Method, apparatus, medium and computer program product for determining vibration signal

Abstract

The embodiment of the invention relates to a method and device for determining a vibration signal, a medium and a computer program product. The method comprises the following steps: collecting a vibration signal at a detection position where the vibration sensor is located; the method also includes obtaining one or more spatial features of the detection location relative to the one or more target locations. Further, the method includes determining one or more target vibration signals at one or more target locations based on the vibration signals and the one or more spatial features, where the one or more target locations and the detected location are different locations of the power tool. Through the scheme provided by the invention, the target vibration signal at the target position can be determined by using the vibration sensor at the detection position, compared with the collected vibration signal, the target vibration signal can better reflect the vibration condition at the target position, and the vibration sensor is only arranged at the detection position, so that the detection accuracy is improved. And the cost of the vibration sensor can be reduced.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computers, and more particularly, to a method, apparatus, device, medium, and computer program product for determining vibration signals. Background Art

[0002] A vibration signal is a wave generated by the vibration of an object, usually captured by a vibration sensor, and is an important information source reflecting the motion state and structural characteristics of the object. By capturing the vibration signal with a sensor, we can deeply understand parameters such as the vibration frequency, amplitude, and phase of the object. Vibration signals play a key role in the fields of engineering and science.

[0003] For example, vibration signals have a variety of important applications in the fields of engineering and science. Vibration signals can be used to monitor and diagnose the health status of equipment or structures, helping to detect potential faults in advance. In addition, vibration signals play a key role in the analysis of the structure and performance of objects, contributing to optimizing the design and improving product performance. In addition, vibration signals are also widely used in sensor technology to measure the motion, speed, and acceleration of objects, providing key information for automatic control systems. Summary of the Invention

[0004] Embodiments of the present disclosure provide a method, apparatus, device, medium, and computer program product for determining vibration signals.

[0005] According to a first aspect of the present disclosure, a method for determining a vibration signal is provided. The method includes collecting a vibration signal at a detection position where a vibration sensor is located. The method further includes obtaining one or more spatial features of the detection position relative to one or more target positions. In addition, the method further includes determining one or more target vibration signals at one or more target positions based on the vibration signal and the one or more spatial features, where the one or more target positions and the detection position are different positions of a power tool.

[0006] According to a second aspect of the present disclosure, a method for fault detection is provided. The method includes determining whether one or more components at one or more target positions are faulty by using a fault detection model based on the one or more target vibration signals determined by the method in the first aspect.

[0007] According to a third aspect of the present disclosure, there is provided an apparatus for determining a vibration signal. The apparatus includes a vibration signal acquisition unit configured to acquire a vibration signal at a detection position where a vibration sensor is located. The apparatus includes a spatial feature acquisition unit configured to acquire one or more spatial features of the detection position relative to one or more target positions. Further, the apparatus includes a target signal determination unit configured to determine one or more target vibration signals at one or more target positions based on the vibration signal and the one or more spatial features, where the one or more target positions and the detection position are different positions of a power tool.

[0008] According to a fourth aspect of the present disclosure, there is provided an electronic device. The electronic device includes at least one processor; and a memory coupled to the at least one processor and having instructions stored thereon, the instructions, when executed by the at least one processor, cause the device to perform the steps of the methods in the first and second aspects of the present disclosure.

[0009] According to a fifth aspect of the present disclosure, there is provided a machine-readable storage medium. Machine-executable instructions are stored on the machine-readable storage medium, where the machine-executable instructions are executed by a processor to implement the steps of the methods in the first and second aspects of the present disclosure.

[0010] According to a sixth aspect of the present disclosure, there is provided a machine-readable storage medium. Machine-executable instructions are stored on the machine-readable storage medium, where the machine-executable instructions are executed by a processor to implement the steps of the methods in the first and second aspects of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] By describing the exemplary embodiments of the present disclosure in more detail in conjunction with the drawings, the above and other objects, features, and advantages of the present disclosure will become more apparent, where, in the exemplary embodiments of the present disclosure, the same reference numerals generally represent the same components.

[0012] Figure 1 A schematic diagram illustrating an example environment in which the device and / or method according to the embodiments of the present disclosure may be implemented;

[0013] Figure 2 A flowchart illustrating a method for determining a vibration signal according to an embodiment of the present disclosure;

[0014] Figure 3A A schematic diagram showing a process of training a vibration signal generation model according to an embodiment of the present disclosure;

[0015] Figure 3B A schematic diagram showing a process of acquiring a vibration signal according to an embodiment of the present disclosure;

[0016] Figure 4It is a flowchart of a method for generating a target vibration signal according to an embodiment of the present disclosure;

[0017] Figure 5 It shows a schematic diagram of a scenario using a target vibration signal according to an embodiment of the present disclosure;

[0018] Figure 6 It illustrates a schematic diagram of an apparatus for determining a vibration signal according to an embodiment of the present disclosure; and

[0019] Figure 7 It illustrates a schematic block diagram of an example device suitable for implementing embodiments of the present disclosure.

[0020] In each of the drawings, the same or corresponding reference numerals represent the same or corresponding parts. Detailed Description of the Embodiments

[0021] It can be understood that the data involved in the technical solution (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of relevant laws, regulations and related provisions.

[0022] Hereinafter, the preferred embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure will be more thorough and complete, and can fully convey the scope of the present disclosure to those skilled in the art.

[0023] As used herein, the term "including" and its variants mean open inclusion, that is, "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "at least partially based on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. There may also be other explicit and implicit definitions hereinafter.

[0024] It should be noted that the numbers or numerical values used herein are for the convenience of understanding the technology of the present disclosure, rather than limiting the scope of the present disclosure.

[0025] As described above, vibration signals are very important and widely used. Currently, the main sensor for detecting faults in power tools is a vibration sensor. A power tool is composed of multiple components, such as an impact hammer, a rotor, a stator, a bearing, etc. Usually, only one vibration sensor is arranged on the power tool to monitor faults at multiple positions respectively. The vibration signal collected by the vibration sensor is actually the superposition of the vibration signals of multiple components during operation (i.e., the mixed vibration signal of multiple vibration signals). However, the vibration sensor cannot obtain the accurate vibration signal at other target positions except the detection position. For example, the collected vibration signal is actually the superposition of the vibration signals of components such as the rotor, stator, and bearing, so the vibration signal at the rotor position cannot be obtained. In addition, if multiple vibration sensors are arranged on the power tool to monitor faults at different positions respectively, the cost will be very high.

[0026] For this reason, an embodiment of the present disclosure proposes a solution for determining a vibration signal. This solution first collects a vibration signal at the detection position where the vibration sensor is located on the power tool, and obtains the spatial data of the detection position relative to the target position. Then, the vibration signal at the target position is determined based on the vibration signal and the spatial data. Thus, through the solution proposed in the present disclosure, the vibration sensor at the detection position can be used to determine the target vibration signal at the target position. Compared with the collected vibration signal, the target vibration signal can better reflect the vibration situation at the target position. At the same time, since only the vibration sensor is arranged at the detection position, the cost of the vibration sensor can also be reduced.

[0027] The embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings, where Figure 1 shows an example environment 100 in which the devices and / or methods of the embodiments of the present disclosure can be implemented.

[0028] As Figure 1 shown, the example environment 100 includes a drill 110. The drill 110 belongs to a power tool. A power tool is a tool powered by electricity, including tools such as drills, electric wrenches, electric screwdrivers, electric hammers, impact drills, concrete vibrators, electric planers, and electric grinders. The example environment 100 shows the drill 110 only for the purpose of example, and does not limit the specific type of the power tool. When the drill 110 is running, multiple key components (such as a rotor, a stator, and a bearing) will vibrate and generate corresponding vibration signals, which are important information sources reflecting the motion states and structural characteristics of these components. By analyzing and processing the vibration signals, it can be determined whether the components have faults. If there are faults, repairs or replacements can be made to avoid safety problems in actual use.

[0029] Refer to Figure 1, point 112 can be the position of a certain rotor on the electric drill 110, point 114 can be the position of a certain bearing on the electric drill 110, and point 116 can be the position where a vibration sensor is arranged. For example, the vibration sensor measures a vibration signal at point 116, which is actually the superposition of the vibration signals of multiple components of the electric drill 110 during operation. Therefore, if the vibration signal obtained at point 116 is regarded as the vibration signal generated by the components at point 112 or point 114, it will introduce a lot of noise, which is not conducive to analyzing whether the target component fails. However, arranging vibration sensors at each component will result in too high costs. Although the example environment 100 only shows two target positions, in fact, there will be dozens or even hundreds of target positions to be measured in power tools. Therefore, arranging vibration sensors at each position is very costly.

[0030] As Figure 1 shown, the example environment 100 further includes a processor 120, and the processor 120 can be deployed on the electric drill 110. The processor 120 includes a vibration sensor 122. The vibration sensor 122 can monitor the vibration characteristics by converting the signals generated when the electric drill 110 vibrates into electrical signals. Generally speaking, vibration sensors have characteristics such as high sensitivity, fast response, and a wide measurement range, and can be widely used in fields such as structural health monitoring, mechanical equipment condition detection, and vehicle safety control. Through the vibration sensor 122, the vibration signal of the electric drill 110 can be collected, so that the electric drill 110 can be fault-detected by analyzing the vibration signal. The vibration sensor 122 is arranged at point 116 (i.e., the detection position), and the collected vibration signal is the superposition of the vibration signals of multiple components on the electric drill 110 during operation.

[0031] In addition, the processor 120 may further include a vibration signal generation model 124. The vibration signal generation model 124 may determine the vibration signals at points 112 and 114 based on the vibration signal collected at point 116. The vibration signal generation model 124 may be a machine learning model or a deep learning model, including but not limited to a convolutional neural network (CNN), a recurrent neural network (RNN), a long short-term memory network (LSTM), a generative adversarial network (GAN), and the like. In addition, when the vibration signal generation model 124 is used to determine the vibration signals at points 112 and 114, it is also necessary to obtain the spatial position data of the target position (e.g., point 112 and point 114) relative to the detection position (e.g., point 116). In addition, when training the vibration signal generation model 124, the spatial position data of the target position relative to the detection position is also required, and the training process will be described below. Since the vibration signal at the detection position and the corresponding spatial relationship are used as input and the vibration signal at the target position is used as output when training the vibration signal generation model 124, the vibration signal at the detection position and the vibration signal at the target position are modeled, so the vibration signal at the target position can be generated by the vibration signal generation model 124.

[0032] Combined with the above Figure 1 A block diagram of an example system 100 is depicted in which embodiments of the present disclosure can be implemented. Figure 2 A flow chart depicts a method 200 for determining a vibration signal according to the present disclosure.

[0033] like Figure 2 As shown, at block 202, a vibration signal at a detection position where a vibration sensor is located is collected. Figure 1 The processor 120 may collect a vibration signal at a detection position (point 116) where the vibration sensor 122 is located on the electric drill 110. The collected vibration signal is actually a superposition of vibration signals of multiple components of the electric drill 110 when they are working.

[0034] At block 204, one or more spatial features of the detection location relative to one or more target locations are obtained. Figure 1 , the processor 120 can obtain the spatial features of the detection position (e.g., point 116) relative to the target position (e.g., point 112 and point 114), the detection position is the position where the vibration sensor 122 is arranged, and the target position is the position where some key components are located. Since there can be multiple target positions, there can also be multiple spatial features, and the spatial relationship of each target position relative to the detection position requires a corresponding spatial feature to represent it.

[0035] At block 206, based on the vibration signal and one or more spatial features, one or more target vibration signals at one or more target positions are determined. For example, referring to Figure 1 , based on the vibration signal and one or more spatial features, the processor 120 can use the vibration signal generation model 124 to determine the target vibration signals at the target positions 112 and 114. Here, listing two target positions is only for example, and actually there can be fewer or more target positions.

[0036] Thus, through the method 200 according to the embodiments of the present disclosure, the vibration sensor at the detection position can be used to determine the target vibration signal at the target position. Compared with the collected vibration signal, the target vibration signal can better reflect the vibration condition at the target position. At the same time, since the vibration sensor is only arranged at the detection position, the cost of the vibration sensor can also be reduced.

[0037] Figure 3A FIG. shows a schematic diagram of a process 300A for training a vibration signal generation model according to an embodiment of the present disclosure, and Figure 3B FIG. shows a schematic diagram of a process 300B for collecting vibration signals according to an embodiment of the present disclosure. The following will be combined with Figure 3A and Figure 3B to describe the process of training a vibration signal generation model according to an embodiment of the present disclosure. As Figure 3A shown, at 302, the vibration signals at the detection position and the target position are collected. Combining Figure 3B , as an example, the vibration signals at the detection position (i.e., point 350) and the target positions (i.e., point 330 and point 340) are collected. The detection position and the target positions are at different positions of the electric drill 320. It should be understood that during the process of training the model, vibration sensors need to be arranged at both the detection position and the target position to obtain the true values of the vibration signals at the corresponding positions. Continuing to refer to Figure 3B , the vibration signal 332 is the vibration signal collected at the position of point 330, the vibration signal 342 is the vibration signal collected at the position of point 340, and the vibration signal 352 is the vibration signal collected at the position of point 350. It can be understood that the vibration signals collected at different positions are different. If the vibration signal collected at point 305 is regarded as the vibration signal generated at point 330 and the components at point 330 are judged by analyzing this vibration signal, it may lead to incorrect judgment.

[0038] At block 304, a sliding window is performed on the vibration signal data at the detection position and the target position. For example, combining Figure 3BAs shown, a vibration signal 352 is collected at the detection position. This vibration signal 352 varies with time. If the acquisition time period is too long (e.g., 100 s), it may be inconvenient for the model to process. Therefore, it is necessary to perform a sliding window process on the model, dividing the vibration signal data into multiple segments of fixed length to unify the training data format and facilitate model training.

[0039] At block 306, wavelet decomposition is performed on the vibration signal data at the detection position and the target position. For example, in combination with Figure 3B As shown, wavelet decomposition is performed on vibration signals 332, 342, and 352. Most of the vibration signals generated during the operation of power tools are non-stationary signals. Using wavelet decomposition, non-stationary signals can be decomposed into frequency components of different scales and the mutual conversion between the time domain and the frequency domain. This decomposition can provide time and frequency information about the vibration signal, thus helping to analyze the local characteristics of the vibration signal. By performing wavelet decomposition on the vibration signal, the wavelet coefficients of each vibration signal can be determined. In some embodiments, the wavelet decomposition can be wavelet packet decomposition, which is an optimization of wavelet decomposition, overcoming the poor frequency resolution of wavelet decomposition in the high-frequency band, and thus can optimize the training of the model.

[0040] At block 308, spatial data of the detection position and the target position is obtained. For example, in combination with Figure 3B As shown, the three-dimensional spatial coordinates of the detection position (point 350) and the target positions (points 330 and 340) can be obtained to calculate the distance value and the angle value of each target position relative to the detection position. In some embodiments, the coordinate information, the distance value, and the angle value can all be used as spatial features related to the spatial data to train the vibration signal generation model.

[0041] At block 310, the processed vibration signal data at the detection position and the spatial data are used as the model input, and the processed vibration signal data at the target position is used as the model output to train the vibration signal generation model. For example, in combination with Figure 3B As shown, after performing the sliding window process and wavelet decomposition process on vibration signals 332, 342, and 352, and using the processed data to train the vibration signal generation model.

[0042] At block 312, the training of the vibration signal generation model is completed. In some embodiments, the trained vibration signal generation model can be deployed on the power tool to generate the vibration signal at the target position based on the vibration signal at the detection position. In addition, in some embodiments, the trained vibration signal generation model can be deployed on an external computing device, and by receiving the vibration signal at the detection position, generate the vibration signal at the target position.

[0043] Figure 4It is a flowchart of a method 400 for generating a target vibration signal according to an embodiment of the present disclosure. Generally, the vibration signal acquisition method arranges points for acquisition near the position of the component to avoid interference from vibration signals at other parts to the signal at the current position. However, in actual use, arranging multiple vibration sensors on an electric machine to monitor faults at different parts will result in too high costs. The method 400 of the embodiment of the present disclosure can rely on only one vibration sensor to restore the vibration signals at multiple positions, reducing the cost of vibration sensors. As Figure 4 shown, at block 402, the vibration signal at the detection position is acquired. For example, as combined with Figure 3B shown, the vibration signal 352 at point 350 is obtained. The vibration sensor is arranged at the detection position, so the acquired vibration signal 352 represents the vibration condition at this position, and the vibration signal 352 is the superposition of the vibration signals of the components at multiple positions when working. Therefore, when it is necessary to analyze the vibration signal at a certain position (for example, at point 330) to determine whether there is a fault in the component at this position, it cannot be judged by analyzing the vibration signal 352, otherwise a large amount of noise will be introduced, resulting in inaccurate fault detection results.

[0044] At block 404, the spatial features of the detection position relative to the target position can be obtained. For example, as combined with Figure 3B shown, the target positions can be point 330 (for example, the position where the rotor is located) and point 340 (for example, the position where the bearing is located), and it is desired to obtain the vibration signals at these positions for fault detection analysis to determine whether there are faults in the corresponding components. Then, the distance value and the angle value of the detection position relative to the target position can be used as spatial features. In some embodiments, a three-dimensional coordinate system can be established for the power tool, and the spatial features of the detection position relative to the target position can be determined through the coordinate system.

[0045] At block 406, the vibration signal at the detection position can be subjected to a sliding window process and a wavelet decomposition process. For example, as combined with Figure 3B shown, for the signal 352, a sliding window process is performed to generate multiple segments of signals; and the multiple segments of signals are subjected to wavelet decomposition to obtain multiple wavelet coefficients. At block 408, the multiple wavelet coefficients representing the vibration signal at the detection position are input into a vibration signal generation model to generate multiple target wavelet coefficients representing the vibration signal at the target position. Then, at block 410, the target vibration signal is generated by reconstructing the multiple target wavelet coefficients. For example, as combined with Figure 3B shown, by reconstructing the multiple target wavelet coefficients, the target vibration signals 332 and 342 are generated.

[0046] Thus, by means of the method 400 of the embodiments of the present disclosure, when analyzing the vibration signal of the component at the target position, instead of directly using the vibration signal collected by the vibration sensor, the vibration signal belonging to the target position in the vibration sensor is peeled and restored through the vibration signal generation model, and the time characteristics and frequency characteristics of the vibration signal are amplified, and the noise of the target vibration signal is reduced.

[0047] Figure 5 FIG. 500 shows a schematic diagram of a scenario 500 that utilizes a target vibration signal according to an embodiment of the present disclosure. At block 502, a target vibration signal at a target position on a power tool can be generated. For example, the above-described method 200 can be used to generate the vibration signal at the target position. At block 504, based on the vibration signal at the target position, it can be determined whether there is a fault in the component at the target position. In some embodiments, a trained fault detection model (e.g., a deep learning model) can be used to determine whether there is an abnormality in the vibration signal at the target position to judge whether there is a fault in the component at the target position. At block 506, a reminder is sent to the user. For example, when it is determined that the component at the target position is normal, a no-fault reminder is sent to the user; when it is determined that the component at the target position is faulty, an alarm is sent to the user to remind the user that there is an abnormality in the component. As described above, since the target vibration signal determined by the embodiments of the present disclosure has low noise, the analysis using the target vibration signal will be more accurate, avoiding false judgments during fault detection.

[0048] In addition, in some embodiments, the target vibration signal on the power tool can be analyzed to determine whether there is an abnormal signal, and in response to detecting an abnormal signal, the user can be reminded in advance that the power tool may have a fault and predictive maintenance can be performed. In some embodiments, based on the target vibration signal on the power tool, a repair prompt for the component at the target position can be generated. For example, a prompt for repairing a certain part of the component or a prompt for direct replacement can be provided. In some embodiments, based on the target vibration signal on the power tool, the service life of the component at the target position can be determined to show the corresponding remaining service life to the user. In addition, in some embodiments, during product design, based on the target vibration signal on the power tool, it can be analyzed whether the structural design of the component at the target position is reasonable.

[0049] Figure 6 FIG. 600 shows a schematic diagram of a device 600 for determining a vibration signal according to an embodiment of the present disclosure. As Figure 6As shown, device 600 includes: a vibration signal acquisition unit 602 configured to acquire vibration signals at a detection position where a vibration sensor is located. The device further includes a spatial feature acquisition unit 604 configured to acquire one or more spatial features of the detection position relative to one or more target positions. Additionally, the device includes a target signal determination unit 606 configured to determine one or more target vibration signals at the one or more target positions based on the vibration signals and the one or more spatial features, where the one or more target positions and the detection position are different positions of a power tool.

[0050] In some embodiments, the target signal determination unit 606 includes: a first wavelet coefficient determination unit configured to determine a plurality of wavelet coefficients of the vibration signal by performing wavelet decomposition on the vibration signal; and a second target signal determination unit configured to determine the one or more target vibration signals based on the plurality of wavelet coefficients.

[0051] In some embodiments, the second target signal determination unit includes: a first target wavelet coefficient determination unit configured to determine a plurality of target wavelet coefficients of the one or more target vibration signals; and a third target signal determination unit configured to reconstruct the one or more target vibration signals using the plurality of target wavelet coefficients.

[0052] In some embodiments, the first target wavelet coefficient determination unit includes: a model output determination unit configured to determine a plurality of outputs based on the plurality of wavelet coefficients using a vibration signal generation model, where the vibration signal generation model is a trained machine learning model; and a second target wavelet coefficient determination unit configured to use the plurality of outputs as the plurality of target wavelet coefficients.

[0053] In some embodiments, it further includes: a first signal acquisition unit configured to acquire a first training vibration signal at the detection position where the vibration sensor is located; a second signal acquisition unit configured to acquire one or more second training vibration signals at the one or more target positions; a spatial data acquisition unit configured to acquire one or more spatial data of the detection position relative to the one or more target positions; and a vibration model training unit configured to train the vibration signal generation model using the first training vibration signal, the one or more second training vibration signals, and the one or more spatial data.

[0054] In some embodiments, the vibration model training unit includes: a first decomposed signal generating unit configured to generate a first wavelet decomposed signal by performing wavelet decomposition on the first training vibration signal; a second decomposed signal generating unit configured to generate one or more second wavelet decomposed signals by performing wavelet decomposition on the one or more second training vibration signals; and a second vibration model training unit configured to train the vibration signal generation model based on the first wavelet decomposed signal, the one or more second wavelet decomposed signals, and the one or more spatial data.

[0055] In some embodiments, the vibration model training unit includes: a first set of window data generating unit configured to generate a first set of window data by performing a sliding window process on the first training vibration signal; a second set of window data generating unit configured to generate one or more second sets of window data by performing a sliding window process on the one or more second training vibration signals; and a third vibration model training unit configured to train the vibration signal generation model based on the first set of window data and the one or more second sets of window data.

[0056] In some embodiments, the spatial feature acquisition unit 604 includes: a distance value acquisition unit that acquires one or more distance values of the detection point position relative to the one or more target positions; and an angle value acquisition unit configured to acquire one or more angle values of the detection point position relative to the one or more target positions.

[0057] In some embodiments, the device 600 further includes: a structural characteristic determination unit configured to analyze the structural characteristics of one or more components at the one or more target positions based on the one or more target vibration signals.

[0058] In some embodiments, the device 600 further includes: a target fault determination unit configured to determine whether one or more components at the one or more target positions have faults by using a fault detection model based on the one or more target vibration signals. The fault detection model may be pre-trained, with vibration signals as its input and a determination result of whether there are faults as its output.

[0059] Figure 7 A schematic block diagram of a device 700 that can be used to implement the embodiments of the present disclosure is shown. The device 700 may be the device or apparatus described in the embodiments of the present disclosure. As Figure 7As shown, device 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 702 or computer program instructions loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The CPU 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0060] Multiple components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a magnetic disk, optical disc, etc.; and a communication unit 709, such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0061] Each of the methods or processes described above can be executed by the processing unit 701. For example, in some embodiments, the method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the CPU 701, one or more steps or actions of the methods or processes described above can be performed.

[0062] In some embodiments, the methods and processes described above can be implemented as a computer program product. The computer program product can include a computer-readable storage medium having computer-readable program instructions thereon for performing various aspects of the present disclosure.

[0063] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device, such as a punched card or raised structures in grooves storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage medium as used herein is not construed as being an instantaneous signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0064] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to respective computing / processing devices, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include a copper transmission cable, an optical fiber transmission, a wireless transmission, a router, a firewall, a switch, a gateway computer, and / or an edge server. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0065] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine - related instructions, microcode, firmware instructions, state - setting data, or source code or object code written in any combination of one or more programming languages, including object - oriented programming languages and conventional procedural programming languages. The computer - readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a stand - alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or, alternatively, may be connected to an external computer (e.g., through the Internet using an Internet service provider). In some embodiments, by using the state information of the computer - readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field - programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer - readable program instructions to implement various aspects of the present disclosure.

[0066] These computer - readable program instructions may be provided to a processing unit of a general - purpose computer, a special - purpose computer, or other programmable data - processing apparatus to produce a machine such that, when the instructions are executed by the processing unit of the computer or other programmable data - processing apparatus, a device is produced that implements the functions / acts specified in one or more blocks of the flowchart and / or block diagram. These computer - readable program instructions may also be stored in a computer - readable storage medium, which causes a computer, a programmable data - processing apparatus, and / or other devices to operate in a particular manner, so that the computer - readable medium storing the instructions comprises a manufacture, which includes instructions for implementing various aspects of the functions / acts specified in one or more blocks of the flowchart and / or block diagram.

[0067] The computer - readable program instructions may be loaded onto a computer, other programmable data - processing apparatus, or other device, causing a series of operational steps to be performed on the computer, other programmable data - processing apparatus, or other device to produce a computer - implemented process such that the instructions executed on the computer, other programmable data - processing apparatus, or other device implement the functions / acts specified in one or more blocks of the flowchart and / or block diagram.

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of devices, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of code, or a portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0069] The embodiments of the present disclosure have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, the practical application, or the technical improvement of the technology in the market, or to enable other ordinary skilled persons in the technical field to understand the embodiments disclosed herein.

Claims

1. A method for determining a vibration signal, comprising: Collecting a vibration signal at a detection position where a vibration sensor is located; Obtaining one or more spatial features of the detection position relative to one or more target positions; And Based on the vibration signal and the one or more spatial features, determining one or more target vibration signals at the one or more target positions, wherein the one or more target positions and the detection position are different positions of a power tool.

2. The method according to claim 1, wherein determining the one or more target vibration signals comprises: Determining a plurality of wavelet coefficients of the vibration signal by performing wavelet decomposition on the vibration signal; And Based on the plurality of wavelet coefficients and the one or more spatial features, determining the one or more target vibration signals.

3. The method according to claim 2, wherein determining the one or more target vibration signals comprises: Based on the plurality of wavelet coefficients and the one or more spatial features, determining a plurality of target wavelet coefficients of the one or more target vibration signals; And Reconstructing the one or more target vibration signals by using the plurality of target wavelet coefficients.

4. The method according to claim 3, wherein determining the plurality of target wavelet coefficients of the one or more target vibration signals comprises: Based on the plurality of wavelet coefficients, using a vibration signal generation model to determine a plurality of target wavelet coefficients, wherein the vibration signal generation model is a trained machine learning model.

5. The method according to claim 4, further comprising: Collecting a first training vibration signal at the detection position where the vibration sensor is located; Collecting one or more second training vibration signals at the one or more target positions; Obtaining one or more spatial data of the detection position relative to the one or more target positions; And Based on the first training vibration signal, the one or more second training vibration signals, and the one or more spatial data, training the vibration signal generation model, comprising: Based on the first training vibration signal and the one or more spatial data, generating one or more predicted vibration signals by the vibration signal generation model; And Based on the one or more second training vibration signals and the one or more predicted vibration signals, updating the vibration signal generation model.

6. The method according to claim 5, wherein training the vibration signal generation model comprises: Generating a first wavelet decomposition signal by performing wavelet decomposition on the first training vibration signal; Generating one or more second wavelet decomposition signals by performing wavelet decomposition on the one or more second training vibration signals; And Based on the first wavelet decomposition signal, the one or more second wavelet decomposition signals, and the one or more spatial data, training the vibration signal generation model, comprising: Based on the first wavelet decomposition signal and the one or more spatial data, generating one or more predicted wavelet decomposition signals by the vibration signal generation model; And Update the vibration signal generation model based on the one or more second wavelet decomposition signals and the one or more predicted wavelet decomposition signals.

7. The method according to claim 5, wherein training the vibration signal generation model comprises: Generating a first set of window data by performing a sliding window process on the first training vibration signal; Generating one or more second sets of window data by performing a sliding window process on the one or more second training vibration signals; And Training the vibration signal generation model based on the first set of window data and the one or more second sets of window data.

8. The method according to claim 1, wherein obtaining the one or more spatial features of the detection position relative to the one or more target positions comprises: Obtaining one or more distance values of the detection point position relative to the one or more target positions; And Obtaining one or more angular values of the detection point position relative to the one or more target positions.

9. The method according to claim 1, wherein: The one or more target vibration signals are used to analyze the structural characteristics of one or more components at the one or more target positions.

10. A method for fault detection, comprising: Based on the one or more target vibration signals determined by the method according to any one of claims 1-9, using a fault detection model to determine whether there are faults in one or more components at one or more target positions.

11. An apparatus for determining a vibration signal, comprising: A vibration signal acquisition unit configured to acquire a vibration signal at a detection position where a vibration sensor is located; A spatial feature acquisition unit configured to acquire one or more spatial features of the detection position relative to one or more target positions; And A target signal determination unit configured to determine one or more target vibration signals at the one or more target positions based on the vibration signal and the one or more spatial features, wherein the one or more target positions and the detection position are different positions of a power tool.

12. An electronic device, comprising: At least one processor; And A memory coupled to the at least one processor and having instructions stored thereon, the instructions causing the device to perform the method according to any one of claims 1 to 10 when executed by the at least one processor.

13. A machine-readable storage medium having machine-executable instructions stored thereon, wherein the machine-executable instructions are executed by a processor to implement the method according to any one of claims 1 to 10.

14. A computer program product, the computer program product being tangibly stored on a non-transitory computer-readable medium and comprising machine-executable instructions for performing the method according to any one of claims 1 to 10.

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