Noise power level determination method, apparatus, storage medium, and computer device

Abstract

The application discloses a noise power level determination method and device, a storage medium and a computer device. The method comprises the following steps: controlling the joint movement of a robot, and recording corresponding robot noise audio; determining the noise energy corresponding to each joint when the joints move respectively according to the robot noise audio; and determining the overall noise power level of the robot according to the noise energy. The application solves the technical problem of low overall noise measurement efficiency of the robot.

Description

Technical Field

[0001] This invention relates to the field of robotics, and more specifically, to a method, apparatus, and storage medium computer device for determining noise power levels. Background Technology

[0002] Industrial robots are increasingly widely used in high-end equipment manufacturing, gradually bringing about environmental pollution problems caused by noise radiation. The noise from industrial robots worsens the acoustic environment of manufacturing workshops and hinders the development of intelligent voice operation technology for robots. Furthermore, the noise level of robots directly affects users' perception of product quality, thus impacting their economic value and market competitiveness. Therefore, the industry has placed higher demands on the noise levels of robots, and their noise radiation value is gradually becoming an important indicator for evaluating industrial robot performance.

[0003] Robotic motion is a complex motion involving multiple joints, and noise generated may be due to the superposition of noise from one or more joints. However, current technologies for measuring noise in the entire robot are time-consuming and inefficient. Furthermore, the numerous posture changes during robot operation can lead to factors such as joint occlusion affecting noise measurement.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a method, apparatus, and storage medium computer device for determining noise power level, in order to at least solve the technical problem of low efficiency in overall robot noise measurement.

[0006] According to one aspect of the present invention, a method for determining noise power level is provided, comprising: controlling the movement of multiple joints of a robot and recording corresponding robot noise audio; determining the noise energy corresponding to the operation of each of the multiple joints respectively based on the robot noise audio; and determining the overall noise power level of the robot based on the noise energy.

[0007] Optionally, determining the overall noise power level of the robot based on the noise energy includes: determining the predetermined operating state time proportion corresponding to each of the plurality of joints during operation; determining the weighting coefficients corresponding to each of the plurality of joints based on the predetermined operating state time proportions; and determining the overall noise power level based on the weighting coefficients and the noise energy.

[0008] Optionally, determining the percentage of time for each of the multiple joints in a predetermined operating state during their respective operations includes: acquiring the robot's operating data, wherein the operating data characterizes the joint motion state of the robot during the recording of the robot's noise audio; determining the uniform speed operating time for each of the multiple joints during their respective operations based on the operating data; determining the total uniform speed operating time for the multiple joints based on the uniform speed operating time; and determining the percentage of time for each of the multiple joints in a predetermined operating state based on the uniform speed operating time and the total time.

[0009] Optionally, determining the percentage of time for each of the predetermined operating states when the plurality of joints are running includes: obtaining a noise detection threshold; determining the noisy operating time of each of the plurality of joints when they are running, based on the noise detection threshold, wherein the noise loudness emitted by each of the plurality of joints during the noisy operating time is greater than the noise detection threshold; determining the total noisy operating time of the plurality of joints based on the noisy operating time; and determining the percentage of time for each of the predetermined operating states when the plurality of joints are running, based on the total noisy operating time.

[0010] Optionally, determining the overall noise power level based on the weighting coefficients and the noise energy includes: determining the joint noise energy corresponding to each of the plurality of joints based on the weighting coefficients and the noise energy; summing the joint noise energy to obtain the total noise energy; and determining the overall noise power level based on the total noise energy and the envelope area of ​​the robot.

[0011] Optionally, controlling the movement of multiple joints of the robot and recording corresponding robot noise audio includes: generating a continuous running sequence of the multiple joints, wherein the continuous running sequence includes the sequential movement order of the multiple joints and the running time of each of the multiple joints; sending the continuous running sequence to the robot, wherein the robot controls the multiple joints to move sequentially according to the continuous running sequence; and recording the robot noise audio corresponding to the robot controlling the movement of the multiple joints according to the continuous running sequence.

[0012] Optionally, controlling the movement of multiple joints of the robot and recording corresponding robot noise audio includes: acquiring the robot's action mode; determining, based on the action mode, that the joints used by the robot when executing the action mode are the multiple joints; and recording the audio of the robot controlling the movement of the multiple joints to obtain the robot noise audio.

[0013] According to another aspect of the present invention, a method for determining noise power level is also provided, comprising: acquiring joint noise audio of a robot, wherein the joint noise audio is audio recorded when a target joint of the robot moves; determining noise energy corresponding to the operation of the target joint based on the joint noise audio; and determining the joint noise power level of the target joint of the robot during operation based on the noise energy.

[0014] According to another aspect of the present invention, a noise power level determination device is also provided, comprising: a recording module for controlling the movement of multiple joints of a robot and recording corresponding robot noise audio; a first determination module for determining the noise energy corresponding to each of the multiple joints when they are running, based on the robot noise audio; and a second determination module for determining the overall noise power level of the robot based on the noise energy.

[0015] According to another aspect of the present invention, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored program, wherein, when the program is executed, the device where the non-volatile storage medium is located is controlled to execute any of the above-described noise power level determination methods.

[0016] According to another aspect of the present invention, a computer device is also provided, the computer device including a memory and a processor, the memory being used to store a program, and the processor being used to run the program stored in the memory, wherein the program, when running, executes any of the noise power level determination methods described above.

[0017] In this embodiment of the invention, by controlling the movement of multiple joints of the robot, corresponding robot noise audio is recorded; based on the robot noise audio, the noise energy corresponding to each joint when it is running is determined; based on the noise energy, the overall noise power level of the robot is determined, thereby achieving the purpose of quickly determining the overall noise power level of the robot, thus realizing the technical effect of improving the measurement efficiency of the overall noise power level of the robot, and thus solving the technical problem of low measurement efficiency of the overall noise of the robot. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0019] Figure 1 A hardware block diagram of a computer terminal for implementing a noise power level determination method is shown.

[0020] Figure 2This is a flowchart illustrating the noise power level determination method provided according to an embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of a robot noise power level measurement process provided by an optional embodiment of the present invention;

[0022] Figure 4 This is a flowchart illustrating another method for determining noise power level according to an embodiment of the present invention;

[0023] Figure 5 This is a structural block diagram of a noise power level determination device provided according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to an embodiment of the present invention, a method embodiment for determining noise power level is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0027] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal for implementing a noise power level determination method is shown. Figure 1As shown, the computer terminal 10 may include one or more processors (shown as processors 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0028] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be implemented wholly or partially as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be wholly or partially integrated into any other element in the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0029] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the noise power level determination method in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the noise power level determination method of the aforementioned application. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0030] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0031] In this invention, the number of joints in the robot can be denoted as n. The noise power level determination method provided by this invention can estimate the overall noise of the robot by measuring the results of different numbers of single joints. In related technologies, robot assembly requires the sequential installation of multiple joints. The sound power level measurement of the overall noise requires noise measurement of the robot after assembly. If the sound power level of the overall noise measured after assembly does not meet the requirements, it is necessary to find the problem and disassemble the robot to eliminate the problem, resulting in a significant reduction in overall work efficiency. Based on the method proposed in this invention, the noise generated by the movement of each joint can be measured before assembly. The sound power level of the entire robot can be estimated using the noise signal of a single joint. If the required overall noise power level is met, the robot can be assembled. This can effectively improve work efficiency and avoid repetitive and ineffective work.

[0032] Figure 2 This is a flowchart illustrating the noise power level determination method provided by an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes the following steps:

[0033] Step S202: Control the movement of multiple joints of the robot and record the corresponding robot noise audio. The robot comprises multiple joints, which can move sequentially without interfering with each other during audio recording. Optionally, the robot noise audio can be divided into multiple joint noise audio segments, each segment corresponding to one joint of the robot; that is, each joint noise audio segment is equivalent to a recording of one joint of the robot running independently.

[0034] To obtain the joint noise audio of a robot, at least the following two methods can be used to achieve this goal.

[0035] Method 1, as an optional embodiment, obtaining the joint noise audio of the robot may include the following steps: generating a continuous running sequence of multiple joints, wherein the continuous running sequence includes the sequential movement order of the multiple joints and the running time of each of the multiple joints; sending the continuous running sequence to the robot, wherein the robot controls the multiple joints to move sequentially according to the continuous running sequence; recording the robot noise audio corresponding to the robot controlling the multiple joints to run according to the above continuous running sequence; and segmenting the robot noise audio according to the continuous running sequence to obtain the joint noise audio corresponding to each of the multiple joints.

[0036] In this optional embodiment, continuous sound sampling can be performed. The robot controller can control multiple joints to operate independently in sequence. The duration of each joint's operation is controlled by the controller. Continuous sound recording yields a relatively long complete audio segment. Then, based on the controller's control behavior, the complete audio is segmented to obtain the joint noise audio corresponding to each joint. The advantage of this approach is its high sound acquisition efficiency, eliminating the need for repeated on / off recording, reducing manual labor, and improving the efficiency of noise audio recording.

[0037] Method Two, as an optional implementation, involves controlling multiple joints to operate independently when acquiring the robot's joint noise audio. The sound from each joint during operation is then sampled separately to obtain the joint noise audio corresponding to each joint. The advantage of this approach is that it avoids motion and sound interference between the robot's joints, ensuring that each recorded audio entry only includes the noise generated by the movement of the corresponding joint, excluding the operating noise of other joints, thus guaranteeing the accuracy of the audio acquisition results.

[0038] As an optional embodiment, the movement of multiple joints of the robot can also be controlled in the following way to record the corresponding robot noise audio: obtain the robot's action mode; determine that the joints used by the robot when executing the action mode are multiple joints based on the action mode; record the audio of the robot controlling the movement of multiple joints to obtain the robot noise audio.

[0039] Based on this optional embodiment, the overall noise power level of the robot under a specific action mode can be estimated. Since the robot can perform different action modes to complete different types of tasks, this embodiment can be used to collect the joint motion sounds of the robot under a specific action mode, thereby estimating the overall noise power level of the robot under that action mode, thus improving the diversity of robot noise power level measurement methods.

[0040] Step S204: Based on the robot's noise audio, determine the noise energy corresponding to each of the multiple joints during operation. Noise energy can refer to the work done by the noise sound wave over a certain time period, or in other words, the sound energy is the average value of the work done by the sound wave over a certain time period.

[0041] Step S206: Determine the overall noise power level of the robot based on the noise energy. Sound power level describes the sound energy radiated outward by a sound source per unit time; it can be determined based on the ratio of sound power to a reference sound power and is a relative measure.

[0042] As an optional embodiment, determining the overall noise power level of the robot based on noise energy may include the following steps: determining the predetermined operating state time proportion corresponding to each of the multiple joints when they are running separately; determining the weighting coefficients corresponding to each of the multiple joints based on the predetermined operating state time proportions; and determining the overall noise power level based on the weighting coefficients and noise energy.

[0043] The determination of sound power level needs to consider the time dimension of noise. Therefore, in this optional embodiment, the proportion of time in each of the predetermined operating states of multiple joints during operation is used as a weighting coefficient to adjust the estimated result of the overall noise power level, making the estimated result of the overall noise power level more consistent with the actual perception of human hearing. The proportion of time in the predetermined operating state can be the ratio of the operating time of each joint in its predetermined operating state to the total operating time of all joints, used to characterize the importance of the noise generated by that joint on human hearing within the overall noise impact on human hearing.

[0044] As an optional embodiment, determining the predetermined operating state time proportion corresponding to each of the multiple joints during operation includes: acquiring robot operation data, wherein the operation data characterizes the joint motion state of the robot during the recording of robot noise audio; determining the uniform speed operation time of each of the multiple joints during operation based on the operation data; determining the total uniform speed operation time of the multiple joints based on the uniform speed operation time; and determining the predetermined operating state time proportion corresponding to each of the multiple joints based on the uniform speed operation time and the total time.

[0045] This embodiment focuses on describing the noise severity during stable robot operation. Therefore, it uses the uniform speed running time of each joint to determine the proportion of time in a predetermined operating state, thereby generating weighting coefficients. In this case, the predetermined operating state is the uniform speed running state of the joint, and the running time of the joint in this state is the uniform speed running time of the joint. Based on this optional embodiment, the overall noise power level of the robot under normal conditions can be estimated. The results obtained are consistent with the user's subjective perception of noise during normal robot use. Furthermore, the uniform speed running time of each joint is relatively easy to obtain, thus accelerating the estimation of the overall noise power level and improving the detection efficiency of the robot's overall noise.

[0046] As an optional embodiment, determining the percentage of predetermined operating state time for each of the multiple joints during their respective operations includes: obtaining a noise detection threshold; determining the noisy operating time of each of the multiple joints during their respective operations based on the noise detection threshold, wherein the noise loudness emitted by each of the multiple joints during the noisy operating time is greater than the noise detection threshold; determining the total noisy operating time of the multiple joints based on the noisy operating time; and determining the percentage of predetermined operating state time for each of the multiple joints based on the noisy operating time and the total noisy operating time.

[0047] In this optional embodiment, noise sources can be collected throughout the operation of each joint of the robot. Regardless of the joint's operating state, the portion of the actual noise that exceeds the noise detection threshold is determined as the noisy operating time of that joint, making the estimation result of the overall machine noise more accurate.

[0048] As an optional embodiment, the noise power level of the whole machine is determined based on the weighting coefficients and noise energy, including: determining the joint noise energy corresponding to each of the multiple joints based on the weighting coefficients and noise energy; summing the joint noise energy to obtain the total noise energy; and determining the noise power level of the whole machine based on the total noise energy and the envelope area of ​​the robot.

[0049] The weighting coefficient can be expressed as ω j Let j represent the j-th joint among multiple joints. The noise energy of joint j can be expressed as... The area of ​​the envelope surface is denoted by S. Optionally, the overall noise power level can be determined based on the following formula: in, This indicates the noise power level of the entire machine.

[0050] In the above steps, by controlling the movement of multiple joints of the robot, the corresponding robot noise audio is recorded; based on the robot noise audio; based on the robot noise audio, the noise energy corresponding to each joint when it runs is determined; based on the noise energy, the overall noise power level of the robot is determined, thus achieving the goal of quickly determining the overall noise power level of the robot, thereby achieving the technical effect of improving the measurement efficiency of the overall noise power level of the robot, and thus solving the technical problem of low measurement efficiency of overall robot noise.

[0051] Figure 3 This is a schematic diagram of a robot noise power level measurement process provided by an optional embodiment of the present invention, such as... Figure 3 As shown, this optional embodiment may include the following steps:

[0052] Step 1: According to the group standard, "Methods and Procedures for Noise Measurement and Evaluation of Industrial Robots," test the radiated noise of each joint of the robotic arm and the radiated noise during the movement of the entire machine. In this step, the BBM PAK acquisition system is used to conduct experimental measurements during individual joint operation and during the operation of the entire machine, based on the "Methods and Procedures for Noise Measurement and Evaluation of Industrial Robots." The sampling time for a single joint is 10 seconds, the sampling time for the entire machine operation is 30 seconds, and the sampling rate is 44100Hz.

[0053] Step 2: Count how many time periods there are in a motion cycle, which joint moves in each time period, and the stable running time of the joint. The stable running time can be the time when the joint maintains a constant speed. The ratio of the stable running time of a joint to the total stable running time of all joints in a time period can be used as the time weighting coefficient for that joint, as shown in Equation (1).

[0054]

[0055] In the formula, ω j -Time weighting coefficient for joint j; T j - The stable running time of joint j.

[0056] In this step, the motion of the whole machine can be divided into multiple stages, each stage containing different moving joints. There may be multiple joints moving at the same time. For such a complex motion process, the stable operation time of each joint can be counted, and the ratio of the stable operation time of each joint to the total stable operation time of all joints can be used as a weighting coefficient.

[0057] Step 3: Based on the cross-weighting coefficient, perform time-weighted summation on the noise energy measured in Step 1 to calculate the overall sound power level, as shown in Equation (2).

[0058]

[0059] In the formula, This represents the estimated total radiated noise power level of the robot; n represents the total number of joints in the robot. represents the noise energy of joint j; S represents the area of ​​the envelope surface.

[0060] In this step, the noise energy of each joint is weighted and summed based on the time weighting coefficients calculated in step 2. Here, S is the parallelepiped measurement surface of the envelope sound source, an imaginary surface with sides parallel to the edges of the reference body and at a certain distance from the reference body. In noise measurement, the envelope surface refers to the surface formed by the geometric positions of points in phase during sound wave propagation. This surface is typically used to describe the propagation characteristics and sound field distribution of sound waves.

[0061] Step 4: Calculate the actual noise power level of the whole machine based on the radiated noise of the whole machine measured in Step 1.

[0062] In this step, the actual noise power level of the entire machine is calculated based on the radiated noise measured in Step 1. Sound pressure level depends on distance, sound source location, and environment, including factors such as the presence or absence of reflection from the ground, whether the source is inside a room, the room's volume, and the duration of sound reverberation. Sound pressure level varies with changing external conditions. Sound power level, however, is independent of distance, location, or environment because it is both a theoretical and an absolute value; the noise source has the same sound power level regardless of its location. Therefore, to accurately quantify the radiated noise of the entire machine and accurately evaluate the feasibility of the estimation method, sound power level is used to measure the robot's noise level.

[0063] Step 5: Compare the overall noise power level estimated in Step 3 and for each individual joint with the actual noise power level calculated in Step 4, and determine whether the error between the two is less than 2 dB(A).

[0064] In this step, by comparing the overall sound power level estimated in step 3 with the actual sound power level measured in step 4, it is determined whether the noise power level estimated in the above embodiment or optional embodiment is accurate. If the error is within 2dB(A), the estimation result can be considered accurate and the error is very small.

[0065] Figure 4 This is a flowchart illustrating another method for determining noise power level according to an embodiment of the present invention, as shown below. Figure 4 As shown, the method includes the following steps:

[0066] Step S402: Obtain the joint noise audio of the robot, wherein the joint noise audio is the audio recorded when the target joint of the robot moves;

[0067] Step S404: Determine the noise energy corresponding to the target joint during operation based on the joint noise audio.

[0068] Step S406: Determine the joint noise power level of the target joint of the robot during operation based on the noise energy.

[0069] A robot may include multiple joints, and the target joint can be any one of the robot's multiple joints. Based on the above method, the noise power level of any joint of the robot during operation can be determined.

[0070] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that the noise power level determination method according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0072] According to an embodiment of the present invention, a noise power level determination apparatus for implementing the above-described noise power level determination method is also provided. Figure 5 This is a structural block diagram of a noise power level determination device provided according to an embodiment of the present invention, such as... Figure 5 As shown, the noise power level determination device includes: a recording module 52, a first determination module 54, and a second determination module 56. The noise power level determination device will be described below.

[0073] Recording module 52 is used to control the movement of multiple joints of the robot and record the corresponding robot noise audio.

[0074] The first determining module 54, connected to the recording module 52, is used to determine the noise energy corresponding to each of the multiple joints when they are running, based on the robot noise audio.

[0075] The second determining module 56, connected to the first determining module 54, is used to determine the overall noise power level of the robot based on the noise energy.

[0076] It should be noted that the recording module 52, the first determining module 54, and the second determining module 56 mentioned above correspond to steps S202 to S206 in the embodiments. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of the device, can run in the computer terminal 10 provided in the embodiments.

[0077] Embodiments of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one of a plurality of network devices in a computer network. The computer device includes a memory and a processor.

[0078] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the noise power level determination method and apparatus in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the aforementioned noise power level determination method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0079] The processor can access the information and application programs stored in the memory via the transmission device to perform the following steps: control the movement of multiple joints of the robot and record the corresponding robot noise audio; determine the noise energy corresponding to each joint when it is running separately based on the robot noise audio; and determine the overall noise power level of the robot based on the noise energy.

[0080] Optionally, the processor may also execute program code that performs the following steps: determining the overall noise power level of the robot based on the noise energy, including: determining the predetermined running state time proportion of each of the multiple joints when they are running separately; determining the weighting coefficients corresponding to each of the multiple joints based on the predetermined running state time proportions; and determining the overall noise power level based on the weighting coefficients and the noise energy.

[0081] Optionally, the processor may also execute program code for the following steps: determining the percentage of predetermined running state time for each of the multiple joints during their respective runs, including: acquiring robot running data, wherein the running data characterizes the joint motion state of the robot during the recording of robot noise audio; determining the uniform speed running time for each of the multiple joints during their respective runs based on the running data; determining the total uniform speed running time for the multiple joints based on the uniform speed running time; and determining the percentage of predetermined running state time for each of the multiple joints based on the uniform speed running time and the total time.

[0082] Optionally, the processor may also execute program code that performs the following steps: determining the percentage of predetermined running state time for each of the multiple joints during their respective runs, including: obtaining a noise detection threshold; determining the noisy running time of each of the multiple joints during their respective runs based on the noise detection threshold, wherein the noise loudness emitted by each of the multiple joints during the noisy running time is greater than the noise detection threshold; determining the total noisy running time of the multiple joints based on the noisy running time; and determining the percentage of predetermined running state time for each of the multiple joints based on the noisy running time and the total noisy running time.

[0083] Optionally, the processor may also execute program code that performs the following steps: determining the overall noise power level based on weighting coefficients and noise energy, including: determining the joint noise energy corresponding to each of the multiple joints based on weighting coefficients and noise energy; summing the joint noise energy to obtain the total noise energy; and determining the overall noise power level based on the total noise energy and the robot's envelope area.

[0084] Optionally, the processor may also execute program code for the following steps: controlling the movement of multiple joints of the robot and recording corresponding robot noise audio, including: generating a continuous running sequence of multiple joints, wherein the continuous running sequence includes the sequential movement order of multiple joints and the running time of each joint; sending the continuous running sequence to the robot, wherein the robot controls the movement of multiple joints in sequence according to the continuous running sequence; and recording the robot noise audio corresponding to the robot controlling the movement of multiple joints according to the continuous running sequence.

[0085] Optionally, the processor may also execute program code that performs the following steps: controlling the movement of multiple joints of the robot and recording the corresponding robot noise audio, including: acquiring the robot's action mode; determining, based on the action mode, that the joints used by the robot when executing the action mode are multiple joints; and recording the audio of the robot controlling the movement of multiple joints to obtain robot noise audio.

[0086] Optionally, the processor may also execute program code that performs the following steps: acquiring the joint noise audio of the robot, wherein the joint noise audio is the audio recorded when the target joint of the robot moves; determining the noise energy corresponding to the operation of the target joint based on the joint noise audio; and determining the joint noise power level of the target joint of the robot based on the noise energy.

[0087] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a non-volatile storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0088] Embodiments of the present invention also provide a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the noise power level determination method provided in the above embodiments.

[0089] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0090] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: controlling the movement of multiple joints of the robot and recording the corresponding robot noise audio; determining the noise energy corresponding to each joint when it is running; and determining the overall noise power level of the robot based on the noise energy.

[0091] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the overall noise power level of the robot based on noise energy, including: determining the predetermined operating state time proportion corresponding to each of the multiple joints when they are running respectively; determining the weighting coefficients corresponding to the multiple joints respectively based on the predetermined operating state time proportions; and determining the overall noise power level based on the weighting coefficients and noise energy.

[0092] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the predetermined running state time proportion corresponding to each of the multiple joints when they run separately, including: acquiring robot running data, wherein the running data characterizes the joint motion state of the robot during the recording of robot noise audio; determining the uniform speed running time of each of the multiple joints when they run separately based on the running data; determining the total uniform speed running time of the multiple joints based on the uniform speed running time; and determining the predetermined running state time proportion corresponding to each of the multiple joints based on the uniform speed running time and the total time.

[0093] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the proportion of predetermined running state time corresponding to each of the multiple joints when they run separately, including: obtaining a noise detection threshold; determining the noisy running time of each of the multiple joints when they run separately according to the noise detection threshold, wherein the noise loudness emitted by each of the multiple joints during the noisy running time is greater than the noise detection threshold; determining the total noisy running time of the multiple joints according to the noisy running time; and determining the proportion of predetermined running state time corresponding to each of the multiple joints according to the noisy running time and the total noisy running time.

[0094] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the overall noise power level based on weighting coefficients and noise energy, including: determining the joint noise energy corresponding to each of the multiple joints based on weighting coefficients and noise energy; summing the joint noise energy to obtain the total noise energy; and determining the overall noise power level based on the total noise energy and the envelope area of ​​the robot.

[0095] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: controlling the movement of multiple joints of the robot and recording corresponding robot noise audio, including: generating a continuous running sequence of multiple joints, wherein the continuous running sequence includes the sequential movement order of multiple joints and the running time of each of the multiple joints; sending the continuous running sequence to the robot, wherein the robot controls the multiple joints to move sequentially according to the continuous running sequence; and recording the robot noise audio corresponding to the robot controlling the operation of multiple joints according to the continuous running sequence.

[0096] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: controlling the movement of multiple joints of the robot and recording corresponding robot noise audio, including: acquiring the robot's action mode; determining, based on the action mode, that the joints used by the robot when executing the action mode are multiple joints; and recording the audio of the robot controlling the movement of multiple joints to obtain robot noise audio.

[0097] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: acquiring joint noise audio of the robot, wherein the joint noise audio is audio recorded when the target joint of the robot moves; determining the noise energy corresponding to the operation of the target joint based on the joint noise audio; and determining the joint noise power level of the target joint of the robot based on the noise energy.

[0098] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0099] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0100] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0101] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0103] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0104] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for determining noise power level, characterized in that, include: Control the movement of multiple joints of the robot and record the robot noise audio corresponding to the multiple joints; Based on the robot noise audio corresponding to the multiple joints, determine the noise energy corresponding to each of the multiple joints when they are running. The overall noise power level of the robot is determined based on the noise energy corresponding to each of the multiple joints during their respective operations. This includes: determining the predetermined operating state time percentage for each of the multiple joints during their respective operations; determining the weighting coefficients for each of the multiple joints based on the predetermined operating state time percentages; determining the joint noise energy for each of the multiple joints based on the weighting coefficients and the noise energy; summing the joint noise energy to obtain the total noise energy; and determining the overall noise power level based on the total noise energy and the envelope area of ​​the robot, using the following formula: ， in, This indicates the noise power level of the entire machine. Here, j represents the weighting coefficient, indicating the j-th joint among the plurality of joints. This represents the noise energy of joint j. S It is expressed as the area of ​​the envelope surface.

2. The method according to claim 1, characterized in that, Determining the percentage of time for each of the multiple joints in their respective predetermined operating states during operation includes: Acquire the robot's operational data, wherein the operational data characterizes the joint motion state of the robot during the recording of the robot's noise audio; Based on the operational data, the uniform speed operation time of each of the multiple joints is determined. Based on the uniform speed running time, determine the total uniform speed running time of the multiple joints; Based on the constant speed running time and the total time, the predetermined running state time proportions corresponding to each of the multiple joints are determined.

3. The method according to claim 1, characterized in that, Determining the percentage of time for each of the multiple joints in their respective predetermined operating states during operation includes: Obtain the noise detection threshold; Based on the noise detection threshold, the noise-containing operating time of each of the plurality of joints is determined when they are running, wherein the noise loudness emitted by each of the plurality of joints during the noise-containing operating time is greater than the noise detection threshold. Based on the noisy running time, determine the total noisy running time of the multiple joints; Based on the noisy running time and the total noisy running time, determine the percentage of the predetermined running state time for each of the multiple joints.

4. The method according to claim 1, characterized in that, The control of multiple joint movements of the robot, and the recording of corresponding robot noise audio, includes: Generate a continuous running sequence of the plurality of joints, wherein the continuous running sequence includes the sequential movement order of the plurality of joints and the running time of each of the plurality of joints; The continuous running sequence is sent to the robot, wherein the robot controls the plurality of joints to move sequentially according to the continuous running sequence; Record the robot noise audio corresponding to the operation of the multiple joints controlled by the robot according to the continuous running sequence.

5. The method according to any one of claims 1 to 4, characterized in that, The control of multiple joint movements of the robot, and the recording of corresponding robot noise audio, includes: Obtain the robot's motion pattern; Based on the action pattern, it is determined that the joints used by the robot when executing the action pattern are the plurality of joints; Record the audio of the robot controlling the movement of the multiple joints to obtain the robot noise audio.

6. A noise power level determination device, characterized in that, include: A recording module is used to control the movement of multiple joints of the robot and record the robot noise audio corresponding to the multiple joints; The first determining module is used to determine the noise energy corresponding to each of the multiple joints when they are running, based on the robot noise audio corresponding to the multiple joints. The second determining module is used to determine the overall noise power level of the robot based on the noise energy corresponding to each of the multiple joints during operation. The second determining module is further configured to: determine the predetermined operating state time proportion for each of the plurality of joints during their respective operation; determine the weighting coefficients for each of the plurality of joints based on the predetermined operating state time proportions; determine the joint noise energy for each of the plurality of joints based on the weighting coefficients and the noise energy; sum the joint noise energy to obtain the total noise energy; and determine the overall noise power level based on the total noise energy and the envelope area of ​​the robot, using the following formula: ， in, This indicates the noise power level of the entire machine. Here, j represents the weighting coefficient, indicating the j-th joint among the plurality of joints. This represents the noise energy of joint j. S It is expressed as the area of ​​the envelope surface.

7. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to perform the noise power level determination method according to any one of claims 1 to 5.

8. A computer device, characterized in that, The computer device includes a memory and a processor, the memory being used to store a program, and the processor being used to run the program stored in the memory, wherein the program, when running, executes the noise power level determination method according to any one of claims 1 to 5.

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