A vibration detection device and method for a multi-axis robot

Abstract

The application provides a vibration detection device and method of a multi-axis mechanical arm, the vibration detection device of the multi-axis mechanical arm comprises a plurality of detection units and an information processing unit. Each detection unit is installed on a connecting rod of the multi-axis mechanical arm, and the detection unit comprises an acceleration sensor. The detection unit obtains a detection signal of the connecting rod through the acceleration sensor. The information processing unit is in communication connection with the plurality of detection units. The information processing unit is used for respectively performing time-frequency analysis on a plurality of detection signals obtained by the plurality of detection units to form a plurality of time-frequency analysis results, and judging whether the corresponding connecting rod has vibration based on the plurality of time-frequency analysis results and a preset condition. The application solves the problems of high detection cost caused by an external torque sensor or a multi-degree-of-freedom sensor and high-precision modeling required by an algorithm in the prior art.

Description

Technical Field

[0001] This invention relates to the field of robotics, and more particularly to a vibration detection device and method for a multi-axis robotic arm. Background Technology

[0002] Multi-axis robotic arms often experience vibrations during actual operation, posing safety hazards. These vibrations can occur due to the robotic arm itself or from collisions with external objects. Vibrations within the robotic arm itself stem from the characteristics of its mechatronic system. Factors such as joint motor drive control and load variations can cause vibrations, even resonance, within the robotic arm. Vibrations caused by collisions arise because the robotic arm operates within a defined workspace, which may contain people, objects, or unexpected intrusions, increasing the risk of collisions. Therefore, it is crucial to detect vibrations or collisions quickly and promptly upon occurrence, enabling the control system to take immediate and appropriate measures to enhance system safety.

[0003] Current vibration detection technologies mostly involve using external sensors to detect external force collisions and the resulting vibrations, using software algorithms to estimate the external force collisions and their resulting vibrations, or incorporating algorithms within the robotic arm to suppress its own vibrations. However, when using external sensors to detect external forces, existing robotic arms typically incorporate multiple torque sensors or at least one multi-degree-of-freedom sensor. The high cost of torque sensors or multi-degree-of-freedom sensors undoubtedly increases the production cost of multi-axis robotic arms. Furthermore, estimating external forces using software algorithms requires improved modeling accuracy and precision, and faces numerous challenges in practical implementation. Therefore, there is an urgent need for a low-cost, easily implemented vibration detection device or method for multi-axis robotic arms. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a vibration detection device and method for a multi-axis robotic arm.

[0005] The embodiments of the present invention provide the following technical solutions:

[0006] A vibration detection device for a multi-axis robotic arm according to an embodiment of the present invention includes:

[0007] A plurality of detection units are provided, each of which is mounted on a link of a multi-axis robotic arm. Each detection unit includes an accelerometer, and the detection unit acquires the raw data signal of the link through the accelerometer.

[0008] An information processing unit is communicatively connected to several detection units. The information processing unit is used to perform time-frequency analysis on several raw data signals acquired by several detection units to form several time-frequency analysis results, and to determine whether the corresponding connecting rod has vibration based on the several time-frequency analysis results and preset conditions.

[0009] A vibration detection method for a multi-axis robotic arm according to an embodiment of the present invention includes:

[0010] The raw data signal of each link on the multi-axis robotic arm is acquired, wherein the raw data signal is the acceleration information acquired by the accelerometer of each detection unit;

[0011] The information processing unit obtains all time-frequency analysis results formed after performing time-frequency analysis on all the original data signals. Based on all the time-frequency analysis results and preset conditions, it is determined whether the corresponding connecting rod has vibration. Herein, all the original data signals are the acceleration information sent to the information processing unit by all the detection units.

[0012] Further, obtaining all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod vibrates based on all time-frequency analysis results and preset conditions includes:

[0013] Perform frequency domain analysis on all the original data signals to obtain all frequency domain analysis results;

[0014] Based on all the frequency domain analysis results, obtain all signal energy values ​​corresponding to the frequency domain analysis results;

[0015] The maximum signal energy is obtained based on all the signal energy values, and if the maximum signal energy is greater than the threshold value Eset, it is determined that the link where the detection unit corresponding to the maximum signal energy is located has been subjected to an external force collision.

[0016] Furthermore, in obtaining all signal energy values ​​corresponding to the frequency domain analysis results based on all the aforementioned frequency domain analysis results, the frequency domain analysis results include the amplitude Ax in the X-axis direction, the frequency fx corresponding to the amplitude Ax, the amplitude Az in the Z-axis direction, and the frequency fz corresponding to the amplitude Az within a specified time period after the original data signal undergoes frequency domain analysis. The signal energy values ​​include the signal energy value E of the original data signal in the X-axis direction within the specified time period. x The signal energy value E in the Z-axis direction z ;

[0017] Calculate the signal energy value E x and signal energy value Ez The formula is:

[0018]

[0019]

[0020] Where Δf is the set frequency range.

[0021] Furthermore, after obtaining all signal energy values ​​corresponding to all the frequency domain analysis results based on all the frequency domain analysis results, the method further includes:

[0022] All synthetic signal energy values ​​are obtained based on all the aforementioned signal energy values. The maximum synthetic signal energy value is obtained based on all the aforementioned synthetic signal energy values. If the maximum synthetic signal energy value is greater than the threshold value Exz_set, it is determined that the link corresponding to the maximum synthetic signal energy value has experienced an external force collision.

[0023] Furthermore, in obtaining all synthesized signal energy values ​​based on all the aforementioned signal energy values, the formula for calculating the synthesized signal energy value is as follows:

[0024]

[0025] Among them, E x E represents the signal energy value of the original data signal in the X-axis direction within a specified time period. z E represents the signal energy value of the original data signal in the Z-axis direction within a specified time period. xz The energy value of the synthesized signal on the XZ plane of the original data signal within a specified time period.

[0026] Further, obtaining all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod vibrates based on all time-frequency analysis results and preset conditions includes:

[0027] Frequency domain analysis is performed on each of the original data signals to obtain all frequency domain analysis results. The frequency domain analysis results include, after performing frequency domain analysis on the original data signals, obtaining several amplitudes Ax in the X-axis direction and several frequencies fx corresponding to the amplitudes Ax within several specified time periods, and obtaining several amplitudes Az in the Z-axis direction and several frequencies fz corresponding to the amplitudes Az within several specified time periods.

[0028] A series of amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into an amplitude sequence, and a series of frequencies fx corresponding to the amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into a frequency sequence.

[0029] Several amplitude changes are obtained based on the amplitude sequence, and several frequency changes are obtained based on the frequency sequence;

[0030] The sum of amplitude changes is obtained based on several amplitude changes, and the sum of frequency changes is obtained based on several frequency changes;

[0031] If the sum of the amplitude changes is less than the threshold value ΔAx_limit and the sum of the frequency changes is less than the threshold value Δfx_limit, it is determined that the connecting rod where the detection unit is located, corresponding to the sum of the amplitude changes and the sum of the frequency changes, has body vibration.

[0032] Further, obtaining all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod vibrates based on all time-frequency analysis results and preset conditions includes:

[0033] Based on all the original data signals, all the synthetic components of all the detection units in the XZ plane are obtained, wherein each of the original data signals includes the X-axis original data signal αx(t) obtained by the accelerometer in the X-axis direction and the Z-axis original data signal αz(t) obtained in the Z-axis direction.

[0034] All correlation coefficients are obtained based on all the aforementioned synthetic components;

[0035] Based on all the aforementioned correlation coefficients, a correlation coefficient change curve is generated. If the correlation coefficient change curve matches the regular curve, it is determined that the link corresponding to the correlation coefficient change curve has experienced an external force collision.

[0036] Furthermore, in obtaining all the synthetic components of all the detection units in the XZ plane based on all the original data signals, the formula for obtaining the synthetic components is:

[0037] ;

[0038] In obtaining all correlation coefficients based on all the composite components, the formula for obtaining the correlation coefficients is:

[0039]

[0040] Wherein, X is one of the composite components, Y is the composite component adjacent to X, Cov(X, Y) is the covariance of X and Y, D(X) is the variance of X, and D(Y) is the variance of Y.

[0041] Furthermore, after obtaining several correlation coefficients based on several of the synthesized components, the method further includes:

[0042] Based on the aforementioned correlation coefficients, the change in correlation coefficients between two adjacent correlation coefficients and the absolute value of the change in correlation coefficients between two adjacent correlation coefficients are obtained.

[0043] Based on the positive and negative values ​​of the changes in several correlation coefficients and whether the absolute values ​​of the changes in several correlation coefficients are greater than the threshold value Δρ_thres1 or the threshold value Δρ_thres2, it is determined whether the link has been subjected to an external force collision.

[0044] Compared with existing technologies, this invention sets up a detection unit on each link and installs an acceleration sensor in the detection unit. The acceleration sensor sends the acquired raw data signal to the information processing unit, which then performs time-frequency analysis on the raw data signal to generate several time-frequency analysis results. Finally, based on the time-frequency analysis results and preset conditions, it determines whether there is vibration on the link. This solves the problem of high production cost of robotic arms caused by external sensors in existing technologies. It also solves the problem of needing to improve the accuracy and precision of modeling in existing technologies by using the information processing unit to determine the vibration of multi-axis robotic arms based on time-frequency analysis results and preset conditions. This reduces the cost of vibration detection for multi-axis robotic arms and improves the sensitivity and accuracy of vibration detection. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the structure of a vibration detection device for a multi-axis robotic arm according to an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the installation of the detection module (detection unit) and the connecting rod according to an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the structure of a six-axis robotic arm according to an embodiment of the present invention;

[0048] Figure 4 This is a connection diagram of the detection module (detection unit) and the information processing unit in an embodiment of the present invention;

[0049] Figure 5 This is a schematic diagram of the detection unit according to an embodiment of the present invention;

[0050] Figure 6 This is a logical function diagram of the detection unit and information processing unit in an embodiment of the present invention;

[0051] Figure 7 This is a structural block diagram of the information processing unit according to an embodiment of the present invention;

[0052] Figure 8This is a logical function diagram of the information processing unit according to an embodiment of the present invention;

[0053] Figure 9 This is a flowchart (I) of the vibration detection method according to an embodiment of the present invention.

[0054] Figure 10 This is a flowchart (II) of the vibration detection method according to an embodiment of the present invention;

[0055] Figure 11 This is a flowchart (III) of the vibration detection method according to an embodiment of the present invention;

[0056] Figure 12 A flowchart (IV) of the vibration detection method according to an embodiment of the present invention.

[0057] Figure 13 This is a fault determination and control flowchart of a vibration detection method for a multi-axis robotic arm according to an embodiment of the present invention.

[0058] Figure 14 This is a flowchart (V) of the vibration detection method according to an embodiment of the present invention;

[0059] Figure 15 This is a schematic diagram of a regular curve illustrating an external force collision and the vibration detection method induced by the multi-axis robotic arm according to an embodiment of the present invention.

[0060] Figure 16 This is a flowchart (VI) of the vibration detection method according to an embodiment of the present invention;

[0061] Figure 17 This is a determination process for a method of detecting external force collisions and the resulting vibrations in a multi-axis robotic arm, according to an embodiment of the present invention. Detailed Implementation

[0062] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0063] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0064] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0065] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0066] Additionally, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that practice can be carried out without these specific details.

[0067] Example 1

[0068] This invention provides a vibration detection device for a multi-axis robotic arm, such as... Figure 1 As shown, the system includes several detection units 10 and an information processing unit 20. Each detection unit 10 is mounted on a link of the multi-axis robotic arm. Each detection unit 10 includes an accelerometer 13, which acquires the raw data signal of the corresponding link. The information processing unit 20 is communicatively connected to each of the detection units 10. The information processing unit 20 performs time-frequency analysis on the raw data signals acquired by the detection units 10 to generate several time-frequency analysis results, and determines whether the corresponding link vibrates based on the time-frequency analysis results and preset conditions.

[0069] Among them, time-frequency analysis includes time-domain analysis and frequency-domain analysis; vibration includes the vibration of the robotic arm itself and the vibration caused by external force collisions.

[0070] In some embodiments, the inside of the connecting rod is configured as a hollow structure, and the detection unit 10 is mounted on the inner wall of the connecting rod.

[0071] Each link of the multi-axis robotic arm is equipped with a detection unit 10.

[0072] In some embodiments, when the detection unit 10 is installed, the detection unit 10 establishes an XYZ coordinate system with its own plane as the XY plane, and the Y-axis of the XYZ coordinate system has a certain installation angle with the central axis of the corresponding connecting rod, so that the detection unit 10 can obtain the detection signal.

[0073] This embodiment of the invention takes the plane in which the detection unit 10 is located as the XY plane as an example. The purpose of this embodiment is to obtain the detection signal in the direction perpendicular to the central axis of the connecting rod. Therefore, no matter how the coordinate system is established, as long as the detection unit can detect the detection signal in the direction perpendicular to the central axis of the connecting rod, it should fall within the protection scope of this embodiment of the invention.

[0074] In a preferred embodiment of the present invention, the Y-axis direction of the XYZ coordinate system in which each detection unit 10 is located is parallel to the central axis of the corresponding connecting rod, and the XZ plane of the XYZ coordinate system in which each detection unit 10 is located is perpendicular to the central axis of the corresponding connecting rod.

[0075] For example, such as Figure 2 As shown, taking the first link 31 and the second link 32 as examples, the first detection module 101 (detection unit) is installed on the inner wall of the first link 31, and the second detection module 102 (detection unit) is installed on the inner wall of the second link 32. The XZ plane of the XYZ coordinate system where the first detection module 101 is located is perpendicular to the central axis of the first link 31, and the Y-axis direction of the first detection module 101 is parallel to the central axis of the first link 31. The XZ plane of the XYZ coordinate system where the second detection module 102 is located is perpendicular to the central axis of the second link 32, and the Y-axis direction of the second detection module 102 is parallel to the central axis of the second link 32. Thus, the above installation method helps to perform signal processing more accurately and obtain more reliable processing results.

[0076] The information processing unit 20 is an information data processing module, and the information data processing module has a data processing algorithm inside.

[0077] In this embodiment of the invention, there are no requirements on the installation method or location of the information processing unit 20. For example, the information processing unit 20 can be installed in the control cabinet of the robot controller or in the internal space of the robot base.

[0078] The information processing unit 20 can be connected to several detection units 10 via several communication cables, and the communication cables can be connected in a daisy chain or other manner.

[0079] The information processing unit 20 communicates with the robot controller, such as the information data processing module and the robot controller exchanging data via an industrial communication bus.

[0080] The embodiments of the present invention do not restrict the communication connection method between the information processing unit 20 and the detection unit 10, or the communication connection method between the information processing unit 20 and the robot controller. That is, regardless of the communication method used, the essence is that each detection unit 10 transmits data to the information processing unit 20, and the information processing unit 20 transmits the judgment result to the robot controller.

[0081] For example, such as Figures 3-4 As shown, in the case of a six-axis robotic arm, where the five links of the six-axis robotic arm are: first link 31, second link 32, third link 33, fourth link 34, and fifth link 35, five detection modules (detection units) can be set up, namely: first detection module 101, second detection module 102, third detection module 103, fourth detection module 104, and fifth detection module 105. Then, the first detection module 101 is set on the first link 31, the second detection module 102 is set on the second link 32, ..., and the fifth detection module 105 is set on the fifth link 35. Thus, the five detection modules can respectively acquire the raw data signals of the five links and can transmit the raw data signals to the signal processing unit 20 through the communication interface 201. The signal processing unit 20 sends the judgment result to the robot controller through the data communication interface connected to the robot controller.

[0082] Furthermore, such as Figures 5-6 As shown, the detection unit 10 includes a mounting base 11, a circuit board 12, an accelerometer 13, a low-pass filter 14, and a communication interface 15. The mounting base 11 is mounted on the connecting rod of the corresponding multi-axis robotic arm; the circuit board 12 is mounted on the mounting base 11; the accelerometer 13 is integrated on the circuit board 12 and is used to acquire acceleration information in three directions; the low-pass filter 14 is disposed within the circuit board 12 and is used to process the acceleration information to form raw data signals; the communication interface 15 is integrated on the circuit board 12 and is used to transmit the raw data signals to the information processing unit 20.

[0083] The mounting base plate 11 is used to fix the circuit board 12, the acceleration sensor 13 and the communication interface 15 to the connecting rod. For example, the mounting base plate 11 has mounting holes at its four corners, and the operator can pass screws or bolts through the mounting holes to connect to the side wall of the connecting rod.

[0084] When the mounting base plate 11 is installed on the inner wall of the robot link, thermal grease is added between the mounting base plate 11 and the link to facilitate the transfer of heat generated by the circuit board 12 to the link, thereby enhancing the heat dissipation capacity of the detection unit 10.

[0085] Among them, the acceleration sensor 13 is an acceleration sensor chip, which is inexpensive and helps to reduce the cost of the vibration detection device of the multi-axis robotic arm of the present invention, so as to solve the problem of high cost caused by the use of torque sensors or multi-degree-of-freedom sensors in the prior art.

[0086] The accelerometer 13 is located on the XY plane of the XYZ coordinate system where the detection unit 10 is located, which facilitates the processing of the acquired detection signal, that is, the processing of the acquired acceleration information.

[0087] The low-pass filter 14 is a digital filter and is located in the processor chip integrated on the circuit board 12. It is used to process the detection signal transmitted from the acceleration sensor 13 to form the raw data signal.

[0088] The communication interface 15 is a signal interface used to connect to the communication cable, and then the communication interface 15 is connected to the information processing unit 20 through the communication cable.

[0089] For example, such as Figure 6 As shown, after the accelerometer 13 acquires the X-axis, Y-axis, and Z-axis detection signals, the low-pass filter 14 processes these signals separately to form the raw X-axis data signal αx(t), the raw Y-axis data signal αy(t), and the raw Z-axis data signal αz(t). Finally, the communication interface 15 sends αx(t), αy(t), and αz(t) to the information processing unit 20. Specifically, the X-axis low-pass filter represents the processing of the X-axis detection signal, the Y-axis low-pass filter represents the processing of the Y-axis detection signal, and the Z-axis low-pass filter represents the processing of the Z-axis detection signal.

[0090] like Figure 7 As shown, the information processing unit 20 includes a DSP (digital signal processor), a communication unit connected to the robot controller, and a communication unit connected to the detection module.

[0091] Furthermore, the information processing unit 20 is also configured with a large-capacity synchronous dynamic random-access memory (SDRAM) and a flash disk.

[0092] The information processing unit 20 is used to acquire the raw data signal sent by the detection unit 10, and then process the raw data signal based on the internal data processing algorithm.

[0093] like Figure 8As shown, Figure 8 The image illustrates a specific implementation of how the information processing unit 20 of this embodiment performs data processing on the original data signal.

[0094] The information processing unit 20 acquires the raw data signals sent by the communication unit (the communication interface connected to the detection module) (e.g., acquiring the raw data signals αx1, αy1, αz1, ... sent by the first detection module installed on the first link, and the raw data signals αx5, αy5, αz5 sent by the fifth detection module installed on the fifth link). Then, the information processing unit 20 processes the raw data signals based on frequency domain analysis to obtain the highest amplitude point A and frequency f within the time period Tc (e.g., acquiring the amplitude Ax1 and frequency fx1 corresponding to the raw data signal αx1, and the amplitude Az1 and frequency fz1 corresponding to the raw data signal αz1 within the time period Tc). Subsequently, the information processing unit 20 calculates the energy spectrum E within the range of f ± Δf (e.g., calculating the energy spectrum Ex1 within the range of fx1 ± Δf). The highest amplitude point within the time period Tc is the aforementioned maximum amplitude value.

[0095] This invention acquires the raw data signal of each link of a multi-axis robotic arm through the acceleration sensor of the detection unit, then performs time-frequency analysis on the raw data signal to form a time-frequency analysis result, and determines whether the corresponding link has vibration based on the time-frequency analysis result and preset conditions. This solves the problem of high cost caused by the use of torque sensors or multi-degree-of-freedom sensors in the prior art, and also eliminates the need for software algorithm modeling, thus reducing the difficulty of detecting link vibration.

[0096] Example 2

[0097] This embodiment provides a vibration detection method for a multi-axis robotic arm, which uses the vibration detection device provided in Embodiment 1 to detect the body vibration of the connecting rod and the vibration caused by external force collisions.

[0098] Figure 9 This is a flowchart (I) of the vibration detection method according to an embodiment of the present invention, as follows: Figure 9 As shown, the vibration detection method includes:

[0099] Step S102: Obtain the raw data signal on each link of the multi-axis robotic arm, wherein the raw data signal is the acceleration information obtained by the acceleration sensor of each detection unit;

[0100] Step S104: Obtain all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all raw data signals respectively, and determine whether the corresponding connecting rod has vibration based on all time-frequency analysis results and preset conditions. Here, all raw data signals are the acceleration information sent by all detection units to the information processing unit.

[0101] In step S102, the raw data signal can be the output signal formed after processing the acceleration information acquired by the accelerometer.

[0102] In step S104, the time-frequency analysis includes time-domain analysis and frequency-domain analysis, and the vibration includes the body vibration of the multi-axis robotic arm and the vibration caused by the multi-axis robotic arm being impacted by external forces.

[0103] Figure 10 This is a flowchart (II) of the vibration detection method for a multi-axis robotic arm according to an embodiment of the present invention, as shown below. Figure 10 As shown, step S104 includes the following steps to determine whether the link has experienced an external force collision based on the frequency domain analysis results:

[0104] Step S202: Perform frequency domain analysis on all raw data signals to obtain all frequency domain analysis results;

[0105] Step S204: Based on all frequency domain analysis results, obtain all signal energy values ​​corresponding to the frequency domain analysis results;

[0106] Step S206: Obtain the maximum signal energy value based on all signal energy values, and if the maximum signal energy value is greater than the threshold value Eset, determine that the link where the detection unit corresponding to the maximum signal energy value is located has been subjected to an external force collision.

[0107] In step S102, frequency domain analysis is performed on the original data signal to obtain the frequency domain analysis result, which is to obtain the amplitude A and the frequency corresponding to the amplitude A of the original data signal within a specified time period.

[0108] For example, within a specified time period, obtain the amplitude Ax of the raw data signal on the X-axis and the frequency fx corresponding to the amplitude Ax.

[0109] In step S204, the frequency domain analysis results include the amplitude Ax and the corresponding frequency fx in the X-axis direction within a specified time period after frequency domain analysis of the original data signal, the amplitude Az and the corresponding frequency fz in the Z-axis direction within the specified time period, and the signal energy value includes the signal energy value E of the original data signal in the X-axis direction within the specified time period. x The signal energy value E in the Z-axis direction z Calculate the signal energy value E x and signal energy value E z The formula is:

[0110]

[0111]

[0112] Where Δf is the set frequency range.

[0113] Δf can be set flexibly.

[0114] Wherein, amplitude A is the value of the highest amplitude point within the specified time period; amplitude Ax is the value of the highest amplitude point in the X-axis direction within the specified time period; amplitude Az is the value of the highest amplitude point in the Z-axis direction within the specified time period.

[0115] For step S108, the threshold value Eset can be flexibly set according to the actual situation.

[0116] The following is a specific implementation of steps S202 to S206 of this invention:

[0117] Taking a 6-axis robotic arm as an example, the five links of the 6-axis robotic arm are: the first link, the second link, the third link, the fourth link, and the fifth link. After the detection unit installed on the first link acquires the detection signal, the detection unit processes the detection signal to form the original data signal α of the first link in the X-axis direction. x1 (t) The original data signal α in the Y-axis direction y1 (t) and the original data signal α in the Z-axis direction. z1 (t), then the information processing unit processes α x1 (t), α z1 (t) Perform frequency domain analysis to obtain α x1 (t) The amplitude Ax1, the frequency fx1 corresponding to the amplitude Ax1, and the α obtained within the specified time period Tc. z1 (t) The amplitude Az1 and the frequency fz1 corresponding to the amplitude Az1 within the specified time period Tc are then used by the information processing unit to obtain the signal energy value E of the first link on the X-axis based on Ax1 and fx1. x1 The signal energy value of the first link on the Z-axis is obtained based on Az1 and fz1;

[0118] The formula for obtaining the signal energy value of the first link on the X-axis is as follows:

[0119]

[0120] The formula for obtaining the signal energy value of the first link on the Z-axis is as follows:

[0121]

[0122] Since the Y-axis of the detection unit is parallel to the central axis of the first link, the detection data of the first link in the Y-axis direction is not obvious when the first link vibrates. Therefore, the data of the detection unit in the Y-axis direction can be ignored, thus simplifying the data processing process.

[0123] Through the above steps, the signal energy value E of the first link in the X-axis direction can be obtained. x1 and the signal energy value E in the Z-axis direction z1 Then, following the steps described above, the signal energy value E of the original data signal corresponding to the second link in the X-axis direction is obtained sequentially. x2 and the signal energy value E in the Z-axis direction z2 ..., the signal energy value E of the fifth link in the X-axis direction x5 and the signal energy value E in the Z-axis direction z5 .

[0124] According to the obtained E x1 E x2 E x3 E x4 E x5 E z1 E z2 E z3 E z4 E z5 Find the maximum value E_max (maximum signal energy). If the maximum value E_max is greater than the threshold value Eset, then it is determined that the link where the detection unit corresponding to E_max is located has been subjected to an external force collision.

[0125] The threshold value Eset can be set based on experience or calibration.

[0126] Steps S202 to S206 perform frequency domain analysis on the raw data signal obtained from the accelerometer to obtain the maximum signal energy of the link, thereby enabling the determination of whether the link has been subjected to an external force collision based on the maximum signal energy value. This solves the problems of high cost and high-precision modeling required by the external sensor in the prior art.

[0127] Figure 11 The flowchart (III) of the vibration detection method according to an embodiment of the present invention is as follows: Figure 11 As shown, after step S204, step S208 is also included to replace step S206 described above:

[0128] Step S208: Obtain all synthetic signal energy values ​​based on all signal energy values, obtain the maximum synthetic signal energy value based on all synthetic signal energy values, and determine that the link corresponding to the maximum synthetic signal energy value has been subjected to an external force collision if the maximum synthetic signal energy value is greater than the threshold value Exz_set.

[0129] The formula for calculating the maximum energy of the synthesized signal is as follows:

[0130]

[0131] Among them, E x E is the signal energy value on the X-axis obtained according to the aforementioned steps. z E is the signal energy value on the Z-axis obtained according to the aforementioned steps. xz This represents the energy value of the synthesized signal in the XZ plane within a specified time period of the original data signal.

[0132] Several signal energy values ​​E are obtained in accordance with the aforementioned feasible method. x1 E x2 E x3 E x4 E x5 E z1 E z2 E z3 E z4 E z5 Subsequently, based on the aforementioned signal energy value, the composite signal energy value E of the first link on the XZ plane can be obtained. xz1 ;

[0133] Where, calculate E xz1 The formula is as follows:

[0134] ;

[0135] Then, based on the above steps, the synthesized signal energy value E corresponding to the second link can be obtained. xz2 The energy value E of the synthesized signal corresponding to the fifth link, ... xz5 Then obtain E. xz1 E xz2 E xz3 E xz4 E xz5 The maximum value of the synthesized signal energy is determined, and if the maximum value of the synthesized signal energy is greater than the threshold value Exz_set, it is determined that the link corresponding to the maximum value of the synthesized signal energy has been subjected to an external force collision.

[0136] Step S208 obtains the maximum value of the composite signal energy of the link on the XZ plane, and determines whether the link has been subjected to an external force collision based on the relationship between the maximum value of the composite signal energy and the threshold value Exz_set.

[0137] By detecting whether the connecting rod has been subjected to external force collision through the above steps, the problem of high cost caused by the need to use torque sensors or multi-degree-of-freedom sensors to detect vibrations caused by external force collisions in the existing technology is solved. By reasonably processing the signals obtained by the acceleration sensor, the problem of difficult data processing of the acceleration sensor is also solved. At the same time, the problem of modeling required for vibration detection using software algorithms in the existing technology is avoided.

[0138] Figure 12 The flowchart (IV) of the vibration detection method according to an embodiment of the present invention is as follows: Figure 12 As shown, step S104 also includes steps S302 to S310, to examine and analyze the values ​​in the frequency domain within the time domain to determine the vibration of the multi-axis robotic arm:

[0139] Step S302: Perform frequency domain analysis on each original data signal to obtain all frequency domain analysis results. The frequency domain analysis results include, after performing frequency domain analysis on the original data signal, obtaining several amplitudes Ax in the X-axis direction and several frequencies fx corresponding to several amplitudes Ax within several specified time periods, and obtaining several amplitudes Az in the Z-axis direction and several frequencies fz corresponding to several amplitudes Az within several specified time periods.

[0140] Step S304: Form an amplitude sequence from several amplitudes Ax that are greater than the amplitude setting value Ax_set, and form a frequency sequence from several frequencies fx corresponding to several amplitudes Ax that are greater than the amplitude setting value Ax_set;

[0141] Step S306: Obtain several amplitude changes based on the amplitude sequence and several frequency changes based on the frequency sequence;

[0142] Step S308: Obtain the sum of amplitude changes based on several amplitude changes, and obtain the sum of frequency changes based on several frequency changes;

[0143] Step S310: If the sum of amplitude changes is less than the threshold value ΔAx_limit and the sum of frequency changes is less than the threshold value Δfx_limit, determine that the connecting rod where the detection unit corresponding to the sum of amplitude changes and the sum of frequency changes is located has body vibration.

[0144] In step S302, the original data signal is analyzed and processed within a preset time period, that is, the original data signal is processed within a certain specified time period to examine the value in the frequency domain in the time domain in order to determine whether the robotic arm has body vibration.

[0145] In step S304, the amplitude setting value Ax_set is a threshold value set when mechanical vibration occurs. An amplitude Ax higher than the amplitude setting value Ax_set is considered to be a body vibration or external force collision of the link, while an amplitude lower than the amplitude setting value Ax_set is considered to be no body vibration or external force collision of the robotic arm.

[0146] By selecting amplitude values ​​Ax that are greater than the amplitude setting value Ax_set, it is indicated that the detection signal detected by the accelerometer at these frequency points has a larger amplitude in the frequency domain. In other words, the detection signal detected by the accelerometer may be the vibration caused by the robotic arm body or the vibration caused by an external force collision. Since the duration of the body vibration is longer than the duration of the vibration caused by the external force collision, and the body vibration is continuous, it is necessary to obtain several amplitude values ​​Ax within a certain time period in step S112, that is, to examine whether the link has experienced body vibration within a relatively long preset time period.

[0147] In step S306, the frequency change is the change between two adjacent amplitudes Ax.

[0148] For step S310, based on the increments between the previously selected amplitude values ​​Ax, if the sum of these increments between amplitude values ​​Ax is lower than the threshold value ΔAx_limit, it means that the change in amplitude value Ax is basically consistent within a certain specified time period. Furthermore, if the sum of frequency changes is lower than the threshold value Δfx_limit, it means that the frequency changes are also basically consistent and are all within the set range, thus conforming to the characteristics of the robotic arm body vibration.

[0149] A specific implementation of steps S302 to S310 in this embodiment of the invention is as follows;

[0150] Frequency domain analysis is performed on the raw data signal sent by the detection unit installed on the connecting rod, and the frequency domain analysis results are obtained within a preset time period T. The preset time period T includes N specified time periods Tc, that is, T=N*Tc.

[0151] The frequency domain analysis results include obtaining N amplitude values ​​Ax and N frequencies fx corresponding to the amplitude values ​​Ax within N specified time periods Tc.

[0152] Each amplitude value Ax represents the highest amplitude point in the X-axis direction within a specified time period Tc. Consequently, N amplitude values ​​Ax can be obtained within N specified time periods Tc.

[0153] Within the frequency domain analysis results, select M amplitude values ​​Ax that are greater than the amplitude setting value Ax_set, and denot the M amplitude values ​​Ax as: Axx(1), Axx(2), ..., Axx(M), and denot the M frequency sequence values ​​fx corresponding to the M amplitude values ​​Ax as: fxx(1), fxx(2), ..., fxx(M).

[0154] From the above data, we can derive the amplitude changes of M-1 values:

[0155] ΔAx(1) = |Axx(2) - Axx(1)|;

[0156] ΔAx(2) = |Axx(3) - Axx(2)|; ......

[0157] ΔAx(M-1)= |Axx(M)- Axx(M-1)|;

[0158] Then the sum of the M-1 amplitude changes is:

[0159] ΔAx= ΔAx(1)+ ΔAx(2)+…+ ΔAx(M-1);

[0160] Similarly, M-1 frequency changes can be obtained:

[0161] Δfx(1) = |fxx(2) - fxx(1)|;

[0162] Δfx(2) = |fxx(3) - fxx(2)|; ......

[0163] Δfx(M-1)= |fx(M)- fx(M-1)|;

[0164] The sum of the M-1 frequency changes is:

[0165] Δfx= Δfx(1)+ Δfx(2)+…+ Δfx(M-1);

[0166] Threshold values ​​are set for the sum of amplitude changes and the sum of frequency changes: ΔAx_limit; Δfx_limit;

[0167] If the sum of amplitude changes ΔAx is less than the threshold value ΔAx_limit and the sum of frequency changes Δfx is less than the threshold value Δfx_limit, then it is determined that the connecting rod where the detection unit corresponding to the original data signal is located has body vibration.

[0168] Finally, based on the aforementioned method, the same analysis and judgment can be performed on other links respectively, thereby determining whether the links of the multi-axis robotic arm have their own vibration.

[0169] like Figure 13 As shown, we can first determine the vibration caused by the external force collision, and then determine the vibration of the robotic arm itself.

[0170] Specifically, after acquiring the frequency domain processing result data, it is first determined whether the vibration is caused by an external force collision. If the vibration is caused by an external force collision, the determination result is transmitted to the robot communication bus module. If it is determined that the vibration is not caused by an external force collision, it is determined whether it is mechanical vibration (body vibration). If it is mechanical vibration, the determination result is transmitted to the robot communication bus module. If it is not mechanical vibration, the frequency domain processing result data is reacquired. Thus, this embodiment can accurately determine the vibration type so that the robot can execute different operation instructions according to the vibration type.

[0171] Figure 14 The flowchart (V) of the vibration detection method according to an embodiment of the present invention is as follows: Figure 14 As shown, step S104 also includes steps S402 to S406, to determine whether the multi-axis robotic arm has been subjected to an external force collision based on the time-domain analysis results:

[0172] Step S402: Based on all the original data signals, obtain all the synthetic components of all detection units on the XZ plane, wherein each original data signal includes the X-axis original data signal αx(t) obtained by the accelerometer in the X-axis direction and the Z-axis original data signal αz(t) obtained in the Z-axis direction.

[0173] Step S404: Obtain all correlation coefficients based on all composite components;

[0174] Step S406: Generate a correlation coefficient change curve based on all correlation coefficients, and if the correlation coefficient change curve matches the regular curve, determine that the link corresponding to the correlation coefficient change curve has experienced an external force collision.

[0175] The formula for calculating the synthesized component in step S402 is as follows:

[0176]

[0177] The formula for calculating the correlation coefficient in step S404 is as follows:

[0178]

[0179] Where X is a composite component, Y is a composite component adjacent to X, Cov(X,Y) is the covariance of X and Y, D(X) is the variance of X, and D(Y) is the variance of Y.

[0180] Among them, D(X)=E(XE(X)) 2 , Cov(X,Y)=E(XY)- E(X)E(Y).

[0181] The correlation coefficient indicates the correlation between the collision effects of two adjacent links. The larger the correlation coefficient, the stronger the correlation between the collision effects of the two adjacent links.

[0182] The following is a specific implementation of steps S402 to S406 of this embodiment of the invention:

[0183] With detection units installed on all five links of the 6-axis robotic arm, the detection unit on the first link processes the acquired detection signals to obtain the raw data signal α that varies with time in the X-axis direction. x1 (t) and the original data signal α that varies with time along the Z-axis. z1 (t), and then based on the formula

[0184]

[0185] Obtain the composite component αxz1(t) of the detection signal in the XZ plane.

[0186] Based on the aforementioned steps, the resultant components αxz2(t), ..., and the resultant component αxz5(t) of the second link in the XZ plane are obtained sequentially.

[0187] The correlation coefficient between the first and second links is obtained based on αxz1(t) and αxz2(t), and the calculation formula is as follows:

[0188]

[0189] Where, ρ 12 This is the correlation coefficient between the first link and the second link.

[0190] Finally, the correlation coefficient ρ between the second and third links is calculated sequentially according to the aforementioned steps. 23 The correlation coefficient ρ between the third and fourth links 34 The correlation coefficient ρ between the fourth and fifth links 45 .

[0191] like Figure 15As shown, the information processing unit can generate regular curves based on the correlation coefficients generated after the five links are collided, namely: L1, L2, L3, L4, and L5. Then, when detecting whether a link has been collided, the information processing unit only needs to determine which regular curve matches the correlation coefficient change curve generated after the link is collided to know which link has been collided. Here, the regular curves represent the changing trends of several correlation coefficients.

[0192] The process of determining which regular curve the correlation coefficient change curve matches mainly involves judging whether the change trends of the correlation coefficient change curve and the regular curve are the same or similar. If the change trends of the correlation coefficient change curve and the regular curve are the same or similar, then the correlation coefficient change curve and the regular curve are matched; if the change trends of the correlation coefficient change curve and the regular curve are not the same or similar, then they are not matched.

[0193] The implementation method for obtaining rule curves L1~L5 is as follows:

[0194] In the case of the first link being hit, the correlation coefficient ρ after the first link is hit is obtained sequentially. 12 ρ 23 ρ 34 ρ 45 Then, based on the correlation coefficient ρ obtained after the first link is collided... 12 ρ 23 ρ 34 ρ 45 Obtain the rule curve L1; in the case of the second link being collided, sequentially obtain the correlation coefficient ρ after the second link is collided. 12 ρ 23 ρ 34 ρ 45 Then according to ρ 12 ρ 23 ρ 34 ρ 45 Obtain the regular curve L2, and then obtain the regular curves L3, L4, and L5 in sequence.

[0195] For example, in the event that a link of a 6-axis robotic arm is subjected to an external force collision, obtain the four correlation coefficients ρ of the link after the collision. 12 ρ 23 ρ 34 ρ 45 Based on the four correlation coefficients, correlation coefficient change curves are obtained. These curves are then compared sequentially with regular curves L1 through L5. The curve showing the highest degree of consistency between the trend of the correlation coefficient change curve and the trend of regular curve L3 is considered the most suitable.23 ρ 34 The value of ρ 12 ρ 45 High, ρ 23 With ρ 34 If the value is close to the value, it can be determined that the third link has been impacted by an external force.

[0196] Figure 16 The flowchart (six) of the vibration detection method according to an embodiment of the present invention is as follows: Figure 16 As shown, steps S408 to S410 are included after step S404 to replace step S406:

[0197] Step S408: Based on several correlation coefficients, obtain the change in correlation coefficients between two adjacent correlation coefficients and the absolute value of the change in correlation coefficients between two adjacent correlation coefficients.

[0198] Step S410: Determine whether the link has been subjected to an external force collision based on the positive and negative values ​​of several correlation coefficient changes and whether the absolute values ​​of several correlation coefficient changes are greater than the threshold value Δρ_thres1 or the threshold value Δρ_thres2.

[0199] The threshold value Δρ_thres1 is a set value for judging whether two correlation coefficients are within the same range of influence of change; if the change value of the correlation coefficient is within the set value, it means that the two correlation coefficients are relatively close.

[0200] The threshold value Δρ_thres2 is a set value for judging whether two correlation coefficients are outside the range of large variation; if the variation value of two adjacent correlation coefficients is higher than this set value, it means that the two correlation coefficients are not very correlated.

[0201] Because the magnitude of the actual external force collision varies, the amplitude represented by the collected data also varies. Therefore, in the actual implementation process, a relative threshold value for the change between correlation coefficients can be set to more accurately determine which link has been subjected to an external force collision.

[0202] Taking a 6-axis robotic arm as an example, the following is a specific implementation of steps S408 to S410:

[0203] like Figure 16 As shown, when a link is struck by an external force, the information processing unit obtains the composite components α of the five links on the XZ plane according to the aforementioned steps. xz1 (t), α xz2 (t), α xz3 (t), α xz4 (t), α xz5 In the case of (t), according to α xz1 (t), αxz2 (t), α xz3 (t), α xz4 (t), α xz5 (t) Obtain the correlation coefficient ρ between the 5 links. 12 ρ 23 ρ 34 ρ 45 Then obtain ρ 12 and ρ 23 The relative change Δρ between 1223 ρ 23 and ρ 34 The relative change Δρ between 2334 ρ 34 and ρ 45 The relative change Δρ between 3445 , where Δρ 1223 =ρ 12 -ρ 23 , Δρ 2334 =ρ 23 -ρ 34 , Δρ 3445 =ρ 34 -ρ 45 .

[0204] Finally at Δρ 1223 >0, Δρ 2334 >0, Δρ 3445 >0 and |Δρ 1223 |>Δρ_thres2、|Δρ 2334 |>Δρ_thres2、|Δρ 2334 If |>Δρ_thres2, then the first link is determined to have collided; if Δρ 2334 >0, Δρ 3445 >0 and |Δρ 1223 |≤Δρ_thres1、|Δρ 2334 |>Δρ_thres2、|Δρ 2334 If |>Δρ_thres2, then the second link is determined to have collided; if Δρ 1223 <0, Δρ 3445 >0 and |Δρ 1223 |>Δρ_thres2、|Δρ 2334 |≤Δρ_thres1、|Δρ 3445 If |>Δρ_thres2, then the third link is determined to have collided; if Δρ 1223 <0, Δρ 2334 <0 and |Δρ 1223 |>Δρ_thres2、|Δρ 2334 |≤Δρ_thres2、|Δρ2334 If |≤Δρ_thres1, then the fourth link is determined to have experienced an external force collision; if Δρ 1223 <0, Δρ 2334 <0, Δρ 3445 <0 and |Δρ 1223 |>Δρ_thres2、|Δρ 2334 |>Δρ_thres2、|Δρ 2334 If |>Δρ_thres2, then the fifth link is determined to have experienced an external force collision. Here, Δρ_thres1 is the threshold value Eset, and Δρ_thres2 is the threshold value Δρ_thres2.

[0205] This embodiment uses the above method to determine which link has collided by comparing the correlation coefficient or the change in the correlation coefficient with preset conditions, thereby solving the problem of high-precision modeling required for calculating external force collisions using algorithms in the prior art.

[0206] In this specification, the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the product embodiments described later, since they correspond to the methods, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions in the system embodiments.

[0207] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vibration detection device for a multi-axis robotic arm, characterized in that, include: A plurality of detection units are provided, each of which is mounted on a link of a multi-axis robotic arm. Each detection unit includes an accelerometer, and the detection unit acquires the raw data signal of the link through the accelerometer. An information processing unit is communicatively connected to several detection units. The information processing unit is used to perform time-frequency analysis on several raw data signals acquired by several detection units to form several time-frequency analysis results, and to determine whether the corresponding connecting rod has vibration based on several time-frequency analysis results and preset conditions. The information processing unit can be configured to perform the following methods: Frequency domain analysis is performed on each of the original data signals to obtain all frequency domain analysis results. The frequency domain analysis results include, after performing frequency domain analysis on the original data signals, obtaining several amplitudes Ax in the X-axis direction and several frequencies fx corresponding to the amplitudes Ax within several specified time periods, and obtaining several amplitudes Az in the Z-axis direction and several frequencies fz corresponding to the amplitudes Az within several specified time periods. A series of amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into an amplitude sequence, and a series of frequencies fx corresponding to the amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into a frequency sequence. Several amplitude changes are obtained based on the amplitude sequence, and several frequency changes are obtained based on the frequency sequence; The sum of amplitude changes is obtained based on several amplitude changes, and the sum of frequency changes is obtained based on several frequency changes; If the sum of the amplitude changes is less than the threshold value ΔAx_limit of amplitude changes and the sum of the frequency changes is less than the threshold value Δfx_limit of frequency changes, it is determined that the connecting rod where the detection unit corresponding to the sum of the amplitude changes and the sum of the frequency changes is located has body vibration.

2. A vibration detection method for a multi-axis robotic arm, characterized in that, include: The raw data signal of each link on the multi-axis robotic arm is acquired, wherein the raw data signal is the acceleration information acquired by the accelerometer of each detection unit; The information processing unit obtains all time-frequency analysis results after performing time-frequency analysis on all the original data signals respectively, and determines whether the corresponding connecting rod has vibration based on all the time-frequency analysis results and preset conditions. Herein, all the original data signals are the acceleration information sent by all the detection units to the information processing unit. The step of acquiring all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod has vibration based on all time-frequency analysis results and preset conditions, includes at least the following steps: Frequency domain analysis is performed on each of the original data signals to obtain all frequency domain analysis results. The frequency domain analysis results include, after performing frequency domain analysis on the original data signals, obtaining several amplitudes Ax in the X-axis direction and several frequencies fx corresponding to the amplitudes Ax within several specified time periods, and obtaining several amplitudes Az in the Z-axis direction and several frequencies fz corresponding to the amplitudes Az within several specified time periods. A series of amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into an amplitude sequence, and a series of frequencies fx corresponding to the amplitude values ​​Ax that are greater than the amplitude setting value Ax_set are formed into a frequency sequence. Several amplitude changes are obtained based on the amplitude sequence, and several frequency changes are obtained based on the frequency sequence; The sum of amplitude changes is obtained based on several amplitude changes, and the sum of frequency changes is obtained based on several frequency changes; If the sum of the amplitude changes is less than the threshold value ΔAx_limit of amplitude changes and the sum of the frequency changes is less than the threshold value Δfx_limit of frequency changes, it is determined that the connecting rod where the detection unit corresponding to the sum of the amplitude changes and the sum of the frequency changes is located has body vibration.

3. The vibration detection method according to claim 2, characterized in that, The process of obtaining all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod vibrates based on all the time-frequency analysis results and preset conditions, further includes: Perform frequency domain analysis on all the original data signals to obtain all frequency domain analysis results; Based on all the frequency domain analysis results, obtain all signal energy values ​​corresponding to the frequency domain analysis results; The maximum signal energy is obtained based on all the signal energy values. If the maximum signal energy is greater than the threshold value Eset of the signal energy, it is determined that the link where the detection unit corresponding to the maximum signal energy is located has been subjected to an external force collision.

4. The vibration detection method according to claim 3, characterized in that, In obtaining all signal energy values ​​corresponding to the frequency domain analysis results based on all the aforementioned frequency domain analysis results, the frequency domain analysis results include the amplitude Ax in the X-axis direction, the frequency fx corresponding to the amplitude Ax, the amplitude Az in the Z-axis direction, and the frequency fz corresponding to the amplitude Az, after the original data signal has undergone frequency domain analysis, within a specified time period. The signal energy values ​​include the signal energy value E of the original data signal in the X-axis direction within the specified time period. x The signal energy value E in the Z-axis direction z ; Calculate the signal energy value E x and the signal energy value E z The formula is: Where Δf is the set frequency range.

5. The vibration detection method according to claim 3, characterized in that, After obtaining all signal energy values ​​corresponding to the frequency domain analysis results based on all the frequency domain analysis results, the method further includes: All synthetic signal energy values ​​are obtained based on all the aforementioned signal energy values. The maximum synthetic signal energy value is obtained based on all the aforementioned synthetic signal energy values. If the maximum synthetic signal energy value is greater than the threshold value Exz_set of the synthetic signal energy value, it is determined that the link corresponding to the maximum synthetic signal energy value has experienced an external force collision.

6. The vibration detection method according to claim 5, characterized in that, In obtaining all synthesized signal energy values ​​based on all the aforementioned signal energy values, the formula for calculating the synthesized signal energy value is as follows: Among them, E x E represents the signal energy value of the original data signal in the X-axis direction within a specified time period. z E represents the signal energy value of the original data signal in the Z-axis direction within a specified time period. xz The energy value of the synthesized signal on the XZ plane of the original data signal within a specified time period.

7. The vibration detection method according to claim 2, characterized in that, The process of obtaining all time-frequency analysis results generated by the information processing unit after performing time-frequency analysis on all the original data signals, and determining whether the corresponding connecting rod vibrates based on all the time-frequency analysis results and preset conditions, further includes: Based on all the original data signals, all the synthetic components of all the detection units in the XZ plane are obtained, wherein each of the original data signals includes the X-axis original data signal αx(t) obtained by the accelerometer in the X-axis direction and the Z-axis original data signal αz(t) obtained in the Z-axis direction. All correlation coefficients are obtained based on all the aforementioned synthetic components; Based on all the aforementioned correlation coefficients, a correlation coefficient change curve is generated. If the correlation coefficient change curve matches the regular curve, it is determined that the link corresponding to the correlation coefficient change curve has experienced an external force collision.

8. The vibration detection method according to claim 7, characterized in that, In obtaining all the composite components of all the detection units in the XZ plane based on all the original data signals, the formula for obtaining the composite components is: ； In obtaining all correlation coefficients based on all the composite components, the formula for obtaining the correlation coefficients is: ； Wherein, X is one of the composite components, Y is the composite component adjacent to X, Cov(X, Y) is the covariance of X and Y, D(X) is the variance of X, and D(Y) is the variance of Y.

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