Program control method and device for cleaning equipment based on stress characteristics, cleaning equipment and medium

Abstract

The invention discloses a program control method and device of cleaning equipment based on stress characteristics, the cleaning equipment and a medium, and belongs to the technical field of general cleaning. The method comprises the steps that in the operation process of the cleaning equipment, stress data of a cleaning rotating device in the cleaning equipment are acquired; extracting stress characteristics based on the stress data; according to a matching result of the stress characteristics and preset abnormal stress characteristics, working parameters of the cleaning program are adjusted; wherein the working parameters comprise at least one of the rotating speed, the rotating period, the program running time and the use of the auxiliary part. According to the technical scheme, the stress characteristics of the stress data of the cleaning rotating device in the cleaning equipment are extracted, and the working parameters of the cleaning program are adjusted according to the matching result of the stress characteristics and the preset abnormal stress characteristics, so that the automation and intelligence level of the cleaning equipment can be enhanced, and the cleaning efficiency is improved. Various conditions during operation of the cleaning equipment are timely and accurately handled, and the cleaning effect is guaranteed.

Description

Technical Field

[0001] The present application belongs to the general field of cleaning technology, and specifically relates to a program control method, device, cleaning equipment and medium for cleaning equipment based on stress characteristics. Background Art

[0002] As a commonly used product in modern manufacturing and modern families, cleaning equipment has been deeply integrated into various industrial scenes and daily life. However, most existing cleaning equipment operates according to fixed working parameters of preset programs. Although the preset programs take into account the materials and degree of stains of common industrial materials or household clothing, in the actual cleaning process, the real-time cleaning conditions are complex and changeable. For example, too much foam is generated during the cleaning process, causing the foam to overflow or residual foam on the industrial materials or household clothing after cleaning.

[0003] When encountering problems that cannot be solved by these preset programs, users are generally required to manually adjust the working parameters of the cleaning program to achieve the best cleaning effect for industrial materials or household clothes. However, this requires users to rely on experience and judgment, and the operation process is cumbersome and complicated. For users who lack relevant professional knowledge and experience, it is not only difficult to accurately adjust the working parameters, but also possible to damage the cleaning equipment or increase energy consumption due to improper operation, which not only fails to achieve the ideal cleaning effect, but also leads to waste of resources and increased usage costs.

[0004] Therefore, how to automatically and accurately control the working parameters of cleaning equipment is an urgent problem that people in this field need to solve. Summary of the invention

[0005] The present application provides a program control method, device, cleaning equipment and medium for cleaning equipment based on stress characteristics, with the aim of enhancing the automation and intelligence level of the cleaning equipment, responding to various conditions during the operation of the cleaning equipment in a timely and accurate manner, and ensuring the cleaning effect.

[0006] In a first aspect, the present application provides a program control method for a cleaning device based on stress characteristics, the method comprising: During the operation of the cleaning device, obtaining stress data of a cleaning rotating device inside the cleaning device; Extracting stress characteristics based on the stress data; wherein the stress characteristics include stress peak sequence and phase distribution characteristics; According to the matching result between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program are adjusted; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

[0007] In a second aspect, the present application provides a program control device for a cleaning device based on stress characteristics, the device comprising: A stress data acquisition module, used to acquire stress data of a cleaning rotating device inside the cleaning device during operation of the cleaning device; A stress feature extraction module, used to extract stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; A working parameter adjustment module is used to adjust the working parameters of the cleaning program according to the matching result between the stress characteristics and the preset abnormal stress characteristics; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

[0008] In a third aspect, the present application provides a cleaning device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0009] In a fourth aspect, the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] In the present application, during the operation of the cleaning equipment, stress data of the cleaning rotating device inside the cleaning equipment is obtained; stress characteristics are extracted based on the stress data; wherein the stress characteristics include stress peak sequence and phase distribution characteristics; according to the matching results of the stress characteristics and the preset abnormal stress characteristics, the working parameters of the cleaning program are adjusted; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts. The above-mentioned program control method of the cleaning equipment based on stress characteristics can enhance the automation and intelligence level of the cleaning equipment, respond to various conditions during the operation of the cleaning equipment in a timely and accurate manner, and ensure the cleaning effect by extracting the stress characteristics of the stress data of the cleaning rotating device inside the cleaning equipment and adjusting the working parameters of the cleaning program according to the matching results of the stress characteristics and the preset abnormal stress characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a flow chart of a program control method of a cleaning device based on stress characteristics provided in Example 1 of the present application; Figure 2 It is a flow chart of a program control method of a cleaning device based on stress characteristics provided in the second embodiment of the present application; Figure 3 It is a flow chart of a program control method of a cleaning device based on stress characteristics provided in the third embodiment of the present application; Figure 4It is a structural schematic diagram of a program control device for a cleaning device based on stress characteristics provided in the fourth embodiment of the present application; Figure 5 It is a schematic diagram of the structure of the cleaning device provided in Example 5 of the present application. DETAILED DESCRIPTION

[0012] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only part of the present application is shown in the accompanying drawings, but not all of the content. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0014] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0015] In conjunction with the accompanying drawings, the program control method, device, cleaning equipment and medium of the cleaning equipment based on stress characteristics provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0016] Embodiment 1 Figure 11 is a flow chart of a method for controlling a cleaning device based on stress characteristics provided in the first embodiment of the present application. Figure 1 As shown, the specific steps include: S101, during the operation of a cleaning device, obtaining stress data of a cleaning rotating device inside the cleaning device; First of all, this application is applicable to scenarios where industrial materials or household clothes need to be cleaned. Based on the above usage scenarios, it can be understood that the execution subject of this application can be the main control PC (Printed Circuit) board. Specifically, the extraction and matching of stress characteristics and the adjustment of working parameters can be performed by the main control PC board, and the cleaning equipment executes the cleaning program according to the adjusted working parameters to ensure that the cleaning effect of industrial materials or household clothes reaches the best state.

[0017] Cleaning equipment can be a device used to clean industrial materials or household clothing. In industrial scenarios, cleaning equipment can be a large industrial cleaning machine used to clean various industrial parts or raw materials, etc. It has strong cleaning capabilities and various cleaning functions to adapt to the characteristics and degree of dirtiness of different industrial materials; in household scenarios, cleaning equipment can be a washing machine that can clean all kinds of clothing.

[0018] The cleaning rotation device may refer to a component in a cleaning device that is used to generate a rotational motion to assist cleaning, such as a pulsator or drum in a washing machine.

[0019] Stress refers to the internal force that interacts between the parts of an object when it is deformed due to external factors (such as force, humidity or temperature field changes). In this solution, the stress data reflects the magnitude and distribution of the force that the cleaning rotating device is subjected to during operation. The stress data of the cleaning rotating device can be collected through equipment such as strain gauges, fiber grating sensors or pressure sensors.

[0020] S102, extracting stress characteristics based on the stress data; wherein the stress characteristics include stress peak sequence and phase distribution characteristics; The stress feature may refer to the key information extracted from the stress data that can reflect the working state of the cleaning rotating device and the cleaning state of the industrial materials or household clothes in the cleaning rotating device. The stress feature may include a stress peak sequence and a phase distribution feature. Specifically, the stress peak sequence may refer to a set of data formed by arranging the stress peaks in the order of their occurrence, wherein the stress peak may refer to the maximum value of the stress data; the phase distribution feature may refer to the distribution of the stress data at different phases, wherein the phase may be a parameter used to describe the position of the signal in a cycle.

[0021] The method of extracting stress features based on stress data can be to input stress data into a pre-trained machine learning model, and the machine learning model outputs stress features. The method of extracting stress features based on stress data can also be to extract stress peak values ​​from stress data through a peak detection algorithm, and arrange them in chronological order to form a stress peak sequence; by using phase-locked loop technology or zero-crossing detection method, phase distribution features can be extracted.

[0022] S103, adjusting the working parameters of the cleaning program according to the matching result between the stress feature and the preset abnormal stress feature; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

[0023] The preset abnormal stress characteristics may be pre-constructed stress characteristics indicating an abnormal working state of the cleaning rotating device or a poor cleaning state of industrial materials or household clothing in the cleaning rotating device. The preset abnormal stress characteristics may include over-washing stress characteristics, under-washing stress characteristics, material entanglement stress characteristics, and foam abnormal stress characteristics, etc.

[0024] The matching result between the stress feature and the preset abnormal stress feature may refer to the matching degree between the stress feature and each preset abnormal stress feature, wherein the matching degree may refer to the similarity between the stress feature and the preset abnormal stress feature.

[0025] A cleaning program may refer to a set of operating steps and processes performed by a cleaning device to clean industrial materials or household clothes. Working parameters of a cleaning program may refer to various parameters that can be adjusted during the running of the cleaning program, which are used to control the working state and cleaning process of the cleaning device.

[0026] Working parameters may include rotation speed, rotation cycle, program running time and auxiliary parts use. Specifically, the rotation speed may refer to the number of revolutions or angles of the cleaning rotating device per unit time; the rotation cycle may refer to the time required for the cleaning rotating device to complete a complete rotation cycle; the program running time may refer to the time from the start to the end of the cleaning program; and the auxiliary parts use may refer to some auxiliary components used by the cleaning equipment during the cleaning process, such as damping devices, etc.

[0027] According to the matching results between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program can be adjusted by determining the preset abnormal stress feature that matches the stress feature most highly as the target preset abnormal stress feature, determining the target adjustment coefficient of each working parameter according to the target preset abnormal stress feature and the correlation between the pre-constructed adjustment coefficient of each working parameter and the preset abnormal stress feature, obtaining the current working parameters of the cleaning program, and calculating the adjusted working parameters of the cleaning program according to the current working parameters and the target adjustment coefficient of each working parameter.

[0028] The adjustment coefficient of the working parameter can be a value used to quantify the adjustment range of the working parameter. The correlation between the adjustment coefficient of each working parameter and the preset abnormal stress feature can be used to describe the corresponding adjustment coefficient of the working parameter to be adopted when a certain preset abnormal stress feature exists.

[0029] Specifically, the adjusted working parameters of the cleaning program can be calculated based on the current working parameters and the target adjustment coefficients of the working parameters, and the adjusted working parameters of the cleaning program can be obtained by multiplying the current working parameters by the corresponding target adjustment coefficients. For example, the adjustment coefficient of the rotation speed corresponding to the washing overstress feature is 0.8, and the current rotation speed is 500 revolutions per minute, then the adjusted rotation speed of the cleaning program is 400 revolutions per minute.

[0030] Optionally, the adjusted working parameters of the cleaning program can be calculated based on the current working parameters and the target adjustment coefficients of each working parameter. The difference between the target adjustment coefficient and 1 can be calculated, and the difference can be multiplied by the matching degree between the stress feature and the target preset abnormal stress feature. The product result can be added to 1 to obtain the correction adjustment coefficient, and the current working parameters and the corresponding correction adjustment coefficient can be multiplied to obtain the adjusted working parameters of the cleaning program. For example, the adjustment coefficient of the rotation speed corresponding to the washing overstress feature is 0.8, the current rotation speed is 500 revolutions per minute, and the matching degree between the stress feature and the washing overstress feature is 90%. The correction adjustment coefficient is 0.82, and the adjusted rotation speed of the cleaning program is 410 revolutions per minute.

[0031] Optionally, the working parameters of the cleaning program can be adjusted according to the matching results between the stress feature and the preset abnormal stress feature. The preset abnormal stress feature whose matching degree with the stress feature exceeds the preset matching threshold can be determined as the target preset abnormal stress feature, and each target adjustment coefficient of each working parameter is determined according to the correlation between each target preset abnormal stress feature and the pre-constructed adjustment coefficient of each working parameter and the preset abnormal stress feature. A weighted average calculation is performed according to the matching degree between the stress feature and each target preset abnormal stress feature and the target adjustment coefficient to obtain a correction adjustment coefficient, and the current working parameter and the corresponding correction adjustment coefficient are multiplied to obtain the adjusted working parameters of the cleaning program. For example, the matching degree between the stress feature and the excessive washing stress feature is 90%, and the matching degree between the stress feature and the abnormal foam stress feature is 80%, both of which exceed the preset matching threshold of 75%. The adjustment coefficient of the rotation speed corresponding to the excessive washing stress feature is 0.8, and the adjustment coefficient of the rotation speed corresponding to the abnormal foam stress feature is 0.6. Then the correction adjustment coefficient is , the current rotation speed is 500 revolutions per minute, and the adjusted rotation speed of the cleaning program is 355 revolutions per minute.

[0032] The working parameters of the cleaning program can be adjusted according to the matching results between the stress characteristics and the preset abnormal stress characteristics. The target working parameter adjustment strategy can be determined according to the matching degree between the stress characteristics and each preset abnormal stress characteristic, and the correlation between the pre-constructed preset abnormal stress characteristics and the working parameter adjustment strategy, the current working parameters of the cleaning program can be obtained, and the adjusted working parameters of the cleaning program can be determined according to the current working parameters and the target working parameter adjustment strategy.

[0033] In the technical solution, optionally, according to the matching result between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program are adjusted, including: Determine the target working parameter adjustment strategy according to the matching degree between the stress feature and each preset abnormal stress feature, and the association relationship between the preset abnormal stress feature and the working parameter adjustment strategy; wherein the preset abnormal stress feature includes at least one of an over-washing stress feature, an under-washing stress feature, a material entanglement stress feature, and a foam abnormal stress feature; The current working parameters of the cleaning program are acquired, and the adjusted working parameters of the cleaning program are determined according to the current working parameters and the target working parameter adjustment strategy.

[0034] The excessive washing stress characteristic may refer to the stress characteristic exhibited when the cleaning equipment washes industrial materials or household clothes with too much force or for too long, causing the cleaning rotating device to be subjected to abnormal stress; the insufficient washing stress characteristic may refer to the stress characteristic exhibited when the cleaning equipment washes industrial materials or household clothes with insufficient force or for too short a time, causing the cleaning rotating device to be subjected to abnormal stress; the material entanglement stress characteristic may refer to the stress characteristic exhibited when industrial materials or household clothes are entangled with each other or around the cleaning rotating device during the cleaning process, causing the cleaning rotating device to be subjected to abnormal stress; the abnormal foam stress characteristic may refer to the stress characteristic exhibited when the amount of foam generated in the cleaning rotating device is abnormal, causing the cleaning rotating device to be subjected to abnormal stress.

[0035] The working parameter adjustment strategy may refer to a series of adjustment measures for working parameters formulated to achieve better cleaning effects for industrial materials or household clothing, protect industrial materials or household clothing, and the cleaning equipment itself. Specifically, the working parameter adjustment strategy may be a joint adjustment strategy for multiple working parameters. The association between the preset abnormal stress feature and the working parameter adjustment strategy may be used to describe the corresponding working parameter adjustment strategy to be adopted in the presence of a certain preset abnormal stress feature. For example, the working parameter adjustment strategy corresponding to the excessive washing stress characteristic may be to adjust the rotation speed to 80% of the original, maintain the rotation cycle unchanged, shorten the program running time to 75% of the original, and maintain the detergent dosage unchanged; the working parameter adjustment strategy corresponding to the insufficient washing stress characteristic may be to adjust the rotation speed to 120% of the original, maintain the rotation cycle unchanged, adjust the program running time to 130% of the original, and adjust the detergent dosage to 120% of the original; the working parameter adjustment strategy corresponding to the material entanglement stress characteristic may be to maintain the rotation speed unchanged, adjust the rotation cycle to 150% of the original, and increase the frequency of forward and reverse alternation; the working parameter adjustment strategy corresponding to the abnormal foam stress characteristic may be to suspend the operation for 3 minutes, adjust the rotation speed to 60% of the original, adjust the rotation cycle to 150% of the original, and adjust the detergent dosage to 80% of the original.

[0036] It can be understood that the target working parameter adjustment strategy is the working parameter adjustment strategy associated with the current stress feature. According to the matching degree between the stress feature and each preset abnormal stress feature, and the association relationship between the preset abnormal stress feature and the working parameter adjustment strategy, the target working parameter adjustment strategy can be determined by determining the preset abnormal stress feature with the highest matching degree with the stress feature as the target preset abnormal stress feature, and using the target preset abnormal stress feature as the query condition to query the stored data of the association relationship between the pre-constructed preset abnormal stress feature and the working parameter adjustment strategy, and the query result includes the target working parameter adjustment strategy.

[0037] The current working parameters of the cleaning program may refer to the working parameters adopted by the cleaning program at the current time point. The current working parameters of the cleaning program are stored on the main control PC board and can be directly read.

[0038] According to the current working parameters and the target working parameter adjustment strategy, the adjusted working parameters of the cleaning program can be determined by determining the working parameters involved in the target working parameter adjustment strategy, and calculating and adjusting the current working parameters according to the specific adjustment coefficients of these working parameters. For example, the current rotation speed is 500 revolutions per minute, the current program running time is 60 minutes, and the stress feature has the highest degree of match with the washing overstress feature, then the working parameter adjustment strategy associated with the washing overstress feature is determined to be the target working parameter adjustment strategy, and the target working parameter adjustment strategy is to adjust the rotation speed to 80% of the original and shorten the program running time to 75% of the original, then it can be calculated that the adjusted rotation speed is 400 revolutions per minute, and the adjusted program running time is 45 minutes.

[0039] The benefit of this arrangement of the present scheme is that by determining the target working parameter adjustment strategy based on the matching degree between the stress characteristics and each preset abnormal stress characteristic and the correlation between the pre-constructed preset abnormal stress characteristics and the working parameter adjustment strategy, and determining the adjusted working parameters of the cleaning program based on the current working parameters and the target working parameter adjustment strategy, the working parameter adjustment strategy to be adopted under each working condition can be accurately determined, thereby quickly responding to abnormal conditions in the operation of the cleaning equipment and realizing dynamic optimization of the working parameters.

[0040] In an embodiment of the present application, during the operation of the cleaning equipment, stress data of the cleaning rotating device inside the cleaning equipment is obtained; stress characteristics are extracted based on the stress data; wherein the stress characteristics include stress peak sequence and phase distribution characteristics; according to the matching result between the stress characteristics and the preset abnormal stress characteristics, the working parameters of the cleaning program are adjusted; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts. The above-mentioned program control method of the cleaning equipment based on stress characteristics can enhance the automation and intelligence level of the cleaning equipment by extracting the stress characteristics of the stress data of the cleaning rotating device inside the cleaning equipment, and adjusting the working parameters of the cleaning program according to the matching result between the stress characteristics and the preset abnormal stress characteristics, so as to timely and accurately respond to various conditions during the operation of the cleaning equipment and ensure the cleaning effect.

[0041] Embodiment 2 Figure 2It is a flow chart of the program control method of the cleaning equipment based on stress characteristics provided in the second embodiment of the present application. This scheme makes a better improvement on the above embodiment, and the specific improvement is: before adjusting the working parameters of the cleaning program according to the matching result of the stress characteristics and the preset abnormal stress characteristics, the method also includes: determining the working mode of the cleaning rotating device according to the stress data; wherein the working mode includes at least one of normal operation, abnormal vibration, load imbalance and mechanical wear; accordingly, adjusting the working parameters of the cleaning program according to the matching result of the stress characteristics and the preset abnormal stress characteristics, including: adjusting the working parameters of the cleaning program according to the matching result of the stress characteristics and the preset abnormal stress characteristics and the working mode; wherein the working parameters include at least one of the rotation speed, rotation cycle, program running time and auxiliary parts use.

[0042] like Figure 2 As shown, the specific steps include: S201, during the operation of the cleaning device, obtaining stress data of a cleaning rotating device inside the cleaning device; S202, extracting stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; S203, determining the operating mode of the cleaning rotating device according to the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance and mechanical wear; The operating mode of the cleaning rotating device can be used to describe the operating state of the cleaning rotating device itself. The operating mode of the cleaning rotating device may include normal operation, abnormal vibration, load imbalance or mechanical wear. Specifically, normal operation means that the cleaning rotating device itself is in a stable and good working state; abnormal vibration means that the cleaning rotating device has vibrations beyond the normal range during operation; load imbalance means that the load borne by the cleaning rotating device is uneven in distribution or size; mechanical wear may refer to the material loss phenomenon caused by friction, fatigue and other reasons during the long-term operation of the cleaning rotating device.

[0043] The working mode of the cleaning rotating device can be determined based on stress data. The stress data can be input into a pre-built support vector machine to obtain the working mode of the cleaning rotating device. The Mel-frequency cepstrum coefficients of the stress data can be extracted as the first eigenvector, and the kurtosis parameter and waveform factor of the stress data can be extracted as the second eigenvector. The first eigenvector and the second eigenvector can be input into a pre-built support vector machine to obtain the working mode of the cleaning rotating device.

[0044] In the technical solution, optionally, determining the working mode of the cleaning rotating device according to the stress data includes: Extracting Mel-frequency cepstrum coefficients of the stress data as a first eigenvector; extracting a kurtosis parameter and a waveform factor of the stress data as a second eigenvector; The first feature vector and the second feature vector are input into a pre-built support vector machine to obtain the working mode of the cleaning rotating device.

[0045] The first eigenvector and the second eigenvector are two eigenvectors extracted from the stress data and related to the working mode of the cleaning rotating device.

[0046] Mel frequency cepstrum coefficients can be obtained by converting stress data from time domain to frequency domain, and then obtaining a set of coefficients that can describe stress characteristics through a series of processing. The Mel frequency cepstrum coefficients of stress data can be extracted as the first eigenvector by pre-emphasizing the stress data to increase the energy of the high frequency part, dividing the stress data into several short frames, and then windowing each frame of stress data, performing fast Fourier transform on each frame of windowed stress data to obtain the spectrum of the stress data, passing the spectrum through a set of Mel filter groups to obtain a Mel spectrum, taking the logarithm of the Mel spectrum, and performing discrete cosine transform on the Mel spectrum after taking the logarithm, converting it to the cepstrum domain to obtain the Mel frequency cepstrum coefficients, and determining the Mel frequency cepstrum coefficients as the first eigenvector.

[0047] The kurtosis parameter can be a statistical parameter describing the shape of the probability density function of stress data, and is used to measure the peak characteristics of stress data; the waveform factor can refer to the ratio of the effective value of stress data to the average value, and can reflect the waveform characteristics of stress data. The method of extracting the kurtosis parameter and the waveform factor of stress data as the second eigenvector can be to perform statistical analysis on the stress data, calculate the kurtosis parameter and the waveform factor, and finally combine the kurtosis parameter and the waveform factor to obtain the second eigenvector.

[0048] Support vector machine is a supervised machine learning algorithm, commonly used for classification and regression analysis; the core goal of support vector machine is to find an optimal hyperplane in the feature space to achieve the division of data of different categories; support vector machine can be trained based on the first eigenvector and the second eigenvector extracted from history, as well as the corresponding operating mode manually annotated. The first eigenvector and the second eigenvector are input into the pre-trained support vector machine, and the pre-trained support vector machine outputs the operating mode of the cleaning rotating device after calculation and prediction.

[0049] The advantage of this arrangement of the present scheme is that by extracting the Mel-frequency cepstrum coefficients of the stress data as the first eigenvector, extracting the kurtosis parameter and the waveform factor of the stress data as the second eigenvector, and inputting the first eigenvector and the second eigenvector into a pre-built support vector machine, the operating mode of the cleaning rotating device is obtained, and the stress data characteristics can be comprehensively characterized from multiple dimensions, thereby realizing accurate identification of the operating mode of the cleaning rotating device.

[0050] S204, adjusting the working parameters of the cleaning program according to the matching result between the stress feature and the preset abnormal stress feature and the working mode; wherein the working parameters include at least one of the rotation speed, rotation cycle, program running time and auxiliary parts use.

[0051] According to the matching result of the stress feature and the preset abnormal stress feature and the working mode, the working parameters of the cleaning program can be adjusted by determining the first target adjustment coefficient according to the working mode and the correlation between the pre-constructed working mode and the adjustment coefficient of each working parameter, obtaining the current working parameters of the cleaning program, and determining the first target working parameters of the cleaning program according to the current working parameters and the first target adjustment coefficient, determining the preset abnormal stress feature with the highest matching degree with the stress feature as the target preset abnormal stress feature, determining the second target adjustment coefficient of each working parameter according to the target preset abnormal stress feature and the correlation between the pre-constructed adjustment coefficient of each working parameter and the preset abnormal stress feature, and determining the adjusted working parameters of the cleaning program according to the first target working parameter and the second target adjustment coefficient. For example, if the first adjustment coefficient of the rotation speed corresponding to the load imbalance is 0.5 and the current rotation speed is 500 rpm, then the first target rotation speed of the cleaning program is 250 rpm, and the second adjustment coefficient of the rotation speed corresponding to the excessive washing stress feature is 0.8, then the adjusted rotation speed of the cleaning program is 200 rpm.

[0052] Optionally, after determining the first target working parameter and the second target adjustment coefficient corresponding to each working parameter, the preset correlation degree between the working mode and the preset abnormal stress characteristic can also be obtained; accordingly, according to the first target working parameter and the second target adjustment coefficient, the method for determining the adjusted working parameters of the cleaning program can be to calculate the difference between the second target adjustment coefficient and 1 as the first difference, calculate the difference between 1 and the preset correlation degree between the target working mode and the target preset abnormal stress characteristic as the second difference, multiply the current working parameter, the first difference and the second difference, add the first target working parameter and the multiplication result, and obtain the adjusted working parameters of the cleaning program. For example, the first adjustment coefficient of the rotation speed corresponding to the load imbalance is 0.5, and the current rotation speed is 500 revolutions per minute, then the first target rotation speed of the cleaning program is 250 revolutions per minute, the preset correlation degree between the load imbalance and the washing overstress characteristic is 60%, and the second adjustment coefficient of the rotation speed corresponding to the washing overstress characteristic is 0.8, then the adjusted rotation speed of the cleaning program is Revolutions per minute.

[0053] The advantage of this arrangement of the present scheme is that by determining the operating mode of the cleaning rotating device based on the stress data and adjusting the working parameters of the cleaning program based on the matching results of the stress characteristics with the preset abnormal stress characteristics and the operating mode, the condition of the cleaning rotating device itself can be taken into consideration during the optimization and adjustment of the working parameters to obtain more accurate adjusted working parameters.

[0054] Embodiment 3 Figure 3 It is a flow chart of the program control method of the cleaning equipment based on stress characteristics provided in the third embodiment of the present application. This scheme makes a better improvement on the above embodiment, and the specific improvement is: according to the matching result of the stress characteristics and the preset abnormal stress characteristics and the working mode, the working parameters of the cleaning program are adjusted, including: when the working mode is load imbalance, the mass eccentricity of the cleaning rotating device is determined according to the matching result of the stress characteristics and the preset abnormal stress characteristics; the load mass in the cleaning rotating device is obtained, and the rotation speed in the working parameters of the cleaning program is determined according to the mass eccentricity and the load mass.

[0055] like Figure 3 As shown, the specific steps include: S301, during the operation of the cleaning device, obtaining stress data of a cleaning rotating device inside the cleaning device; S302, extracting stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; S303, determining the operating mode of the cleaning rotating device according to the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance and mechanical wear; S304, when the working mode is load imbalance, determining the mass eccentricity of the cleaning rotating device according to a matching result between the stress feature and a preset abnormal stress feature; The mass eccentricity can be a parameter used to describe the degree of uneven load distribution in the cleaning rotating device. The method of determining the mass eccentricity of the cleaning rotating device according to the matching result of the stress feature and the preset abnormal stress feature can be adopted to determine the target preset abnormal stress feature according to the matching result of the stress feature and the preset abnormal stress feature, preliminarily determine the possible range of the mass eccentricity according to the target preset abnormal stress feature, and adjust the mass eccentricity in the possible range according to the current stress feature based on the theoretical model of rotor dynamics by using the least squares method, so that the error between the theoretically calculated stress feature and the current stress feature is minimized, thereby obtaining an estimated value of the mass eccentricity.

[0056] S305, obtaining the load mass in the cleaning rotation device, and determining the rotation speed in the working parameters of the cleaning program according to the mass eccentricity and the load mass.

[0057] The load mass in the cleaning rotating device may refer to the mass of industrial materials or household clothes in the cleaning rotating device. The load mass in the cleaning rotating device may be acquired by a pressure sensor before the cleaning program starts to be executed.

[0058] The method of determining the rotation speed in the working parameters of the cleaning program based on the mass eccentricity and the load mass can be achieved by multiplying the square value of the natural frequency, the load mass and the mass eccentricity, dividing the stiffness coefficient of the cleaning rotating device by the product, and obtaining the rotation speed in the working parameters of the cleaning program.

[0059] In the technical solution, optionally, after determining the rotation speed in the working parameters of the cleaning program according to the mass eccentricity and the load mass, the method further includes: calculating a kurtosis parameter of the stress data; In the case that the kurtosis parameter exceeds the preset kurtosis threshold, it is determined to use a damping device to provide a counteracting force in the cleaning procedure.

[0060] The preset kurtosis threshold may be a preset upper limit of a kurtosis parameter indicating that the load imbalance problem cannot be solved by adjusting the rotation speed.

[0061] The damping device may be a device that can consume vibration energy and reduce vibration amplitude, such as a viscous damper, a friction damper, etc. Specifically, a viscous damper consumes vibration energy by using the resistance of a viscous fluid, and a friction damper hinders vibration by friction between components.

[0062] The reverse force may refer to a force in the opposite direction to the force causing the vibration. When the cleaning rotating device is unbalanced in load, a force causing the cleaning rotating device to vibrate is generated, and the reverse force provided by the damping device is in the opposite direction to the force causing the vibration.

[0063] In the technical solution, optionally, before determining to use a damping device to provide a reverse force in the cleaning procedure, the method further includes: Obtaining the force-bearing area of ​​the cleaning rotating device; Calculating a sudden change gradient of the stress data; The magnitude of the reverse force is determined according to the force-bearing area and the sudden change gradient.

[0064] The force bearing area of ​​the cleaning rotating device may refer to the material area of ​​the cleaning rotating device that contacts and bears force on industrial materials or household clothing. The force bearing area of ​​the cleaning rotating device may be obtained by referring to the design documents or product manuals of the cleaning equipment.

[0065] The sudden change gradient of stress data can be used to describe the severity of the change of stress data in a certain period of time or spatial position. The sudden change gradient of stress data can be calculated by numerical difference method, least squares fitting straight line method, wavelet transform-based method or finite element analysis method.

[0066] The magnitude of the reverse force can be determined according to the force-bearing area and the sudden change gradient by multiplying the force-bearing area, the sudden change gradient and a preset compensation coefficient to obtain the magnitude of the reverse force.

[0067] The benefit of this arrangement of the present invention is that by determining the magnitude of the reverse force according to the force-bearing area of ​​the cleaning rotating device and the sudden change gradient of the stress data, the damping device can be helped to provide a precisely adapted reverse force, thereby improving the solution to the load balancing problem.

[0068] The advantage of this arrangement of the present scheme is that by determining to use a damping device to provide a reverse force in the cleaning procedure when the kurtosis parameter of the stress data exceeds a preset kurtosis threshold, the high-frequency impact load in the cleaning rotating device can be dynamically sensed and suppressed, thereby avoiding fatigue damage to the cleaning rotating device caused by stress concentration.

[0069] The benefit of this arrangement of the present scheme is that, by determining the mass eccentricity of the cleaning rotating device according to the matching result of the stress characteristics and the preset abnormal stress characteristics when the working mode is load imbalance, and determining the rotation speed in the working parameters of the cleaning program according to the mass eccentricity and the load mass, the adjusted rotation speed can be accurately adapted to the load condition, avoiding incomplete cleaning or excessive cleaning due to load imbalance, ensuring uniform and efficient cleaning operations, and improving the overall cleaning quality.

[0070] Embodiment 4 Figure 4 Schematic diagram of the structure of the program control device of the cleaning equipment based on stress characteristics provided in the fourth embodiment of the present application. Figure 4 As shown, the device comprises: A stress data acquisition module 410 is used to acquire stress data of a cleaning rotating device inside the cleaning device during operation of the cleaning device; A stress feature extraction module 420, configured to extract stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; The working parameter adjustment module 430 is used to adjust the working parameters of the cleaning program according to the matching result between the stress characteristics and the preset abnormal stress characteristics; wherein the working parameters include at least one of the rotation speed, rotation cycle, program running time and auxiliary parts use.

[0071] In an embodiment of the present application, a stress data acquisition module is used to acquire stress data of a cleaning rotating device inside the cleaning device during operation of the cleaning device; a stress feature extraction module is used to extract stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; a working parameter adjustment module is used to adjust the working parameters of the cleaning program according to the matching results between the stress features and the preset abnormal stress features; wherein the working parameters include at least one of the rotation speed, rotation cycle, program running time, and auxiliary parts use. The program control device of the cleaning device based on stress features can enhance the automation and intelligence level of the cleaning device, respond to various conditions during operation of the cleaning device in a timely and accurate manner, and ensure the cleaning effect by extracting the stress features of the stress data of the cleaning rotating device inside the cleaning device and adjusting the working parameters of the cleaning program according to the matching results between the stress features and the preset abnormal stress features.

[0072] The program control device of the cleaning equipment based on stress characteristics in the embodiment of the present application can be a device, or a component, an integrated circuit, or a chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplary, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a palmtop computer, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., and the embodiment of the present application is not specifically limited.

[0073] The program control device of the cleaning device based on stress characteristics in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0074] The program control device of the cleaning equipment based on stress characteristics provided in the embodiment of the present application can realize each process implemented in the above-mentioned embodiments one to three, and will not be described again here to avoid repetition.

[0075] Embodiment 5 like Figure 5 As shown, an embodiment of the present application also provides a cleaning device 500, including a processor 501, a memory 502, and a program or instruction stored in the memory 502 and executable on the processor 501. When the program or instruction is executed by the processor 501, each process of the above-mentioned program control method embodiment of the cleaning device based on stress characteristics is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0076] Embodiment 6 An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned program control method embodiment of the cleaning equipment based on stress characteristics is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0077] The processor is the processor in the cleaning device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0078] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0079] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0080] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0081] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A program control method for cleaning equipment based on stress characteristics, characterized in that: The method comprises: During the operation of the cleaning device, obtaining stress data of a cleaning rotating device inside the cleaning device; Extracting stress characteristics based on the stress data; wherein the stress characteristics include stress peak sequence and phase distribution characteristics; According to the matching result between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program are adjusted; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

2. The program control method of the cleaning equipment based on stress characteristics according to claim 1, characterized in that: According to the matching result between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program are adjusted, including: Determine the target working parameter adjustment strategy according to the matching degree between the stress feature and each preset abnormal stress feature, and the association relationship between the preset abnormal stress feature and the working parameter adjustment strategy; wherein the preset abnormal stress feature includes at least one of an over-washing stress feature, an under-washing stress feature, a material entanglement stress feature, and a foam abnormal stress feature; The current working parameters of the cleaning program are acquired, and the adjusted working parameters of the cleaning program are determined according to the current working parameters and the target working parameter adjustment strategy.

3. The program control method of the cleaning equipment based on stress characteristics according to claim 1, characterized in that: Before adjusting the working parameters of the cleaning program according to the matching result between the stress feature and the preset abnormal stress feature, the method further includes: Determine the operating mode of the cleaning rotating device according to the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance and mechanical wear; Accordingly, according to the matching result between the stress feature and the preset abnormal stress feature, the working parameters of the cleaning program are adjusted, including: According to the matching result between the stress feature and the preset abnormal stress feature and the working mode, the working parameters of the cleaning program are adjusted; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

4. The program control method of the cleaning equipment based on stress characteristics according to claim 3, characterized in that: According to the matching result between the stress feature and the preset abnormal stress feature and the working mode, the working parameters of the cleaning program are adjusted, including: When the working mode is load imbalance, determining the mass eccentricity of the cleaning rotating device according to the matching result between the stress characteristic and the preset abnormal stress characteristic; The load mass in the cleaning rotating device is obtained, and the rotation speed in the working parameters of the cleaning program is determined according to the mass eccentricity and the load mass.

5. The program control method of the cleaning equipment based on stress characteristics according to claim 4, characterized in that: After determining the rotation speed in the working parameters of the cleaning program according to the mass eccentricity and the load mass, the method further includes: calculating a kurtosis parameter of the stress data; In the case that the kurtosis parameter exceeds the preset kurtosis threshold, it is determined to use a damping device to provide a counteracting force in the cleaning procedure.

6. The program control method of the cleaning equipment based on stress characteristics according to claim 5, characterized in that: Prior to determining to use a damping device to provide a counter force in a cleaning procedure, the method further includes: Obtaining the force-bearing area of ​​the cleaning rotating device; Calculating a sudden change gradient of the stress data; The magnitude of the reverse force is determined according to the force bearing area and the sudden change gradient.

7. The program control method of the cleaning equipment based on stress characteristics according to claim 3, characterized in that: Determining the operating mode of the cleaning rotating device according to the stress data includes: Extracting Mel-frequency cepstrum coefficients of the stress data as a first eigenvector; extracting a kurtosis parameter and a waveform factor of the stress data as a second eigenvector; The first feature vector and the second feature vector are input into a pre-built support vector machine to obtain the working mode of the cleaning rotating device.

8. A program control device for cleaning equipment based on stress characteristics, characterized in that: The device comprises: A stress data acquisition module, used to acquire stress data of a cleaning rotating device inside the cleaning device during operation of the cleaning device; A stress feature extraction module, used to extract stress features based on the stress data; wherein the stress features include stress peak sequence and phase distribution features; A working parameter adjustment module is used to adjust the working parameters of the cleaning program according to the matching result between the stress characteristics and the preset abnormal stress characteristics; wherein the working parameters include at least one of the rotation speed, the rotation cycle, the program running time and the use of auxiliary parts.

9. A cleaning device, characterized in that: It comprises a processor, a memory and a program or instruction stored in the memory and executable on the processor, wherein when the program or instruction is executed by the processor, the steps of the program control method of the cleaning equipment based on stress characteristics as described in any one of claims 1 to 7 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the program control method of a cleaning device based on stress characteristics as described in any one of claims 1 to 7 are implemented.

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