 ) 2 / Hz] is generated. The calculation unit 83 causes the generated distribution data of the power spectrum density for each frequency to be transmitted to the wireless communication device 9 as processing data. The wireless communication device 9 transmits the processing data to the management computer 100 (step S17).

[0067] FIG. 7 is a diagram showing an example of processed data in the analysis method according to the present embodiment. The vertical axis of FIG. 7 is the power spectral density [(m / s 2 ) 2 / Hz], and the horizontal axis represents frequency [Hz].

[0068] As shown by line L3a in Fig. 7, distribution data of power spectrum density for each frequency is generated by FFT analysis from the section average corrected data generated in step S15 shown in Fig. 4. That is, the calculation unit 83 performs FFT analysis on the section average corrected data in which the number of calculation points is reduced from the acceleration data and the absolute value processing corrected data by the section average correction process.

[0069] Line L3b in Fig. 7 is comparison data of the distribution of power spectrum density for each frequency generated by FFT analysis from the comparison data shown in line L2b in Fig. 6. Note that the number of calculation points of the comparison data is not reduced from the acceleration data and the absolute value processing correction data.

[0070] As shown in FIG. 7, line L3a of the distribution data of power spectral density for each frequency in this embodiment in which the number of calculation points is reduced can reproduce the waveform characteristics of line L3b of the comparison data in which the number of calculation points is not reduced and low-pass filter processing is performed before the FFT analysis.

[0071] Based on the transmitted processing data, the management computer 100 can monitor and manage the state of the device B. Based on the transmitted processing data, the management computer 100 can diagnose whether or not there is an abnormality in the device B.

[0072] [effect] As described above, according to this embodiment, the vibration sensor 6 is installed in the device B. The detection data of the vibration sensor 6 is output to the microcomputer 8. The calculation unit 83 of the microcomputer 8 calculates the average value of the detection data of the vibration sensor 6 in each section divided at a predetermined period. The calculation unit 83 performs vibration analysis with a reduced number of calculation points by converting a plurality of points included in each section into one point of the average value. In this way, the calculation load can be suppressed by appropriately reducing the number of calculation points to be calculated using the analysis method of this embodiment, so that it is possible to output an analysis result that maintains necessary and sufficient accuracy even with low power consumption.

[0073] The processed data output by the calculation unit 83 in the vibration analysis is transmitted from the wireless communication device 9 to the management computer 100. Therefore, the management computer 100 can properly diagnose the device B based on the analysis result calculated with an appropriately reduced number of calculation points.

[0074] The calculation unit 83 converts each point of the detection data of the vibration sensor 6 into an absolute value before reducing the number of calculation points. That is, the calculation unit 83 converts the acceleration data, which contains both positive and negative values, into data with only positive values. This allows the calculation unit 83 to calculate the average value in each section from the absolute value, thereby suppressing errors when reducing the number of calculation points.

[0075] The microcomputer 8 of the analysis device 1 includes a setting unit 81 that sets the sampling frequency for acquiring detection data based on the number of sampling points determined by the memory capacity and the set measurement time. This allows the sampling frequency to be set to the maximum value within a range that satisfies the memory capacity restrictions and the required measurement time conditions. In other words, after measurement at a high frequency, the number of calculation points to be processed by the analysis method of this embodiment can be appropriately reduced, so that analysis results that maintain sufficient accuracy even with low power consumption while suppressing the calculation load can be output.

[0076] Second embodiment A second embodiment will be described. In the following description, the same or equivalent components as those in the first embodiment described above are denoted by the same reference numerals, and their description will be simplified or omitted. The physical configuration of the analysis device 1 according to the second embodiment is the same as that of the first embodiment, and is characterized by the processing by the calculation unit 83.

[0077] In this embodiment, the calculation unit 83 performs an integration process for integrating the acceleration to obtain the velocity on the vibration waveform (acceleration data) acquired by the detection data acquisition unit 82, and generates integration process correction data. Before performing the integration process, the calculation unit 83 may perform, for example, high-pass filter processing as a band-pass filter.

[0078] The calculation unit 83 performs an extraction process for the integral processing correction data, which extracts speed data for each predetermined period based on the set number of calculation points after reduction, and generates extracted correction data. In the extraction process, points other than the first point, for example, are deleted from among the multiple points included in each section. If extraction is performed for each predetermined period, the extracted point may be any point in each section.

[0079] The calculation unit 83 performs a fast Fourier transform analysis on the extracted correction data, and calculates the power spectrum density [(m / s) 2 The calculation unit 83 may further convert the power spectral density into decibels and output the sensitivity [dB] for each frequency [Hz] as the processed data.

[0080] [Analysis method] Fig. 8 is a flowchart showing the analysis method according to this embodiment. In this embodiment, the equipment B on which the analysis device 1 is installed is a motor, which is a type of rotating machine. The motor operates a pump. In the analysis method according to this embodiment, in order to diagnose the installation condition of the rotating machine, the power spectrum density [(m / s) / Hz] for each frequency [Hz] is output as processing data.

[0081] The processing from step S21 to step S22 is similar to the processing from step S11 to step S12 shown in FIG. 4 in the first embodiment, and therefore the description thereof will be omitted.

[0082] The calculation unit 83 performs an integration process for integrating the acceleration of the acceleration data acquired by the detection data acquisition unit 82 in step S22 to acquire speed data (step S23). The calculation unit 83 generates integration process data through the integration process.

[0083] The process of step S25 is similar to the process of step S15 shown in FIG. 4 in the first embodiment, and therefore a description thereof will be omitted.

[0084] The calculation unit 83 performs an extraction process for extracting speed data for each predetermined period based on the number of calculation points after reduction set in step S24 from the integral processing correction data generated in step S23 (step S25). The calculation unit 83 generates extracted correction data through the extraction process.

[0085] That is, in this embodiment, first, the extracted correction data is generated as a waveform obtained by extracting only one point of the speed data from the eight points of the speed data in each section. This generates the extracted correction data with the number of points reduced to 1 / 8 from the integral processing correction data.

[0086] The calculation unit 83 performs FFT analysis on the extracted and corrected data generated in step S15 (step S26). The calculation unit 83 calculates the power spectrum density [(m / s) 2 / Hz] is generated. The calculation unit 83 causes the wireless communication device 9 to transmit the generated distribution data of the power spectrum density for each frequency as processing data. The wireless communication device 9 transmits the processing data to the management computer 100 (step S27).

[0087] FIG. 9 is a diagram showing an example of processed data in the analysis method according to this embodiment. The vertical axis of FIG. 9 indicates sensitivity [dB], and the horizontal axis indicates frequency [Hz]. The processed data shown in FIG. 9 shows the frequency dependency of the effective value calculated from the velocity calculated from the acceleration by the calculation unit 83 using the analysis method shown in FIG. 8. Line L4a shows the effective value data obtained by converting the acceleration data to a lower sampling frequency by decimation processing and then calculating the velocity. Line L4b shows the effective value data obtained by reducing the number of points after calculating the velocity from the acceleration.

[0088] As shown in FIG. 9, line L4b, which indicates the sensitivity calculated by the analysis method of this embodiment, exhibits good characteristics, but line L4a has a large deviation due to poor integration precision from acceleration to velocity.

[0089] [effect] As described above, according to this embodiment, the vibration sensor 6 is installed in the device B, as in the first embodiment. The detection data of the vibration sensor 6 is output to the microcomputer 8. The calculation unit 83 of the microcomputer 8 integrates the acceleration data of the detection data of the vibration sensor 6 to obtain speed data, and then performs vibration analysis with the reduced number of calculation points by extracting the speed data for each predetermined period. In this way, by appropriately reducing the number of calculation points for calculation processing using the analysis method of this embodiment, it is possible to output analysis results that maintain necessary and sufficient accuracy even with low power consumption.

[0090] The processed data output by the calculation unit 83 in the vibration analysis is transmitted from the wireless communication device 9 to the management computer 100. Therefore, the management computer 100 can properly diagnose the device B based on the analysis result calculated with an appropriately reduced number of calculation points.

[0091] Third embodiment A third embodiment will now be described. In the following description, the same or equivalent components as those in the first and second embodiments described above are denoted by the same reference numerals, and the description thereof will be simplified or omitted.

[0092] [Analysis system] FIG. 10 is a diagram showing a schematic diagram of an analysis system 200 according to the present embodiment. As shown in FIG. 10, the analysis system 200 includes a plurality of analysis devices 1 installed in equipment B, a communication device 210, and a repeater 220. A plurality of pieces of equipment B are provided in an industrial facility. As described above, an example of equipment B is a motor that operates a pump. Equipment B may be installed underground. Equipment B generates heat when it operates. Equipment B functions as a heat source for the analysis devices 1.

[0093] The communication device 210 receives the detection data of the vibration sensor 6 and the processed data output by the calculation unit 83 transmitted from each of the multiple analysis devices 1 via the repeater 220, and transmits them to the management computer 100. The communication device 210 processes the detection data and the processed data transmitted from each of the multiple analysis devices 1 into a predetermined format, for example, and then transmits them to the management computer 100. The detection data and the processed data from each of the multiple analysis devices 1 are aggregated by the communication device 210 and then transmitted to the management computer 100. The communication device 210 and the management computer 100 may communicate wirelessly or via wired communication.

[0094] The repeater 220 relays communication between the analysis device 1 and the communication device 210. A plurality of repeaters 220 are provided. The repeaters 220 and the communication device 210 communicate wirelessly.

[0095] The management computer 100 can monitor and manage the states of the multiple devices B based on the detection data of the vibration sensors 6 transmitted from each of the multiple analysis devices 1 and the processed data output by the calculation unit 83. The management computer 100 can diagnose whether or not there is an abnormality in the device B based on the detection data of the vibration sensors 6 transmitted from each of the multiple analysis devices 1 and the processed data output by the calculation unit 83.

[0096] The multiple analysis devices 1 can transmit detection data and processing data independently. That is, each analysis device 1 can transmit detection data and processing data without being affected by other analysis devices 1.

[0097] For example, if equipment B and analysis device 1 are located underground and communication device 210 and management computer 100 are located above ground, a repeater 220 is installed so that the detection data and processing data sent from analysis device 1 can be smoothly transmitted to management computer 100.

[0098] [effect] As described above, in this embodiment, the analysis system 200 includes a plurality of analysis devices 1 installed in each of the plurality of devices B, and a communication device 210 that receives processing data transmitted from each of the plurality of analysis devices 1 and transmits the processing data to the management computer 100. Therefore, the management computer 100 can monitor and manage the status of the plurality of devices B, and diagnose the presence or absence of abnormalities in the plurality of devices B.

[0099] [Other embodiments] In the above-described embodiment, the management computer 100 may be configured as one computer, or may be configured as multiple computers.

[0100] In the above-described embodiment, the thermoelectric power generation module 5, the vibration sensor 6, the microcomputer 8, and the wireless communication device 9 are accommodated in one housing 20. The thermoelectric power generation module 5 may be accommodated in a first housing, and the vibration sensor 6, the microcomputer 8, and the wireless communication device 9 may be accommodated in a second housing. The first housing and the second housing are separate housings. The power storage unit 14 may be disposed between the first housing and the second housing.

[0101] In the above-described embodiment, the function of the calculation unit 83 may be provided in the management computer 100. The detection data of the vibration sensor 6 may be transmitted to the management computer 100 via the wireless communication device 9, and the management computer 100 may output the processed data. Also, the function of the management computer 100 may be provided in the microcomputer 8. For example, the calculation unit 83 may diagnose the presence or absence of an abnormality. [Explanation of symbols]

[0102] 1...analysis device, 2...heat receiving portion, 2A...heat receiving surface, 2B...inner surface, 3...heat dissipation portion, 3A...heat dissipation surface, 3B...inner surface, 4...peripheral wall portion, 4B...inner surface, 5...thermoelectric power generation module, 5N...n-type thermoelectric semiconductor element, 5P...p-type thermoelectric semiconductor element, 6...vibration sensor, 8...microcomputer, 9...wireless communication device, 10...heat transfer member, 11...substrate, 11A...support member, 11B...support member, 12...internal space, 13A ...sealing member, 13B...sealing member, 14...storage unit, 20...housing, 51...end surface, 51S...first board, 52...end surface, 52S...second board, 53...first electrode, 54...second electrode, 55...lead wire, 81...setting unit, 82...detection data acquisition unit, 83...calculation unit, 84...communication control unit, 100...management computer, 200...analysis system, 210...communication device, 220...repeater, B...equipment.

Claims

1. A vibration sensor that detects vibration of the device; a calculation unit that divides a predetermined measurement time for the detection data of the vibration sensor into a plurality of intervals each having a predetermined period, calculates an average value of a plurality of points included in each interval of the detection data, and performs vibration analysis using a reduced number of calculation points by converting the plurality of points into a single point of the average value; and a wireless communication device for transmitting processed data output by the vibration analysis performed by the calculation unit. Analysis device.

2. The calculation unit converts each point of the detection data of the vibration sensor into an absolute value before reducing the number of calculation points. The analysis device according to claim 1 .

3. The calculation unit performs vibration analysis with a reduced number of calculation points by integrating acceleration data from the detection data of the vibration sensor to obtain velocity data, and then extracting the velocity data for each predetermined period. The analysis device according to claim 1 .

4. Equipped with a thermoelectric power generation module, The vibration sensor is driven by the power generated by the thermoelectric power generation module. The analysis device according to claim 1 .

5. An analysis device according to any one of claims 1 to 4, a management computer that receives the processing data transmitted from the analysis device and diagnoses the device; Analysis system.

6. Obtaining detection data from a vibration sensor that detects vibration of an equipment; Dividing a predetermined measurement time for the detection data of the vibration sensor into a plurality of intervals each having a predetermined period, calculating an average value of a plurality of points included in each interval of the detection data, and converting the plurality of points into a single point of the average value, thereby performing a vibration analysis with a reduced number of calculation points; and transmitting processed data output from the vibration analysis. Analysis method.

7. The method includes integrating acceleration data to obtain velocity data from the detection data of the vibration sensor, and then performing vibration analysis with a reduced number of calculation points by extracting velocity data for each predetermined period. The analysis method according to claim 6.

8. The vibration sensor is driven by power generated by a thermoelectric power generation module. The analysis method according to claim 6 or 7.

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