Signal processing method, signal processing apparatus, signal processing system, and signal processing program

Abstract

To provide a signal processing method which enables computation of an index that allows a user to determine the presence or absence of anomaly even when an unexpected abnormality occurs in the vibration state.SOLUTION: There is provided a signal processing method comprising: generating a first Lissajous figure based on a physical quantity generated by vibration in a first period; generating, for each integer i between 2 and N inclusive, where N is an integer of 2 or greater, an i-th Lissajous figure based on a physical quantity generated by a vibration in an i-th period; and calculating an (i-1)th degree of difference as a degree of difference between the first Lissajous figure and the i-th Lissajous figure.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a signal processing method, a signal processing device, a signal processing system, and a signal processing program. [Background technology]

[0002] Patent Document 1 describes an abnormality diagnosis device for a bearing part of a rotating equipment, which includes a vibration detection means for detecting vibrations at predetermined positions on at least two axes that are orthogonal to each other on the same plane centered on the axis of the rotating equipment and outputting a vibration waveform signal, a Lissajous waveform diagram generation means for generating a Lissajous waveform diagram based on both vibration waveform signals, a reference Lissajous waveform diagram setting means for setting and storing in advance a plurality of reference Lissajous waveform diagrams that are each assumed based on the cause of each abnormality, and an abnormality cause determination means for comparing the Lissajous waveform diagram with each reference Lissajous waveform diagram to determine and output the cause of the abnormality. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2000-258305 Summary of the Invention [Problem to be solved by the invention]

[0004] The method described in Patent Document 1 requires the time and effort of preparing in advance multiple reference Lissajous waveform diagrams that are each assumed to be the cause of each abnormality, and also determines the cause of the abnormality by comparing the Lissajous waveform diagram with each reference Lissajous waveform diagram and determining which one is most similar, making it difficult to determine whether or not an abnormality exists when an unexpected abnormality occurs. [Means for solving the problem]

[0005] One aspect of the signal processing method according to the present invention is to generating a first Lissajous figure based on a physical quantity caused by the vibration during a first period; Let N be an integer greater than or equal to 2, and for each integer i greater than or equal to 2 and less than or equal to N, generating an i-th Lissajous figure based on a physical quantity caused by the vibration in the i-th period; The (i-1)th degree of difference, which is the degree of difference between the first Lissajous figure and the ith Lissajous figure, is calculated.

[0006] One aspect of the signal processing device according to the present invention is a Lissajous figure generating circuit that generates a first Lissajous figure based on a physical quantity caused by vibration in a first period, and generates an i-th Lissajous figure for each integer i between 2 and N, inclusive, based on the physical quantity caused by vibration in an i-th period, where N is an integer of 2 or more; a dissimilarity calculation circuit that calculates an (i-1)th dissimilarity between the first Lissajous figure and the i-th Lissajous figure; Includes:

[0007] One aspect of the signal processing system according to the present invention is An aspect of the signal processing device; at least one physical quantity sensor that detects the physical quantity generated by the vibration in each of the first to Nth periods; Equipped with.

[0008] One aspect of the signal processing program according to the present invention is generating a first Lissajous figure based on a physical quantity caused by the vibration during a first period; Let N be an integer greater than or equal to 2, and for each integer i greater than or equal to 2 and less than or equal to N, generating an i-th Lissajous figure based on a physical quantity caused by the vibration in the i-th period; The computer is caused to calculate the (i-1)th degree of difference, which is the degree of difference between the first Lissajous figure and the i-th Lissajous figure. [Brief explanation of the drawings]

[0009] [Figure 1]FIG. 3 is a flowchart showing the procedure of the signal processing method according to the first embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of the detailed procedure of step S60 in FIG. 1. [Figure 3] FIG. 10 is a diagram illustrating a method for calculating the dissimilarity. [Figure 4] FIG. 1 is a diagram showing an example of the configuration of a signal processing device that executes a signal processing method according to a first embodiment. [Figure 5] FIG. 10 is a flowchart showing the procedure of a signal processing method according to a second embodiment. [Figure 6] A graph of the transition information. [Figure 7] FIG. 10 is a diagram showing an example of the configuration of a signal processing device that executes a signal processing method according to a second embodiment. [Figure 8] FIG. 10 is a flowchart showing the procedure of a signal processing method according to a third embodiment. [Figure 9] FIG. 10 is a diagram showing an example of interpolation of a Lissajous figure. [Figure 10] FIG. 10 is a diagram showing an example of the configuration of a signal processing device that executes a signal processing method according to a third embodiment. [Figure 11] FIG. 10 is a flowchart showing the procedure of a signal processing method according to a fourth embodiment. [Figure 12] FIG. 10 is a diagram showing an example of the configuration of a signal processing device that executes a signal processing method according to a fourth embodiment. [Figure 13] FIG. 1 is a diagram showing an example of the configuration of a signal processing system according to an embodiment of the present invention. [Figure 14] FIG. 2 is a schematic perspective view showing the configuration of a vacuum pump. [Figure 15] FIG. 2 is a schematic cross-sectional side view showing the internal structure of a vacuum pump. [Figure 16] FIG. 2 is a schematic cross-sectional plan view showing the internal structure of a vacuum pump. DETAILED DESCRIPTION OF THE INVENTION

[0010] Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Note that the embodiments described below do not unduly limit the content of the present invention as defined in the claims. Furthermore, not all of the configurations described below are necessarily essential components of the present invention.

[0011] 1. Signal processing method and signal processing device 1-1. First embodiment 1-1-1.Signal processing method 1 is a flowchart showing the steps of a signal processing method according to the first embodiment. The signal processing method according to the first embodiment is executed, for example, by a signal processing device 100 operating in accordance with a signal processing program. An example of the configuration of the signal processing device 100 that executes the signal processing method according to the first embodiment will be described later.

[0012] 1, first, in step S10, the signal processing device 100 acquires measurement data for a first period. The measurement data is data based on signals output from a physical quantity sensor that detects physical quantities on multiple axes caused by vibrations of an object. The measurement data may be time-series data of digital signals output from the physical quantity sensor, or time-series data of digital signals obtained by converting analog signals output from the physical quantity sensor by an analog front-end.

[0013] The first period is a period of any length, and the measurement data for the first period is time-series data of physical quantities on multiple axes detected by a physical quantity sensor during the first period. The physical quantity sensor may detect the physical quantities multiple times during the first period and output the measurement data for the multiple times, and the signal processing device 100 may acquire the measurement data for the multiple times. For example, if the first period is a one-day period and the physical quantity sensor detects the physical quantities six times every four hours, the signal processing device 100 may acquire the measurement data for the six times.

[0014] The multiple axes along which the physical quantity sensor detects the physical quantity may be, for example, two axes, three axes, or more than three axes. The multiple axes preferably intersect each other and are perpendicular to each other. The physical quantity sensor may be, for example, a sensor using a MEMS resonator or a sensor using a quartz resonator. MEMS is an abbreviation for Micro Electro Mechanical Systems. Furthermore, the physical quantity sensor may be built into a single device such as an IMU, or at least one of the multiple sensors that detect the physical quantity of each axis may be physically separated from the other sensors. IMU is an abbreviation for Inertial Measurement Unit.

[0015] The object is an object to be subjected to signal processing, and its type is not particularly limited, and may be, for example, various devices such as electric motors or motors having a rotating mechanism or a vibrating mechanism, structures such as bridges or buildings that vibrate due to external forces, or electrical circuits that generate periodic signals. The type of physical quantity generated by the vibration of the object is not particularly limited, and for example, the physical quantity may be acceleration, angular velocity, velocity, displacement, pressure, current, voltage, etc.

[0016] Next, in step S20, the signal processing device 100 generates a first Lissajous figure based on the measurement data for the first period acquired in step S10. That is, in step S20, the signal processing device 100 generates the first Lissajous figure based on physical quantities caused by vibration of the object during the first period. For example, if a physical quantity sensor detects physical quantities on the X-axis and Y-axis, and the measurement data for the first period includes time-series data of the physical quantity on the X-axis and time-series data of the physical quantity on the Y-axis, the signal processing device 100 may generate a Lissajous figure on a two-dimensional plane with the first axis as the X-axis and the second axis as the Y-axis. Furthermore, when the physical quantity sensor detects physical quantities on the X-axis, Y-axis, and Z-axis, and the measurement data for a first period includes time series data of the physical quantity on the X-axis, time series data of the physical quantity on the Y-axis, and time series data of the physical quantity on the Z-axis, the signal processing device 100 may generate a Lissajous figure in a three-dimensional space with the first axis as the X-axis, the second axis as the Y-axis, and the third axis as the Z-axis. In this case, the signal processing device 100 may generate at least one of a Lissajous figure on a two-dimensional plane with the first axis as the X-axis and the second axis as the Y-axis, a Lissajous figure on a two-dimensional plane with the first axis as the Y-axis and the second axis as the Z-axis, and a Lissajous figure on a two-dimensional plane with the first axis as the Z-axis and the second axis as the X-axis.

[0017] Furthermore, when the signal processing device 100 acquires multiple sets of measurement data in step S10, it may generate multiple Lissajous figures based on the multiple sets of measurement data and average the multiple Lissajous figures to generate the first Lissajous figure in step S20. For example, if the first period is a one-day period and the physical quantity sensor detects the physical quantity six times every four hours, the signal processing device 100 may generate six Lissajous figures based on the six sets of measurement data and average the six Lissajous figures to generate the first Lissajous figure.

[0018] Next, in step S30, the signal processing device 100 sets the integer i to 2, and in step S40, acquires measurement data for the i-th period. The measurement data is data based on signals output from a physical quantity sensor that detects physical quantities on multiple axes caused by vibrations of the object. The measurement data may be time-series data of digital signals output from the physical quantity sensor, or time-series data of digital signals obtained by converting analog signals output from the physical quantity sensor by an analog front end.

[0019] The i-th period is a period of any length, and the measurement data for the i-th period is time-series data of physical quantities on multiple axes detected by a physical quantity sensor during the i-th period. The physical quantity sensor may detect the physical quantities multiple times during the i-th period and output the measurement data for the multiple times, and the signal processing device 100 may acquire the measurement data for the multiple times. For example, if the i-th period is a one-day period and the physical quantity sensor detects the physical quantities six times every four hours, the signal processing device 100 may acquire the measurement data for the six times.

[0020] The multiple axes along which the physical quantity sensor detects the physical quantity may be, for example, two axes, three axes, or more than three axes. The multiple axes preferably intersect each other and are perpendicular to each other. The physical quantity sensor may be, for example, a sensor using a MEMS resonator or a sensor using a quartz crystal resonator. Furthermore, the physical quantity sensor may be built into a single device such as an IMU, or at least one of the multiple sensors detecting the physical quantity of each axis may be physically separated from the other sensors.

[0021] In this embodiment, the physical quantity sensor that outputs measurement data in the first period and the physical quantity sensor that outputs measurement data in the i-th period may be the same or different. In the latter case, it is sufficient that the two physical quantity sensors detect the same type of physical quantity. Furthermore, the object whose physical quantity is detected in the first period and the object whose physical quantity is detected in the i-th period may be the same or different. In the latter case, it is sufficient that the two objects are the same type of object, for example, devices with the same model number.

[0022] Next, in step S50, the signal processing device 100 generates an i-th Lissajous figure based on the measurement data for the i-th period acquired in step S40. That is, in step S50, the signal processing device 100 generates an i-th Lissajous figure based on the physical quantity caused by the vibration of the object in the i-th period. The axes of the first Lissajous figure and the axes of the i-th Lissajous figure are the same.

[0023] When the signal processing device 100 acquires multiple sets of measurement data in step S40, the signal processing device 100 may generate multiple Lissajous figures based on the multiple sets of measurement data and average the multiple Lissajous figures to generate the i-th Lissajous figure in step S50. For example, if the i-th period is a one-day period and the physical quantity sensor detects the physical quantity six times every four hours, the signal processing device 100 may generate six Lissajous figures based on the six sets of measurement data and average the six Lissajous figures to generate the i-th Lissajous figure.

[0024] Next, in step S60, the signal processing device 100 calculates the degree of difference D between the first Lissajous figure generated in step S20 and the i-th Lissajous figure generated in step S50. i-1 For example, when the integer i is 2, the signal processing apparatus 100 calculates the degree of difference D1 between the first Lissajous figure and the second Lissajous figure in step S60.

[0025] Then, the signal processing device 100 increments the integer i by 1 in step S110 and repeats steps S40 to S60 until the signal processing in step S100 is completed.

[0026] 2 is a flowchart showing an example of the detailed procedure of step S60 in FIG. 1. As shown in FIG. 2, first, in step S61, the signal processing device 100 calculates the sum of distances SD0 between each of M points of the first Lissajous figure and each of M points of the i-th Lissajous figure, where M is an integer equal to or greater than 2. For example, as shown in FIG. 3, in a two-dimensional plane defined by the X-axis and the Y-axis, the first Lissajous figure indicated by the dashed line is divided into M points A1 to A2. M The ith Lissajous figure shown by the solid line is composed of M points B1 to B M In the equation (1), the signal processing device 100 calculates SD0 by using the equation (1). 1k is point A k is the X coordinate of 1k is point A k is the Y coordinate of the ik is point B k is the X coordinate of ik is point B k is the Y coordinate of the

[0027]

number

[0028] When the first Lissajous figure and the i-th Lissajous figure are drawn in a three-dimensional space defined by the X-axis, the Y-axis, and the Z-axis, the signal processing device 100 can calculate SD0 by the formula (2). 1k is point A k is the X coordinate of 1k is point A k is the Y coordinate of 1k is point A k is the Z coordinate of the ik is point B k is the X coordinate of ik is point B k is the Y coordinate ofik is the Z coordinate of point B k .

[0029]

Number

[0030] Next, the signal processing device 100 sets the minimum value SD min = SD0 in step S62 and sets the integer j to 1 in step S63.

[0031] Next, the signal processing device 100 shifts only j points among the M points of the first resurgence figure or the i-th resurgence figure in step S64, and calculates the sum SD j of the distances between each of the M points of the first resurgence figure and each of the M points of the i-th resurgence figure. Specifically, the signal processing device 100 calculates the distance between point A k and point B k+j for each integer k satisfying 1 ≤ k ≤ M - j according to Equation (3), calculates the distance between point A k and point B k+j-M for each integer k satisfying M - j < k ≤ M, and adds these distances to calculate SD j .

[0032]

Number

[0033] Alternatively, the signal processing device 100 calculates the distance between point A k+j and point B k for each integer k satisfying 1 ≤ k ≤ M - j according to Equation (4), calculates the distance between point A k+j-M and point B k for each integer k satisfying M-j < k ≤ M, and adds these distances to calculate SD j .

[0034] <00​​​​​

[0035] When the first Lissajous figure and the i-th Lissajous figure are drawn in a three-dimensional space defined by the X-axis, the Y-axis, and the Z-axis, the signal processing device 100 calculates the SD j can be calculated.

[0036]

number

[0037]

number

[0038] Next, the signal processing device 100 performs the SD j <SD min If so, in step S66, SD min =SD j Let's say.

[0039] The signal processing device 100 increments the integer j by 1 in step S68 and repeats steps S64 to S66 until the integer j reaches M-1 in step S67. When the integer j reaches M-1 in step S67, the signal processing device 100 finally performs step S69 to min Divide by the area of ​​the first Lissajous figure to get the dissimilarity D i-1 Calculate the SD min The dissimilarity D i-1 It may also be possible to use the following.

[0040] In this way, for each integer i between 2 and N, the signal processing device 100 calculates the sums SD0 to SD1 of the distances between each of the M points of the first Lissajous figure and each of the M points of the ith Lissajous figure in step S60 of FIG. M-1 Based on this, the dissimilarity D i-1 The signal processing device 100 performs step S60 of FIG. 1 N-1 times to calculate N-1 dissimilarities D1 to D N-1 The differences D1 to D N-1is an example of the "first to (N-1)th degree of difference."

[0041] 1-1-2.Signal processing device Fig. 4 is a diagram showing an example of the configuration of a signal processing device 100 that executes the signal processing method of the first embodiment. As shown in Fig. 4, the signal processing device 100 includes a physical quantity sensor 200, an analog front-end 210, a processing circuit 110, a memory circuit 120, an operation unit 130, a display unit 140, a sound output unit 150, and a communication unit 160. Note that the signal processing device 100 may be configured by omitting or changing some of the components shown in Fig. 4, or by adding other components. For example, the physical quantity sensor 200 and the analog front-end 210 do not have to be components of the signal processing device 100.

[0042] The physical quantity sensor 200 detects a physical quantity caused by vibration of an object and outputs a signal having a magnitude corresponding to the detected physical quantity. The output signal of the physical quantity sensor 200 is input to the analog front end 210.

[0043] The analog front end 210 performs amplification processing, A / D conversion processing, etc. on the output signal of the physical quantity sensor 200, and outputs a digital time-series signal.

[0044] The processing circuit 110 acquires, as measurement data for the first period, a digital time-series signal output from the physical quantity sensor 200 and output from the analog front-end 210 during a first period, and performs signal processing. Furthermore, for each integer i between 2 and N, the processing circuit 110 acquires, as measurement data for the i-th period, a digital time-series signal output from the physical quantity sensor 200 and output from the analog front-end 210 during the i-th period, and performs signal processing. That is, the processing circuit 110 acquires measurement data for the first to N-th periods and performs signal processing. Specifically, the processing circuit 110 executes a signal processing program 121 stored in the storage circuit 120 and performs various calculations on the measurement data for the first to N-th periods. Additionally, the processing circuit 110 performs various processes in response to operation signals from the operation unit 130, a process of transmitting display signals for displaying various information on the display unit 140, a process of transmitting sound signals for generating various sounds to the sound output unit 150, a process of controlling the communication unit 160 for data communication with an external device (not shown), and the like. The processing circuit 110 is realized by, for example, a CPU or a DSP. CPU is an abbreviation for Central Processing Unit, and DSP is an abbreviation for Digital Signal Processor.

[0045] The processing circuit 110 executes the signal processing program 121 to function as a measurement data acquisition circuit 111, a Lissajous figure generation circuit 112, and a dissimilarity calculation circuit 113. That is, the signal processing device 100 includes the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, and the dissimilarity calculation circuit 113.

[0046] The measurement data acquisition circuit 111 acquires measurement data based on the physical quantity detected by the physical quantity sensor 200 in a first period. Furthermore, for each integer i between 2 and N, the measurement data acquisition circuit 111 acquires measurement data based on the physical quantity caused by vibration of the object, detected by the physical quantity sensor 200 in the i-th period, where N is an integer greater than or equal to 2. That is, the measurement data acquisition circuit 111 executes steps S10 and S40 in FIG. 1. The measurement data acquired by the measurement data acquisition circuit 111 for the first to N-th periods is stored in the memory circuit 120.

[0047] The Lissajous figure generation circuit 112 generates a first Lissajous figure based on the measurement data for the first period acquired by the measurement data acquisition circuit 111. That is, the Lissajous figure generation circuit 112 generates the first Lissajous figure based on the physical quantity caused by the vibration of the object during the first period. Furthermore, the Lissajous figure generation circuit 112 generates an i-th Lissajous figure for each integer i between 2 and N based on the measurement data for the i-th period acquired by the measurement data acquisition circuit 111. That is, the Lissajous figure generation circuit 112 generates the i-th Lissajous figure based on the physical quantity caused by the vibration of the object during the i-th period. In this way, the Lissajous figure generation circuit 112 executes steps S20 and S50 of FIG. 1 . The first to N-th Lissajous figures generated by the Lissajous figure generation circuit 112 are stored in the memory circuit 120.

[0048] The dissimilarity calculation circuit 113 calculates, for each integer i between 2 and N, a dissimilarity D between the first Lissajous figure generated by the Lissajous figure generation circuit 112 and the ith Lissajous figure. i-1 The dissimilarity calculation circuit 113 calculates the dissimilarity D for each integer i between 2 and N based on the sum of the distances between each of the M points of the first Lissajous figure and each of the M points of the i-th Lissajous figure. i-1 where N is an integer equal to or greater than 2. That is, the dissimilarity calculation circuit 113 executes step S60 in FIG. 1, specifically steps S61 to S69 in FIG. 2. The dissimilarity calculation circuit 113 generates the dissimilarity D1 to D N-1is stored in the storage circuit 120.

[0049] In this way, the signal processing program 121 is a program that causes the signal processing device 100, which is a computer, to execute each procedure of the flowcharts shown in FIGS.

[0050] The storage circuitry 120 has a ROM and a RAM (not shown). ROM is an abbreviation for Read Only Memory, and RAM is an abbreviation for Random Access Memory. The ROM stores various programs such as the signal processing program 121 and predetermined data, and the RAM stores data generated by the processing circuitry 110. The RAM is also used as a working area for the processing circuitry 110, and stores programs and data read from the ROM, data input from the operation unit 130, and data temporarily generated by the processing circuitry 110.

[0051] The operation unit 130 is an input device configured with operation keys, button switches, etc., and outputs an operation signal to the processing circuit 110 in response to an operation by a user.

[0052] The display unit 140 is a display device configured by an LCD or the like, and displays various information based on a display signal output from the processing circuit 110. LCD is an abbreviation for Liquid Crystal Display. The display unit 140 may be provided with a touch panel that functions as the operation unit 130. For example, the display unit 140 displays the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2 based on the display signal output from the processing circuit 110. N-1 A screen including at least a part of the above may be displayed.

[0053] The sound output unit 150 is configured with a speaker or the like, and generates various sounds based on the sound signal output from the processing circuit 110. For example, the sound output unit 150 may generate sounds indicating the start or end of signal processing based on the sound signal output from the processing circuit 110.

[0054] The communication unit 160 performs various controls to establish data communication between the processing circuit 110 and an external device. For example, the communication unit 160 transmits the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2. N-1 The external device may transmit information including at least a part of the above to an external device, and the external device may display at least a part of the received information on a display unit (not shown).

[0055] At least a part of the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, and the dissimilarity calculation circuit 113 may be realized by dedicated hardware. Furthermore, the signal processing device 100 may be a single device, or may be configured by multiple devices. For example, the physical quantity sensor 200 and the analog front end 210 may be included in a first device, and the processing circuit 110, the memory circuit 120, the operation unit 130, the display unit 140, the sound output unit 150, and the communication unit 160 may be included in a second device separate from the first device. Furthermore, for example, the processing circuit 110 and the memory circuit 120 may be realized by a device such as a cloud server, and the device may store the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2. N-1 The generated information may be transmitted to a terminal including the operation unit 130, the display unit 140, the sound output unit 150, and the communication unit 160 via a communication line.

[0056] 1-1-3.Effects In the signal processing method of the first embodiment described above, if the vibration state of the object, such as the amplitude, frequency, and phase, is normal in the first period and an abnormality occurs in the vibration state of the object in the i-th period, the difference between the vibration state in the first period and the vibration state in the i-th period generally becomes large regardless of the type of abnormality.The larger the difference between the vibration state of the object in the first period and the vibration state of the object in the i-th period, the larger the deviation of the i-th Lissajous figure from the first Lissajous figure tends to become.Therefore, a dissimilarity D is calculated based on the sum of the distances between each point of the first Lissajous figure and each point of the i-th Lissajous figure. i-1Therefore, according to the signal processing method of the first embodiment, the signal processing device 100 uses the differences D1 to D2 as indices that allow the user to determine whether or not an abnormality exists even if an unexpected abnormality occurs in the vibration state of the object during the second to Nth periods. N-1 Furthermore, the signal processing device 100 does not need to store Lissajous figures corresponding to assumed abnormal modes in advance.

[0057] 1-2. Second embodiment In the following, in the second embodiment, the same components as those in the first embodiment are given the same reference numerals, and explanations that overlap with those in the first embodiment are omitted or simplified, and differences from the first embodiment are mainly described.

[0058] 5 is a flowchart showing the procedure of the signal processing method of the second embodiment. The signal processing method of the second embodiment is executed, for example, by the signal processing device 100 operating in accordance with a signal processing program. An example of the configuration of the signal processing device 100 that executes the signal processing method of the second embodiment will be described later.

[0059] As shown in Fig. 5, first, the signal processing device 100 executes steps S10 to S60, similarly to the first embodiment. The detailed procedure of step S60 is the same as that in Fig. 2, and therefore will not be illustrated or described again. Note that in this embodiment, the vibrations in each of the first to Nth periods are vibrations caused by the movement of the same object.

[0060] Next, in step S70, the signal processing device 100 sets an integer N=i to the dissimilarities D1 to D2 calculated in step S60. N-1Transition information including the above in a time series is generated. N is an integer equal to or greater than 3. FIG. 6 is a graph showing an example of the transition information. In the example of FIG. 6, from day 0 to around day 10, the dissimilarity gradually increases from approximately 20% to approximately 30%, and the object is in an "initial progression" state. From around day 10 to around day 19, the dissimilarity remains almost unchanged at approximately 30% to 35%, and the object is in a "stagnation" state. On day 20, the dissimilarity suddenly increases to nearly 50%, and from day 20 onwards, the object is in a "final progression" state. From the graph of the transition information shown in FIG. 6, the user can determine that an abnormality has occurred in the object on day 20.

[0061] Then, the signal processing device 100 increments the integer i by 1 in step S110 and repeats steps S40 to S70 until the signal processing in step S100 is completed.

[0062] 7 is a diagram showing an example of the configuration of a signal processing device 100 that executes the signal processing method of the second embodiment. As shown in FIG. 7, the signal processing device 100 includes a physical quantity sensor 200, an analog front-end 210, a processing circuit 110, a memory circuit 120, an operation unit 130, a display unit 140, a sound output unit 150, and a communication unit 160. Note that the signal processing device 100 may be configured by omitting or changing some of the components shown in FIG. 7, or by adding other components. For example, the physical quantity sensor 200 and the analog front-end 210 do not have to be components of the signal processing device 100.

[0063] The configurations and functions of the physical quantity sensor 200, analog front end 210, memory circuit 120, operation unit 130, display unit 140, sound output unit 150, and communication unit 160 are the same as those in the first embodiment, and therefore will not be described again.

[0064] The processing circuitry 110 executes a signal processing program 121 stored in the memory circuitry 120, thereby functioning as a measurement data acquisition circuit 111, a Lissajous figure generation circuit 112, a dissimilarity calculation circuit 113, and a transition information generation circuit 114. In other words, the signal processing device 100 includes the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, the dissimilarity calculation circuit 113, and the transition information generation circuit 114.

[0065] The measurement data acquisition circuit 111 executes steps S10 and S40 in Fig. 5. The Lissajous figure generation circuit 112 executes steps S20 and S50 in Fig. 5. The dissimilarity calculation circuit 113 executes step S60 in Fig. 5, specifically steps S61 to S69 in Fig. 2. The functions of the measurement data acquisition circuit 111, Lissajous figure generation circuit 112, and dissimilarity calculation circuit 113 are the same as in the first embodiment, so their description will be omitted.

[0066] The transition information generating circuit 114 calculates the differences D1 to D2 calculated by the difference calculation circuit 113. N-1 In other words, the transition information generation circuit 114 executes step S70 in Fig. 5. The transition information generated by the transition information generation circuit 114 is stored in the storage circuit 120.

[0067] The display unit 140 displays the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2 based on the display signal output from the processing circuit 110. N-1 A screen including at least a part of the transition information may be displayed.

[0068] The communication unit 160 receives the first to Nth Lissajous figures and the dissimilarity degrees D1 to D N-1 and information including at least a part of the transition information may be transmitted to an external device, and the external device may display at least a part of the received information on a display unit (not shown).

[0069] At least some of the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, the dissimilarity calculation circuit 113, and the transition information generation circuit 114 may be realized by dedicated hardware.

[0070] Other configurations of the signal processing device 100 in the second embodiment are the same as those in the first embodiment, and therefore description thereof will be omitted.

[0071] In this embodiment, the object whose physical quantity is detected in the first period is the same as the object whose physical quantity is detected in the i-th period. That is, the transition information is calculated by dividing the differences D1 to D N-1 In addition, the physical quantity sensor 200 that outputs the measurement data for the first period and the physical quantity sensor 200 that outputs the measurement data for the i-th period are preferably the same sensor, but may be different sensors that detect the same type of physical quantity.

[0072] According to the signal processing method of the second embodiment described above, the same effects as those of the signal processing method of the first embodiment can be obtained. Furthermore, according to the signal processing method of the second embodiment, when the vibration state of the object changes from a normal vibration state to an abnormal vibration state in the i-th period, the difference D i-1 Since the difference D1 to D N-1 Based on the transition information including the time series of the above, it is possible to grasp the timing at which the object changes into an abnormal vibration state.

[0073] 1-3. Third embodiment Hereinafter, for the third embodiment, components similar to those in the first or second embodiment will be given the same symbols, explanations that overlap with those in the first or second embodiment will be omitted or simplified, and the following will mainly describe the differences from the first and second embodiments.

[0074] 8 is a flowchart showing the procedure of the signal processing method of the third embodiment. The signal processing method of the third embodiment is executed, for example, by the signal processing device 100 operating in accordance with a signal processing program. An example of the configuration of the signal processing device 100 that executes the signal processing method of the third embodiment will be described later.

[0075] As shown in FIG. 8, first, the signal processing device 100 executes steps S10 to S50 in the same manner as in the first or second embodiment.

[0076] Next, in step S52, the signal processing device 100 calculates the coordinates of some of the M points by interpolation for at least one of the first Lissajous figure generated in step S20 and the i-th Lissajous figure generated in step S50. For example, as shown in FIG. 9, in a two-dimensional plane defined by the X-axis and the Y-axis, the first Lissajous figure generated in step S20, indicated by a dashed line, is arranged at a plurality of black points A1, A3, A5, ..., A M-3 ,A M-1 The ith Lissajous figure shown by the solid line generated in step S50 is made up of a plurality of black points B1, B3, B5, ..., B M-3 ,B M-1 The signal processing device 100 places white points A2, A4, A6, ..., A between each two points for the first Lissajous figure. M-2 ,A M By interpolating M points A1 to A M For the ith Lissajous figure, white points B2, B4, B6, …, B are placed between each of the two points. M-2 ,B M By interpolating M points B1 to B M For example, these interpolations may be spline interpolations.

[0077] Next, in step S60, the signal processing device 100 calculates the degree of difference D between the first Lissajous figure generated in step S20 and interpolated as needed in step S52 and the i-th Lissajous figure generated in step S50 and interpolated as needed in step S52. i-1 The detailed procedure of step S60 is the same as that shown in FIG.

[0078] Next, the signal processing device 100 executes step S70 in the same manner as in the second embodiment. Then, the signal processing device 100 increments the integer i by 1 in step S110 and repeatedly executes steps S40 to S70 until the signal processing in step S100 is completed.

[0079] Fig. 10 is a diagram showing an example of the configuration of a signal processing device 100 that executes the signal processing method of the third embodiment. As shown in Fig. 10, the signal processing device 100 includes a physical quantity sensor 200, an analog front-end 210, a processing circuit 110, a memory circuit 120, an operation unit 130, a display unit 140, a sound output unit 150, and a communication unit 160. Note that the signal processing device 100 may be configured by omitting or changing some of the components shown in Fig. 10, or by adding other components. For example, the physical quantity sensor 200 and the analog front-end 210 do not have to be components of the signal processing device 100.

[0080] The configurations and functions of the physical quantity sensor 200, analog front end 210, memory circuit 120, operation unit 130, display unit 140, sound output unit 150, and communication unit 160 are the same as those of the first or second embodiment, and therefore will not be described again.

[0081] The processing circuitry 110 executes a signal processing program 121 stored in the memory circuitry 120, thereby functioning as a measurement data acquisition circuit 111, a Lissajous figure generation circuit 112, a dissimilarity calculation circuit 113, a transition information generation circuit 114, and an interpolation circuit 115. In other words, the signal processing device 100 includes the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, the dissimilarity calculation circuit 113, the transition information generation circuit 114, and the interpolation circuit 115.

[0082] The measurement data acquisition circuit 111 executes steps S10 and S40 in Fig. 8. The Lissajous figure generation circuit 112 executes steps S20 and S50 in Fig. 8. The dissimilarity calculation circuit 113 executes step S60 in Fig. 8, specifically steps S61 to S69 in Fig. 2. The transition information generation circuit 114 executes step S70 in Fig. 8. The functions of the measurement data acquisition circuit 111, Lissajous figure generation circuit 112, and dissimilarity calculation circuit 113 are the same as in the first or second embodiment, and the function of the transition information generation circuit 114 is the same as in the second embodiment, so their description will be omitted.

[0083] The interpolation circuit 115 calculates the coordinates of some of the M points by interpolation for at least one of the first Lissajous figure and the i-th Lissajous figure generated by the Lissajous figure generation circuit 112. For example, the interpolation may be spline interpolation.

[0084] The display unit 140 displays the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2 based on the display signal output from the processing circuit 110. N-1 A screen including at least a part of the transition information may be displayed.

[0085] The communication unit 160 receives the first to Nth Lissajous figures and the dissimilarity degrees D1 to D N-1 and information including at least a part of the transition information may be transmitted to an external device, and the external device may display at least a part of the received information on a display unit (not shown).

[0086] At least some of the measurement data acquisition circuit 111, Lissajous figure generation circuit 112, dissimilarity calculation circuit 113, transition information generation circuit 114, and interpolation circuit 115 may be realized by dedicated hardware.

[0087] The other configurations of the signal processing device 100 in the third embodiment are the same as those in the first or second embodiment, and therefore the description thereof will be omitted.

[0088] In this embodiment, the physical quantity sensor 200 that outputs measurement data in the first period and the physical quantity sensor 200 that outputs measurement data in the i-th period may be the same or different. In the latter case, it is sufficient that the two physical quantity sensors 200 detect the same type of physical quantity. Furthermore, the object whose physical quantity is detected in the first period and the object whose physical quantity is detected in the i-th period may be the same or different. In the latter case, it is sufficient that the two objects are the same type of object, for example, devices with the same model number.

[0089] According to the signal processing method of the third embodiment described above, the same effects as those of the signal processing method of the first or second embodiment can be obtained. Furthermore, according to the signal processing method of the third embodiment, even if the number of points of the first Lissajous figure and the number of points of the i-th Lissajous figure are different, the signal processing device 100 can make the numbers of points of both figures the same, so that the dissimilarity D i-1 Furthermore, according to the signal processing method of the third embodiment, the signal processing device 100 can increase the number of points of both the first Lissajous figure and the i-th Lissajous figure even when the number of points of both the first Lissajous figure and the i-th Lissajous figure is small, so that the dissimilarity D i-1 The calculation accuracy can be improved.

[0090] 1-4. Fourth embodiment Hereinafter, for the fourth embodiment, components similar to those of any of the first to third embodiments will be given the same symbols, and explanations that overlap with those of any of the first to third embodiments will be omitted or simplified, and the following will mainly describe the differences from any of the first to third embodiments.

[0091] 11 is a flowchart showing the procedure of the signal processing method of the fourth embodiment. The signal processing method of the fourth embodiment is executed, for example, by the signal processing device 100 operating in accordance with a signal processing program. An example of the configuration of the signal processing device 100 that executes the signal processing method of the fourth embodiment will be described later.

[0092] As shown in FIG. 11, first, the signal processing device 100 executes steps S10 to S70 in the same manner as in any of the first to third embodiments.

[0093] Next, in step S80, the signal processing device 100 calculates the dissimilarities D1 to D2 calculated in step S60. N-1 For example, the signal processing device 100 determines whether the vibration state in the i-th period is normal or abnormal based on the difference D i-1 is compared with a predetermined threshold and the difference D i-1 If is less than the threshold, the vibration state in the i-th period is determined to be normal, and the difference D i-1 Alternatively, the signal processing device 100 may determine that the vibration state in the i-th period is abnormal if the difference degrees D1 to D2 generated in step S70 are equal to or greater than the threshold value. N-1 Based on the transition information including the time series, the difference D i-1 Dissimilarity D i-2 If the rate of increase relative to the vibration frequency is equal to or greater than a predetermined threshold, it may be determined that the vibration state has become abnormal.

[0094] Then, the signal processing device 100 increments the integer i by 1 in step S110 and repeats steps S40 to S80 until the signal processing in step S100 is completed.

[0095] Fig. 12 is a diagram showing an example of the configuration of a signal processing device 100 that executes the signal processing method of the fourth embodiment. As shown in Fig. 12, the signal processing device 100 includes a physical quantity sensor 200, an analog front-end 210, a processing circuit 110, a memory circuit 120, an operation unit 130, a display unit 140, a sound output unit 150, and a communication unit 160. Note that the signal processing device 100 may be configured by omitting or changing some of the components shown in Fig. 12 or by adding other components. For example, the physical quantity sensor 200 and the analog front-end 210 do not have to be components of the signal processing device 100.

[0096] The configurations and functions of the physical quantity sensor 200, analog front end 210, memory circuit 120, operation unit 130, display unit 140, sound output unit 150, and communication unit 160 are the same as those of any of the first to third embodiments, and therefore will not be described again.

[0097] The processing circuitry 110 executes a signal processing program 121 stored in the memory circuitry 120, thereby functioning as a measurement data acquisition circuit 111, a Lissajous figure generation circuit 112, a dissimilarity calculation circuit 113, a transition information generation circuit 114, an interpolation circuit 115, and a state determination circuit 116. That is, the signal processing device 100 includes the measurement data acquisition circuit 111, the Lissajous figure generation circuit 112, the dissimilarity calculation circuit 113, the transition information generation circuit 114, the interpolation circuit 115, and the state determination circuit 116.

[0098] The measurement data acquisition circuit 111 executes steps S10 and S40 in Fig. 11. The Lissajous figure generation circuit 112 executes steps S20 and S50 in Fig. 11. The dissimilarity calculation circuit 113 executes step S60 in Fig. 11, specifically steps S61 to S69 in Fig. 2. The transition information generation circuit 114 executes step S70 in Fig. 11. The interpolation circuit 115 executes step S52 in Fig. 11. The functions of the measurement data acquisition circuit 111, Lissajous figure generation circuit 112, and dissimilarity calculation circuit 113 are the same as those in any of the first to third embodiments, the function of the transition information generation circuit 114 is the same as that in the second or third embodiment, and the function of the interpolation circuit 115 is the same as that in the third embodiment, so their description will be omitted.

[0099] The state determination circuit 116 determines the differences D1 to D2 calculated by the difference calculation circuit 113. N-1 For example, the state determination circuit 116 determines whether the vibration state is normal or abnormal for each of the second to Nth periods based on the difference D i-1 is compared with a predetermined threshold and the difference D i-1 If is less than the threshold, the vibration state in the i-th period is determined to be normal, and the difference D i-1Alternatively, the state determination circuit 116 may determine that the vibration state in the i-th period is abnormal if the difference degrees D1 to D2 generated by the transition information generation circuit 114 are equal to or greater than the threshold value. N-1 Based on the transition information including the time series, the difference D i-1 Dissimilarity D i-2 The state of vibration may be determined to be abnormal if the rate of increase relative to the vibration level is equal to or greater than a predetermined threshold. The result of the determination of the vibration state by the state determination circuit 116 is stored in the memory circuit 120.

[0100] The display unit 140 displays the first to Nth Lissajous figures and the dissimilarity degrees D1 to D2 based on the display signal output from the processing circuit 110. N-1 A screen including at least a part of the transition information and the vibration state determination result may be displayed.

[0101] The communication unit 160 receives the first to Nth Lissajous figures and the dissimilarity degrees D1 to D N-1 The external device may transmit information including at least a part of the transition information and the vibration state determination result to an external device, and the external device may display at least a part of the received information on a display unit (not shown).

[0102] At least some of the measurement data acquisition circuit 111, Lissajous figure generation circuit 112, dissimilarity calculation circuit 113, transition information generation circuit 114, interpolation circuit 115, and state determination circuit 116 may be realized by dedicated hardware.

[0103] The other configurations of the signal processing device 100 in the fourth embodiment are the same as those in any of the first to third embodiments, and therefore the description thereof will be omitted.

[0104] In this embodiment, the physical quantity sensor 200 that outputs measurement data in the first period and the physical quantity sensor 200 that outputs measurement data in the i-th period may be the same or different. In the latter case, it is sufficient that the two physical quantity sensors 200 detect the same type of physical quantity. Furthermore, the object whose physical quantity is detected in the first period and the object whose physical quantity is detected in the i-th period may be the same or different. In the latter case, it is sufficient that the two objects are the same type of object, for example, devices with the same model number.

[0105] According to the signal processing method of the fourth embodiment described above, the same effects as those of the signal processing methods of the first to third embodiments can be obtained. Furthermore, according to the signal processing method of the fourth embodiment, the signal processing device 100 calculates the dissimilarity degrees D1 to D N-1 Whether the vibration state of the object in each of the second to Nth periods is normal or abnormal is objectively determined based on the above, thereby reducing the effort required for the user to make the determination and reducing variations in the determination results.

[0106] 2.Signal Processing System Hereinafter, for the signal processing system of this embodiment, components similar to those described in any of the above embodiments will be given the same symbols, and explanations that overlap with any of the above embodiments will be omitted or simplified, with the main focus being on the differences from any of the above embodiments.

[0107] 13 is a diagram showing an example of the configuration of a signal processing system according to this embodiment. As shown in FIG. 13, the signal processing system 10 according to this embodiment includes a physical quantity sensor 200, an analog front-end 210, a signal processing device 100, and a display device 220.

[0108] The object 1 includes a movable body 2 and a housing 3 that houses the movable body 2. The physical quantity sensor 200 is attached to the housing 3, detects a physical quantity caused by vibration of the object 1 in each of the first to Nth periods, and outputs a signal having a magnitude corresponding to the detected physical quantity. The output signal of the physical quantity sensor 200 is input to an analog front end 210.

[0109] The analog front end 210 performs amplification processing, A / D conversion processing, etc. on the output signal of the physical quantity sensor 200, and outputs a digital time-series signal.

[0110] The signal processing device 100 acquires, as measurement data for the first period, a digital time-series signal that is output from the physical quantity sensor 200 and output from the analog front-end 210 during the first period, and generates a first Lissajous figure based on the measurement data for the first period. Furthermore, for each integer i between 2 and N, the signal processing device 100 acquires, as measurement data for the i-th period, a digital time-series signal that is output from the physical quantity sensor 200 during the i-th period and output from the analog front-end 210, and generates an i-th Lissajous figure based on the measurement data for the i-th period. That is, the signal processing device 100 acquires measurement data for the first to N-th periods and generates the first to N-th Lissajous figures. Then, for each integer i between 2 and N, the signal processing device 100 calculates a degree of difference D between the first Lissajous figure and the i-th Lissajous figure. i-1 Calculate the calculated differences D1 to D N-1 and displays at least a part of the various pieces of information on the display device 220. The display device 220 may be a device separate from the signal processing device 100, or may be a display unit included in the signal processing device 100. Note that when the physical quantity sensor 200 outputs a digital time-series signal, the signal processing device 100 only needs to acquire the digital time-series signal, and therefore the analog front end 210 may not be provided. As the signal processing device 100, for example, any of the signal processing devices 100 of the first to fourth embodiments described above can be applied.

[0111] FIG. 14 shows a vacuum pump 1a, which is an example of the target object 1. As shown in FIG. 14, the vacuum pump 1a is installed on a base 20. The cross section of the vacuum pump 1a is a columnar shape with a substantially oval shape. The longitudinal direction of the vacuum pump 1a is the X direction. The long axis direction of the oval is the Y direction, and the short axis direction of the oval is the Z direction.

[0112] The vacuum pump 1a includes a housing 3. The housing 3 includes a motor case 4, a connection portion 5, a pump case 6, and a gear case 7, which are arranged from the -X direction side toward the +X direction side. The housing 3 includes a first side wall 8 serving as a bearing casing between the connection portion 5 and the pump case 6. The housing 3 includes a second side wall 9 between the pump case 6 and the gear case 7.

[0113] An intake pipe 11 is connected to the surface of the pump case 6 on the +Z direction side, and an exhaust pipe 12 is connected to the surface of the pump case 6 on the −Z direction side.

[0114] The connecting part 5 has a first leg 13 and a second leg on the base 20 side. The first leg 13 is arranged on the -Y direction side, and the second leg is arranged on the +Y direction side. The gear case 7 has a third leg 14 and a fourth leg on the base 20 side. The third leg 14 is arranged on the -Y direction side, and the fourth leg is arranged on the +Y direction side. The first leg 13 to the fourth leg are fastened to the base 20 by a first bolt 15.

[0115] A physical quantity sensor 200 is attached to the housing 3. The physical quantity sensor 200 is attached to, for example, the connection portion 5. For example, the physical quantity sensor 200 may be a three-axis acceleration sensor that detects acceleration in the X-axis direction, acceleration in the Y-axis direction, and acceleration in the Z-axis direction. Furthermore, for example, the physical quantity sensor 200 may be a three-axis velocity sensor that detects velocity in the X-axis direction, velocity in the Y-axis direction, and velocity in the Z-axis direction.

[0116] The internal structure of vacuum pump 1a will be described using Figures 15 and 16. Figure 15 is a view from the -Y direction. Figure 16 is a view from the +Z direction. The first leg 13 to the fourth leg 14 are omitted from the figure. Vacuum pump 1a includes pump rotors 18 as two movable bodies 2 that transfer gas, and two motors 19 that rotate the two pump rotors 18. Housing 3 houses pump rotors 18.

[0117] The two pump rotors 18 have two rotating shafts 21. The two rotating shafts 21 are rotatably supported by first and second bearings 22 and 23, respectively. Two motors 19 are connected to one end of each rotating shaft 21. The motors 19 are configured to rotate the two pump rotors 18 in synchronous directions opposite to each other. Two timing gears 24 are fixed to the other end of the rotating shafts 21. These timing gears 24 are provided to ensure synchronous rotation of the two pump rotors 18 in the event that the two motors 19 lose synchronous rotation.

[0118] The pump case 6 is sandwiched between a first side wall 8 and a second side wall 9. The pump rotor 18 is disposed in a pump chamber 25 defined by the pump case 6, the first side wall 8, and the second side wall 9.

[0119] The first side wall 8 supports a first bearing 22 on the intake pipe 11 side. The first bearing 22 is disposed within the connecting portion 5. The motor 19 is disposed within a motor case 4 fixed to the connecting portion 5. A second bearing 23 on the exhaust pipe 12 side is fixed to the second side wall 9. The timing gear 24 and the second bearing 23 are disposed within the gear case 7. The first bearing 22 and the second bearing 23 vibrate due to the rotation of the pump rotor 18. The vibrations of the first bearing 22 and the second bearing 23 are transmitted to the housing 3 of the connecting portion 5 etc. via the first side wall 8 and the second side wall 9. The physical quantity sensor 200 detects the vibrations transmitted to the housing 3.

[0120] According to the signal processing system 10 of this embodiment, the signal processing device 100 calculates the dissimilarity degrees D1 to D2 based on the signals output from the physical quantity sensor 200 during the first to Nth periods. N-1 Calculate the difference D1 to D N-1 Various pieces of information based on the above can be displayed on the display device 220. Therefore, the user can monitor the state of the object 1 based on the information displayed on the display device 220 and accurately determine whether the state of the object 1 is normal or abnormal.

[0121] The signal processing system 10 may include a plurality of physical quantity sensors 200. The plurality of physical quantity sensors 200 may be provided on different objects 1, and each physical quantity sensor 200 may detect a physical quantity caused by vibration in each of the first to Nth periods.

[0122] The present invention is not limited to the present embodiment, and various modifications are possible within the scope of the present invention.

[0123] The above-described embodiment and modifications are merely examples, and the present invention is not limited to these. For example, the embodiments and modifications can be combined as appropriate.

[0124] The present invention includes configurations that are substantially the same as the configurations described in the embodiments, for example, configurations with the same functions, methods, and results, or configurations with the same purpose and effects. The present invention also includes configurations that replace non-essential parts of the configurations described in the embodiments. The present invention also includes configurations that achieve the same effects or purposes as the configurations described in the embodiments. The present invention also includes configurations that add publicly known technology to the configurations described in the embodiments.

[0125] The following can be derived from the above-described embodiment and modifications.

[0126] One aspect of the signal processing method includes: generating a first Lissajous figure based on a physical quantity caused by the vibration during a first period; Let N be an integer greater than or equal to 2, and for each integer i greater than or equal to 2 and less than or equal to N, generating an i-th Lissajous figure based on a physical quantity caused by the vibration in the i-th period; The (i-1)th degree of difference, which is the degree of difference between the first Lissajous figure and the ith Lissajous figure, is calculated.

[0127] In this signal processing method, if the vibration state, such as the amplitude, frequency, and phase of the vibration, is normal in the first period and an abnormality occurs in the vibration state in the ith period, generally, regardless of the type of abnormality, the difference between the vibration state in the first period and the vibration state in the ith period will be large, and as a result, the (i-1)th difference degree, which is the difference degree between the first Lissajous figure and the ith Lissajous figure, will be large. Therefore, according to this signal processing method, even if an unexpected abnormality occurs in the vibration state in the second to Nth periods, it is possible to calculate the first to (N-1)th differences as indicators that allow the user to determine whether or not there is an abnormality.

[0128] In one aspect of the signal processing method, the vibrations in each of the first to Nth periods are vibrations caused by the movement of the same object, The integer N may be 3 or greater, and transition information may be generated that includes the first to (N-1)th degrees of difference in time series.

[0129] According to this signal processing method, if the object changes from a normal vibration state to an abnormal vibration state during the i-th period, the (i-1)th difference degree increases suddenly, and the user can grasp the timing at which the object changed into an abnormal vibration state based on the transition information.

[0130] In one aspect of the signal processing method, It may be determined whether the state of the vibration in the i-th period is normal or abnormal based on the first to (N-1)-th degrees of difference.

[0131] According to this signal processing method, if a vibration state changes from a normal state to an abnormal state during the i-th period, the i-th difference degree changes significantly, allowing the user or the signal processing device to determine whether the vibration state is normal or abnormal.

[0132] In one aspect of the signal processing method, The (i-1) dissimilarity may be calculated based on the sum of the distances between each of the M points of the first Lissajous figure and each of the M points of the i-th Lissajous figure, where M is an integer equal to or greater than 2.

[0133] In this signal processing method, the greater the difference between the vibration state in the first period and the vibration state in the i-th period, the greater the deviation of the i-th Lissajous figure from the first Lissajous figure tends to be, so the (i-1)th difference degree becomes larger based on the sum of the distances between each point on the first Lissajous figure and each point on the i-th Lissajous figure. Therefore, even if an unexpected abnormality occurs in the vibration state in the i-th period, the (i-1)th difference degree can be calculated as an index that allows the user to determine whether or not there is an abnormality.

[0134] In one aspect of the signal processing method, Coordinates of some of the M points may be calculated by interpolation for at least one of the first Lissajous figure and the i-th Lissajous figure.

[0135] According to this signal processing method, even if the number of points of the first Lissajous figure and the number of points of the ith Lissajous figure are different, the numbers of points of both figures can be made the same, so that the (i-1)th dissimilarity can be calculated correctly. Also, according to this signal processing method, even if the number of points of the first Lissajous figure and the number of points of the ith Lissajous figure are small, the numbers of points of both figures can be increased, so that the accuracy of calculating the (i-1)th dissimilarity can be improved.

[0136] One aspect of the signal processing device includes: a Lissajous figure generating circuit that generates a first Lissajous figure based on a physical quantity caused by vibration in a first period, and generates an i-th Lissajous figure for each integer i between 2 and N, inclusive, based on the physical quantity caused by vibration in an i-th period, where N is an integer of 2 or more; a dissimilarity calculation circuit that calculates an (i-1)th dissimilarity between the first Lissajous figure and the i-th Lissajous figure; Includes:

[0137] In this signal processing device, if the vibration state, such as the amplitude, frequency, and phase of the vibration, is normal in the first period and an abnormality occurs in the vibration state in the ith period, generally, regardless of the type of abnormality, the difference between the vibration state in the first period and the vibration state in the ith period will be large, and as a result, the (i-1)th difference degree, which is the difference degree between the first Lissajous figure and the ith Lissajous figure, will be large. Therefore, according to this signal processing device, even if an unexpected abnormality occurs in the vibration state in the second to Nth periods, it is possible to calculate the first to (N-1)th differences as indicators that allow the user to determine whether or not there is an abnormality.

[0138] One aspect of the signal processing system comprises: An aspect of the signal processing device; at least one physical quantity sensor that detects the physical quantity generated by the vibration in each of the first to Nth periods; Equipped with.

[0139] One aspect of the signal processing program is generating a first Lissajous figure based on a physical quantity caused by the vibration during a first period; Let N be an integer greater than or equal to 2, and for each integer i greater than or equal to 2 and less than or equal to N, generating an i-th Lissajous figure based on a physical quantity caused by the vibration in the i-th period; The computer is caused to calculate the (i-1)th degree of difference, which is the degree of difference between the first Lissajous figure and the i-th Lissajous figure.

[0140] In this signal processing program, if the vibration state, such as the amplitude, frequency, and phase of the vibration, is normal in the first period and an abnormality occurs in the vibration state in the ith period, generally, regardless of the type of abnormality, the difference between the vibration state in the first period and the vibration state in the ith period will be large, and as a result, the (i-1)th difference degree, which is the difference between the first Lissajous figure and the ith Lissajous figure, will be large. Therefore, according to this signal processing program, the computer can calculate the first to (N-1)th difference degrees as indicators that allow the user to determine whether or not there is an abnormality, even if an unexpected abnormality occurs in the vibration state in the second to Nth periods. [Explanation of symbols]

[0141] 1...object, 1a...vacuum pump, 2...moving body, 3...housing, 4...motor case, 5...connection part, 6...pump case, 7...gear case, 8...first side wall, 9...second side wall, 10...signal processing system, 11...intake pipe, 12...exhaust pipe, 13...first leg, 14...third leg, 15...first bolt, 18...pump rotor, 19...motor, 20...base, 21...rotating shaft, 22...first bearing, 23...second bearing, 24...timing gear, 25...pump Chamber, 100... signal processing device, 110... processing circuit, 111... measurement data acquisition circuit, 112... Lissajous figure generation circuit, 113... dissimilarity calculation circuit, 114... transition information generation circuit, 115... interpolation circuit, 116... state determination circuit, 120... memory circuit, 121... signal processing program, 130... operation unit, 140... display unit, 150... sound output unit, 160... communication unit, 200... physical quantity sensor, 210... analog front end, 220... display device

Claims

1. generating a first Lissajous figure based on a physical quantity caused by the vibration during the first period; N is an integer of 2 or more, and for each integer i between 2 and N, generating an i-th Lissajous figure based on a physical quantity caused by vibration in the i-th period; A signal processing method for calculating an (i-1)th degree of difference between the first Lissajous figure and the i-th Lissajous figure.

2. In claim 1, the vibrations in each of the first to Nth periods are vibrations caused by the movement of the same object, The signal processing method generates transition information including the first to (N-1)th dissimilarity degrees in a time series, wherein the integer N is 3 or greater.

3. In claim 1, A signal processing method for determining whether the state of the vibration in the i-th period is normal or abnormal based on the first to (N-1)-th degrees of difference.

4. In claim 1, a signal processing method for calculating the (i-1) dissimilarity based on a sum of distances between each of M points of the first Lissajous figure and each of M points of the i-th Lissajous figure, where M is an integer equal to or greater than 2.

5. In claim 4, a signal processing method for calculating, by interpolation, coordinates of some of the M points for at least one of the first Lissajous figure and the i-th Lissajous figure;

6. a Lissajous figure generating circuit that generates a first Lissajous figure based on a physical quantity caused by vibration in a first period, and generates an i-th Lissajous figure for each integer i between 2 and N, inclusive, based on the physical quantity caused by vibration in an i-th period, where N is an integer of 2 or more; a dissimilarity calculation circuit that calculates an (i-1)th dissimilarity between the first Lissajous figure and the i-th Lissajous figure; a signal processing device comprising:

7. A signal processing device according to claim 6; at least one physical quantity sensor that detects the physical quantity caused by the vibration in each of the first to Nth periods; A signal processing system comprising:

8. generating a first Lissajous figure based on a physical quantity caused by the vibration during the first period; N is an integer of 2 or more, and for each integer i between 2 and N, generating an i-th Lissajous figure based on a physical quantity caused by vibration in the i-th period; a signal processing program that causes a computer to calculate an (i-1)th degree of difference that is a degree of difference between the first Lissajous figure and the i-th Lissajous figure;

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