A program control method and device of a cleaning device based on stress characteristics, a cleaning device, and a medium

Abstract

The application discloses a program control method and device of a cleaning equipment based on stress characteristics, a cleaning equipment and a medium, and belongs to the general cleaning technical field.The method comprises the following steps: obtaining stress data of a cleaning rotating device inside the cleaning equipment during the operation of the cleaning equipment; extracting stress characteristics based on the stress data; and adjusting working parameters of a cleaning program according to the matching result of the stress characteristics and preset abnormal stress characteristics; wherein the working parameters comprise at least one of a rotating speed, a rotating period, a program operation time and the use of an auxiliary part.The technical scheme can enhance the automation and intelligent level of the cleaning equipment, timely and accurately cope with various conditions during the operation of the cleaning equipment, and guarantee 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 result of the stress characteristics and the preset abnormal stress characteristics.

Description

Technical Field

[0001] This 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 Technology

[0002] Cleaning equipment, as a common product in modern manufacturing and modern households, has been deeply integrated into various industrial scenarios and daily life. However, most existing cleaning equipment operates according to fixed working parameters based on preset programs. Although the preset programs take into account the materials and degree of stains of common industrial materials or household clothing, the actual cleaning process is complex and variable in real time. For example, excessive foam may be generated during the cleaning process, causing foam overflow or foam residue on the cleaned industrial materials or household clothing.

[0003] When encountering problems that the preset programs cannot solve, users generally need to manually adjust the cleaning program's parameters to achieve the best cleaning results for industrial materials or household clothing. However, this requires users to rely on experience and judgment, and the operation process is cumbersome and complex. For users lacking relevant professional knowledge and experience, it is not only difficult to accurately adjust the working parameters, but improper operation may also damage the cleaning equipment or increase energy consumption, resulting in neither the desired cleaning effect nor the waste of resources and increased operating costs.

[0004] Therefore, how to automatically and accurately control the operating parameters of cleaning equipment is a problem that urgently needs to be solved by those in this field. Summary of the Invention

[0005] This 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 cleaning equipment, responding to various conditions during the operation of cleaning equipment in a timely and accurate manner, and ensuring cleaning effect.

[0006] In a first aspect, this application provides a program control method for a cleaning device based on stress characteristics, the method comprising:

[0007] During the operation of the cleaning equipment, stress data of the cleaning rotation device inside the cleaning equipment is acquired;

[0008] Stress features are extracted based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features;

[0009] Based on 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 following: rotation speed, rotation cycle, program running time, and the use of auxiliary parts.

[0010] Secondly, this application provides a program control device for a cleaning equipment based on stress characteristics, the device comprising:

[0011] The stress data acquisition module is used to acquire stress data of the cleaning rotation device inside the cleaning equipment during the operation of the cleaning equipment.

[0012] 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;

[0013] The working parameter adjustment module is used to adjust the working parameters of the cleaning program based on the matching result between the stress characteristics and the preset abnormal stress characteristics; wherein, the working parameters include at least one of rotation speed, rotation cycle, program running time, and the use of auxiliary parts.

[0014] Thirdly, this application provides a cleaning device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0015] Fourthly, this application provides a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0016] In this application, during the operation of the cleaning equipment, stress data of the cleaning rotation device inside the cleaning equipment is acquired; stress features are extracted based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features; and the working parameters of the cleaning program are adjusted according to the matching result of the stress features and preset abnormal stress features; wherein, the working parameters include at least one of rotation speed, rotation cycle, program running time, and the use of auxiliary parts. The above-described program control method for cleaning equipment based on stress features, by extracting stress features from the stress data of the cleaning rotation device inside the cleaning equipment and adjusting the working parameters of the cleaning program according to the matching result of the stress features and preset abnormal stress features, can enhance the automation and intelligence level of the cleaning equipment, respond promptly and accurately to various conditions during the operation of the cleaning equipment, and ensure cleaning effectiveness. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the program control method for a cleaning device based on stress characteristics provided in Embodiment 1 of this application;

[0018] Figure 2This is a schematic flowchart of the program control method for a cleaning device based on stress characteristics provided in Embodiment 2 of this application;

[0019] Figure 3 This is a flowchart illustrating the program control method for a cleaning device based on stress characteristics provided in Embodiment 3 of this application;

[0020] Figure 4 This is a schematic diagram of the program control device for a cleaning equipment based on stress characteristics provided in Embodiment 4 of this application;

[0021] Figure 5 This is a schematic diagram of the cleaning equipment provided in Embodiment 5 of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0023] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0024] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0025] The following description, in conjunction with the accompanying drawings, details the program control method, apparatus, cleaning equipment, and medium for stress-characteristic cleaning equipment provided in this application, through specific embodiments and application scenarios.

[0026] Example 1

[0027] Figure 1 This is a schematic flowchart of the program control method for a cleaning device based on stress characteristics provided in Embodiment 1 of this application. Figure 1 As shown, the specific steps include the following:

[0028] S101, During the operation of the cleaning equipment, obtain the stress data of the cleaning rotation device inside the cleaning equipment;

[0029] First, this application is applicable to scenarios where industrial materials or household clothing require cleaning. Based on the above usage scenarios, it is understood that the executing entity of this application can be a 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 clothing reaches the optimal state.

[0030] Cleaning equipment can be a device used to clean industrial materials or household clothing. In industrial settings, cleaning equipment can be a large industrial cleaning machine used to clean various industrial parts or raw materials, possessing powerful cleaning capabilities and diverse cleaning functions to adapt to the characteristics and levels of dirt of different industrial materials; in household settings, cleaning equipment can be a washing machine that can wash various types of clothing.

[0031] A cleaning rotating device can refer to a component in cleaning equipment that generates a rotating motion to assist in cleaning, such as the impeller or drum in a washing machine.

[0032] Stress refers to the internal forces that interact between different parts of an object when it deforms due to external factors (such as force, humidity, or changes in temperature). In this scheme, stress data reflects the magnitude and distribution of forces experienced by the cleaning rotating device during operation. Stress data of the cleaning rotating device can be collected using devices such as strain gauges, fiber optic sensors, or pressure sensors.

[0033] S102, extract stress features based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features;

[0034] Stress characteristics refer to key information extracted from stress data that reflects the working state of the cleaning rotating device and the cleaning status of industrial materials or household clothing within it. Stress characteristics can include stress peak sequence and phase distribution characteristics. Specifically, the stress peak sequence refers to a set of data formed by arranging stress peaks in chronological order of their occurrence, where the stress peaks can refer to the maximum values ​​of the stress data. The phase distribution characteristics refer to the distribution of stress data across different phases, where the phase can be a parameter describing the position of the signal within one cycle.

[0035] One method for extracting stress features from stress data is to input the stress data into a pre-trained machine learning model, which then outputs the stress features. Another method involves using peak detection algorithms to extract stress peaks from the stress data and arranging them in chronological order to form a stress peak sequence; phase distribution features can be extracted using phase-locked loop (PLL) technology or zero-crossing detection.

[0036] S103, based on 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 rotation speed, rotation cycle, program running time, and the use of auxiliary parts.

[0037] Preset abnormal stress characteristics can be pre-constructed stress characteristics that indicate abnormal working conditions of the cleaning rotating device or poor cleaning conditions of industrial materials or household clothes in the cleaning rotating device. Preset abnormal stress characteristics can include over-washing stress characteristics, under-washing stress characteristics, material entanglement stress characteristics, and foam abnormal stress characteristics, etc.

[0038] The matching result between stress characteristics and preset abnormal stress characteristics can refer to the degree of matching between the stress characteristics and each preset abnormal stress characteristic. Specifically, the degree of matching can refer to the similarity between the stress characteristics and the preset abnormal stress characteristics.

[0039] A cleaning program can refer to a set of operational steps and processes performed by cleaning equipment to clean industrial materials or household clothing. The operating parameters of a cleaning program refer to various adjustable parameters used to control the working status of the cleaning equipment and the cleaning process.

[0040] Operating parameters may include rotation speed, rotation cycle, program running time, and the use of auxiliary parts. Specifically, rotation speed refers to the number of rotations or angles of the cleaning rotation device per unit time; rotation cycle refers to the time required for the cleaning rotation device to complete one complete rotation cycle; program running time refers to the duration of the cleaning program from start to finish; and the use of auxiliary parts refers to some auxiliary components used by the cleaning equipment during the cleaning process, such as damping devices.

[0041] The method for adjusting the working parameters of the cleaning program based on the matching results between the stress characteristics and the preset abnormal stress characteristics can be as follows: the preset abnormal stress characteristic with the highest matching degree with the stress characteristics is determined as the target preset abnormal stress characteristic; the target adjustment coefficient of each working parameter is determined based on the target preset abnormal stress characteristic and the correlation between the pre-constructed adjustment coefficients of each working parameter and the preset abnormal stress characteristic; the current working parameters of the cleaning program are obtained; and the adjusted working parameters of the cleaning program are calculated based on the current working parameters and the target adjustment coefficients of each working parameter.

[0042] The adjustment coefficient of the working parameters can be a numerical value used to quantify the adjustment range of the working parameters. The correlation between the adjustment coefficients of each working parameter and the preset abnormal stress characteristics can be used to describe the corresponding adjustment coefficients of the working parameters that should be adopted when a certain preset abnormal stress characteristic exists.

[0043] Specifically, the adjusted operating parameters of the cleaning program can be calculated by multiplying the current operating parameters by the corresponding target adjustment coefficients. For example, if the adjustment coefficient for the rotation speed corresponding to the excessive washing stress characteristic is 0.8, and the current rotation speed is 500 revolutions per minute, then the adjusted rotation speed of the cleaning program will be 400 revolutions per minute.

[0044] Optionally, the adjusted operating parameters of the cleaning program can be calculated based on the current operating parameters and the target adjustment coefficients for each operating parameter. This can be achieved by calculating the difference between the target adjustment coefficient and 1, multiplying this difference by the degree of matching between the stress characteristic and the target preset abnormal stress characteristic, adding the product to 1 to obtain the correction adjustment coefficient, and then multiplying the current operating parameters by the corresponding correction adjustment coefficient to obtain the adjusted operating parameters of the cleaning program. For example, if the adjustment coefficient for the rotation speed corresponding to the excessive washing stress characteristic is 0.8, the current rotation speed is 500 rpm, and the degree of matching between the stress characteristic and the excessive washing stress characteristic is 90%, then the correction adjustment coefficient is 0.82, and the adjusted rotation speed of the cleaning program is 410 rpm.

[0045] Optionally, adjusting the cleaning program's operating parameters based on the matching results of stress characteristics and preset abnormal stress characteristics can also be achieved by identifying preset abnormal stress characteristics whose matching degree with the stress characteristics exceeds a preset matching threshold as target preset abnormal stress characteristics. Based on the correlation between each target preset abnormal stress characteristic and the pre-built adjustment coefficients of each operating parameter and the preset abnormal stress characteristics, target adjustment coefficients for each operating parameter are determined. A weighted average is then calculated based on the matching degree between the stress characteristics and each target preset abnormal stress characteristic, along with the target adjustment coefficients, to obtain a corrected adjustment coefficient. The current operating parameters are then multiplied by the corresponding corrected adjustment coefficient to obtain the adjusted operating parameters of the cleaning program. For example, if the matching degree between the stress characteristics and the over-washing stress characteristics is 90%, and the matching degree between the stress characteristics and the foam abnormal stress characteristics is 80%, both exceeding the preset matching threshold of 75%, and the adjustment coefficient for the rotation speed corresponding to the over-washing stress characteristics is 0.8, and the adjustment coefficient for the rotation speed corresponding to the foam abnormal stress characteristics is 0.6, then the corrected adjustment coefficient is... If the current rotation speed is 500 revolutions per minute, then the adjusted rotation speed of the cleaning program will be 355 revolutions per minute.

[0046] The cleaning procedure's working parameters can be adjusted based on the matching results between stress characteristics and preset abnormal stress characteristics. Alternatively, the target working parameter adjustment strategy can be determined based on the degree of matching between stress characteristics and each preset abnormal stress characteristic, as well as the correlation between the pre-built preset abnormal stress characteristics and the working parameter adjustment strategy. The current working parameters of the cleaning procedure can then be obtained, and the adjusted working parameters of the cleaning procedure can be determined based on the current working parameters and the target working parameter adjustment strategy.

[0047] In this technical solution, optionally, the working parameters of the cleaning procedure are adjusted based on the matching result between the stress characteristics and the preset abnormal stress characteristics, including:

[0048] Based on the degree of matching 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 target working parameter adjustment strategy is determined; wherein, the preset abnormal stress characteristics include at least one of the following: excessive washing stress characteristics, insufficient washing stress characteristics, material entanglement stress characteristics, and foam abnormal stress characteristics.

[0049] The current working parameters of the cleaning program are obtained, and the adjusted working parameters of the cleaning program are determined based on the current working parameters and the target working parameter adjustment strategy.

[0050] Over-washing stress characteristics refer to the stress characteristics exhibited when cleaning equipment applies excessive washing force or time to industrial materials or household clothes, causing abnormal stress on the cleaning rotating device. Under-washing stress characteristics refer to the stress characteristics exhibited when cleaning equipment applies insufficient washing force or time to industrial materials or household clothes, causing abnormal stress on the cleaning rotating device. Material entanglement stress characteristics refer to the stress characteristics exhibited when industrial materials or household clothes become entangled with each other or entangled on the cleaning rotating device during the cleaning process, causing abnormal stress on the cleaning rotating device. Abnormal foam stress characteristics refer to the stress characteristics exhibited when the amount of foam generated in the cleaning rotating device is abnormal, causing abnormal stress on the cleaning rotating device.

[0051] Operating parameter adjustment strategies refer to a series of measures to adjust operating parameters in order to achieve better cleaning results for industrial materials or household clothing, protect these materials or clothing, and protect the cleaning equipment itself. Specifically, an operating parameter adjustment strategy can be a combined adjustment strategy for multiple operating parameters. The correlation between preset abnormal stress characteristics and operating parameter adjustment strategies can be used to describe the corresponding operating parameter adjustment strategy to be adopted when a certain preset abnormal stress characteristic exists. For example, the working parameter adjustment strategy corresponding to the over-washing stress characteristic could be to adjust the rotation speed to 80% of the original, keep the rotation cycle unchanged, shorten the program running time to 75% of the original, and keep the detergent dosage unchanged; the working parameter adjustment strategy corresponding to the under-washing stress characteristic could be to adjust the rotation speed to 120% of the original, keep 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 could be to keep the rotation speed unchanged, adjust the rotation cycle to 150% of the original, and increase the frequency of alternating forward and reverse rotation; the working parameter adjustment strategy corresponding to the foam abnormal stress characteristic could be to pause 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.

[0052] Understandably, the target working parameter adjustment strategy is the working parameter adjustment strategy associated with the current stress characteristics. Based on the degree of matching between the stress characteristics and each preset abnormal stress characteristic, and the correlation between the pre-built preset abnormal stress characteristics and the working parameter adjustment strategies, the target working parameter adjustment strategy can be determined by identifying the preset abnormal stress characteristic with the highest degree of matching with the stress characteristics as the target preset abnormal stress characteristic. Using the target preset abnormal stress characteristic as the query condition, the stored data on the correlation between the pre-built preset abnormal stress characteristics and the working parameter adjustment strategies is queried, and the query results include the target working parameter adjustment strategy.

[0053] The current operating parameters of the cleaning program refer to the operating parameters used by the cleaning program at the current point in time. These parameters are stored on the main control PC board and can be directly read.

[0054] The method for determining the adjusted operating parameters of a cleaning program based on current operating parameters and the target operating parameter adjustment strategy can be as follows: Identify the operating parameters involved in the target operating parameter adjustment strategy, and then calculate and adjust the current operating parameters based on the specific adjustment coefficients of these parameters. For example, if the current rotation speed is 500 revolutions per minute, the current program running time is 60 minutes, and the stress characteristics have the highest matching degree with the over-wash stress characteristics, then the operating parameter adjustment strategy associated with the over-wash stress characteristics is determined as the target operating parameter adjustment strategy. If the target operating 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 the adjusted rotation speed can be calculated to be 400 revolutions per minute, and the adjusted program running time to be 45 minutes.

[0055] The advantage of this scheme is that by determining the target working parameter adjustment strategy based on the matching degree between stress characteristics and each preset abnormal stress characteristic, as well as the correlation between the pre-built preset abnormal stress characteristics and the working parameter adjustment strategy, and by 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 working parameters.

[0056] In this embodiment, during the operation of the cleaning equipment, stress data of the cleaning rotation device inside the cleaning equipment is acquired; stress features are extracted based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features; and the working parameters of the cleaning program are adjusted according to the matching result of the stress features and preset abnormal stress features; wherein, the working parameters include at least one of rotation speed, rotation cycle, program running time, and the use of auxiliary parts. The above-described program control method for cleaning equipment based on stress features, by extracting stress features from the stress data of the cleaning rotation device inside the cleaning equipment and adjusting the working parameters of the cleaning program according to the matching result of the stress features and preset abnormal stress features, can enhance the automation and intelligence level of the cleaning equipment, respond promptly and accurately to various conditions during the operation of the cleaning equipment, and ensure cleaning effectiveness.

[0057] Example 2

[0058] Figure 2This is a flowchart illustrating the program control method for a cleaning device based on stress characteristics provided in Embodiment 2 of this application. This solution makes a further improvement to the above embodiment, specifically: before adjusting the working parameters of the cleaning program based on the matching result of the stress characteristics and preset abnormal stress characteristics, the method further includes: determining the operating mode of the cleaning rotation device based on the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance, and mechanical wear; correspondingly, adjusting the working parameters of the cleaning program based on the matching result of the stress characteristics and preset abnormal stress characteristics includes: adjusting the working parameters of the cleaning program based on the matching result of the stress characteristics and preset abnormal stress characteristics and the operating mode; wherein the working parameters include at least one of rotation speed, rotation cycle, program running time, and the use of auxiliary parts.

[0059] like Figure 2 As shown, the specific steps include the following:

[0060] S201, During the operation of the cleaning equipment, obtain stress data of the cleaning rotation device inside the cleaning equipment;

[0061] S202, extract stress features based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features;

[0062] S203, determine the operating mode of the cleaning rotating device based on the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance, and mechanical wear;

[0063] The operating mode of the cleaning rotary device can be used to describe the operating status of the device itself. These modes can include normal operation, abnormal vibration, load imbalance, or mechanical wear. Specifically, normal operation indicates that the cleaning rotary device is in a stable and good working condition; abnormal vibration indicates that the device experiences vibrations exceeding the normal range during operation; load imbalance indicates that the load on the device is unevenly distributed or of varying magnitude; and mechanical wear refers to material loss caused by friction, fatigue, or other factors during long-term operation.

[0064] Determining the operating mode of the cleaning rotating device based on stress data can be achieved by inputting the stress data into a pre-built support vector machine to obtain the operating mode of the cleaning rotating device; alternatively, the Mel frequency cepstral coefficients of the stress data can be extracted as the first feature vector, and the kurtosis parameters and waveform factors of the stress data can be extracted as the second feature vector. The first and second feature vectors can then be input into a pre-built support vector machine to obtain the operating mode of the cleaning rotating device.

[0065] In this technical solution, optionally, determining the operating mode of the cleaning rotation device based on the stress data includes:

[0066] The Mel frequency cepstral coefficients of the stress data are extracted as the first feature vector;

[0067] Extract the kurtosis parameter and waveform factor of the stress data as a second feature vector;

[0068] The first feature vector and the second feature vector are input into a pre-constructed support vector machine to obtain the operating mode of the cleaning rotation device.

[0069] The first and second feature vectors are two feature vectors extracted from stress data that are related to the operating conditions of the cleaning rotating device.

[0070] Mel frequency cepstral coefficients can be obtained by transforming stress data from the time domain to the frequency domain and then processing it to obtain a set of coefficients that describe the stress characteristics. One method for extracting the Mel frequency cepstral coefficients of stress data as the first eigenvector is to pre-emphasize the stress data to enhance the energy of the high-frequency components, divide the stress data into several short frames, window each frame of stress data, perform a Fast Fourier Transform on each windowed frame of stress data to obtain the stress data spectrum, pass the spectrum through a set of Mel filters to obtain the Mel spectrum, take the logarithm of the Mel spectrum, and then perform a Discrete Cosine Transform on the logarithmic Mel spectrum to transform it into the cepstral domain, obtaining the Mel frequency cepstral coefficients, which are then used as the first eigenvector.

[0071] Kurtosis parameter can be a statistical parameter describing the shape of the probability density function of stress data, used to measure the peak characteristics of stress data; waveform factor can be the ratio of the effective value to the average value of stress data, reflecting the waveform characteristics of stress data. Extracting kurtosis parameter and waveform factor from stress data as a second feature vector can be achieved by performing statistical analysis on the stress data to calculate the kurtosis parameter and waveform factor, and finally combining the kurtosis parameter and waveform factor to obtain the second feature vector.

[0072] Support Vector Machine (SVM) is a supervised machine learning algorithm commonly used in classification and regression analysis. Its core objective is to find an optimal hyperplane in the feature space to separate data into different categories. SVMs can be trained using historically extracted first and second feature vectors, along with manually labeled operating conditions. The first and second feature vectors are input into a pre-trained SVM, which, after calculation and prediction, outputs the operating conditions of the cleaning rotating device.

[0073] The advantage of this scheme is that by extracting the Mel frequency cepstral coefficients of the stress data as the first feature vector and extracting the kurtosis parameter and waveform factor of the stress data as the second feature vector, and inputting the first feature vector and the second feature vector into a pre-built support vector machine, the operating mode of the cleaning rotating device can be obtained. This can comprehensively characterize the stress data features from multiple dimensions, thereby achieving accurate identification of the operating mode of the cleaning rotating device.

[0074] S204, based on 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; wherein, the working parameters include at least one of rotation speed, rotation cycle, program running time and the use of auxiliary parts.

[0075] The cleaning program's operating parameters are adjusted based on the matching results between stress characteristics and preset abnormal stress characteristics, as well as the operating mode. This can be achieved by determining a first target adjustment coefficient based on the operating mode and the correlation between the pre-built operating mode and the adjustment coefficients of each operating parameter; obtaining the current operating parameters of the cleaning program; determining the first target operating parameters of the cleaning program based on the current operating parameters and the first target adjustment coefficient; identifying the preset abnormal stress characteristic with the highest matching degree with the stress characteristics as the target preset abnormal stress characteristic; determining the second target adjustment coefficients of each operating parameter based on the target preset abnormal stress characteristic and the correlation between the pre-built adjustment coefficients of each operating parameter and the preset abnormal stress characteristic; and finally, determining the adjusted operating parameters of the cleaning program based on the first target operating parameters and the second target adjustment coefficients. For example, if the first adjustment coefficient for the rotation speed corresponding to 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. If the second adjustment coefficient for the rotation speed corresponding to the washing overstress characteristic is 0.8, then the adjusted rotation speed of the cleaning program is 200 rpm.

[0076] 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 condition mode and the preset abnormal stress characteristic can also be obtained. Correspondingly, based on the first target working parameter and the second target adjustment coefficient, the adjusted working parameters of the cleaning program can be determined by calculating the difference between the second target adjustment coefficient and 1 as the first difference, calculating the difference between 1 and the preset correlation degree between the target working condition mode and the target preset abnormal stress characteristic as the second difference, multiplying the current working parameter, the first difference, and the second difference, and adding the first target working parameter to the product result to obtain the adjusted working parameters of the cleaning program. For example, if the first adjustment coefficient for the rotation speed corresponding to 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. If the preset correlation degree between load imbalance and the washing overstress characteristic is 60%, and the second adjustment coefficient for the rotation speed corresponding to the washing overstress characteristic is 0.8, then the adjusted rotation speed of the cleaning program is... Revolves every minute.

[0077] The advantage of this scheme is that by determining the operating mode of the cleaning rotating device based on stress data, and adjusting the working parameters of the cleaning program based on the matching results of stress characteristics and preset abnormal stress characteristics and the operating mode, the condition of the cleaning rotating device itself can be considered during the optimization and adjustment of the working parameters, resulting in more accurate adjusted working parameters.

[0078] Example 3

[0079] Figure 3 This is a flowchart illustrating the program control method for a cleaning device based on stress characteristics provided in Embodiment 3 of this application. This solution makes a further improvement to the above embodiment, specifically by adjusting the working parameters of the cleaning program according to the matching result of the stress characteristics and preset abnormal stress characteristics, and the operating mode. This includes: when the operating mode is load imbalance, determining the mass eccentricity of the cleaning rotating device based on the matching result of the stress characteristics and preset abnormal stress characteristics; obtaining the load mass within the cleaning rotating device; and determining the rotation speed in the working parameters of the cleaning program based on the mass eccentricity and the load mass.

[0080] like Figure 3 As shown, the specific steps include the following:

[0081] S301, During the operation of the cleaning equipment, obtain the stress data of the cleaning rotation device inside the cleaning equipment;

[0082] S302, extract stress features based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features;

[0083] S303, determine the operating mode of the cleaning rotating device based on the stress data; wherein the operating mode includes at least one of normal operation, abnormal vibration, load imbalance, and mechanical wear;

[0084] S304, when the working condition 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.

[0085] Mass eccentricity can be a parameter used to describe the degree of uneven load distribution in a cleaning rotating device. The mass eccentricity of the cleaning rotating device can be determined by matching stress characteristics with preset abnormal stress characteristics. This can be achieved by determining the target preset abnormal stress characteristics based on the matching results, initially determining the possible range of mass eccentricity based on the target preset abnormal stress characteristics, and then adjusting the mass eccentricity within this possible range using the least squares method based on the theoretical model of rotor dynamics and the current stress characteristics. This minimizes the error between the theoretically calculated stress characteristics and the current stress characteristics, thus obtaining an estimated value for the mass eccentricity.

[0086] S305, obtain the load mass in the cleaning rotating device, and determine the rotation speed in the working parameters of the cleaning program based on the mass eccentricity and the load mass.

[0087] The load mass within the cleaning rotation unit can refer to the mass of industrial materials or household clothing within the unit. This load mass can be measured by a pressure sensor before the cleaning process begins.

[0088] The rotational speed in the cleaning process's working parameters can be determined by multiplying the square of the natural frequency, the load mass, and the mass eccentricity, and then dividing the stiffness coefficient of the cleaning rotating device by the product.

[0089] Optionally, in this technical solution, after determining the rotational speed in the working parameters of the cleaning procedure based on the mass eccentricity and the load mass, the method further includes:

[0090] Calculate the kurtosis parameter of the stress data;

[0091] If the kurtosis parameter exceeds a preset kurtosis threshold, a damping device is determined to be used in the cleaning process to provide a counterforce.

[0092] The preset kurtosis threshold can be a pre-set upper limit of the kurtosis parameter that indicates that adjusting the rotation speed can no longer solve the load imbalance problem.

[0093] A damping device can be a device that dissipates vibration energy and reduces the amplitude of vibration, such as a viscous damper or a friction damper. Specifically, a viscous damper uses the resistance of a viscous fluid to dissipate vibration energy, while a friction damper impedes vibration through friction between components.

[0094] A counterforce can be a force that acts in the opposite direction to the force causing vibration. When a cleaning rotating device experiences load imbalance, it generates a force that causes the device to vibrate. The counterforce provided by the damping device acts in the opposite direction to these vibration-causing forces.

[0095] In this technical solution, optionally, before determining whether to use a damping device to provide a counterforce in the cleaning process, the method further includes:

[0096] Obtain the force-bearing area of ​​the cleaning rotating device;

[0097] Calculate the abrupt gradient of the stress data;

[0098] The magnitude of the reverse force is determined based on the force-bearing area and the abrupt gradient.

[0099] The force-bearing area of ​​a cleaning rotating device refers to the area of ​​the material in contact with industrial materials or household clothing that bears the force. The force-bearing area of ​​a cleaning rotating device can be obtained by consulting the design documents or product manuals of the cleaning equipment.

[0100] The abrupt change gradient of stress data can be used to describe the drastic change of stress data over a certain time period or spatial location. The abrupt change gradient of stress data can be calculated using methods such as numerical difference, least squares linear fitting, wavelet transform-based methods, or finite element analysis.

[0101] The magnitude of the reverse force can be determined by multiplying the force area, the gradient of the abrupt change, and the preset compensation coefficient.

[0102] The advantage of this scheme is that by determining the magnitude of the reverse force based on the force-bearing area of ​​the cleaning rotating device and the abrupt gradient of stress data, it can help the damping device provide a precisely matched reverse force, thereby improving the solution to the load balancing problem.

[0103] The advantage of this scheme is that, by determining that a damping device is used to provide a reverse force in the cleaning process when the kurtosis parameter of the stress data exceeds the preset kurtosis threshold, the high-frequency impact load in the cleaning rotating device can be dynamically sensed and suppressed, thus avoiding fatigue damage to the cleaning rotating device caused by stress concentration.

[0104] The advantage of this solution is that, under the condition of unbalanced load, the mass eccentricity of the cleaning rotating device is determined based on the matching result of stress characteristics and preset abnormal stress characteristics. The rotation speed in the working parameters of the cleaning program is then determined based on the mass eccentricity and the load mass. This allows the adjusted rotation speed to accurately adapt to the load condition, avoiding incomplete or over-cleaning due to load imbalance, ensuring uniform and efficient cleaning operations, and improving the overall cleaning quality.

[0105] Example 4

[0106] Figure 4 This is a schematic diagram of the program control device for a cleaning equipment based on stress characteristics, provided in Embodiment 4 of this application. Figure 4 As shown, the device includes:

[0107] The stress data acquisition module 410 is used to acquire stress data of the cleaning rotating device inside the cleaning equipment during the operation of the cleaning equipment.

[0108] The stress feature extraction module 420 is used to extract stress features based on the stress data; wherein, the stress features include stress peak sequence and phase distribution features;

[0109] The working parameter adjustment module 430 is used to adjust the working parameters of the cleaning program according to the matching result of the stress characteristics and the preset abnormal stress characteristics; wherein, the working parameters include at least one of rotation speed, rotation cycle, program running time, and auxiliary parts.

[0110] In this embodiment, a stress data acquisition module is used to acquire stress data of the cleaning rotation device inside the cleaning equipment during operation; 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; and a working parameter adjustment module is used to adjust the working parameters of the cleaning program according to the matching result of the stress features and preset abnormal stress features; wherein the working parameters include at least one of rotation speed, rotation cycle, program running time, and auxiliary parts usage. The above-mentioned program control device for cleaning equipment based on stress features, by extracting stress features from the stress data of the cleaning rotation device inside the cleaning equipment and adjusting the working parameters of the cleaning program according to the matching result of the stress features and preset abnormal stress features, can enhance the automation and intelligence level of the cleaning equipment, respond promptly and accurately to various conditions during the operation of the cleaning equipment, and ensure cleaning effectiveness.

[0111] The program control device for the stress-characteristic-based cleaning equipment in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0112] The program control device for the stress-characteristic-based cleaning equipment in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0113] The program control device for cleaning equipment based on stress characteristics provided in this application embodiment can realize the various processes implemented in embodiments one to three above. To avoid repetition, it will not be described again here.

[0114] Example 5

[0115] like Figure 5As shown, this application embodiment also provides a cleaning device 500, including a processor 501, a memory 502, and a program or instructions stored in the memory 502 and executable on the processor 501. When the program or instructions are executed by the processor 501, they implement the various processes of the above-described program control method embodiment for a cleaning device based on stress characteristics and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0116] Example 6

[0117] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described program control method embodiment for a cleaning device based on stress characteristics, and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0118] The processor mentioned above is the processor in the cleaning device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0119] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0120] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they 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 this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer 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 (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0121] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0122] The above description is merely a preferred embodiment and the technical principles employed in this application. This 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 depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.

Claims

1. A program control method of a cleaning apparatus based on stress characteristics, characterized by, The method comprises: During operation of the cleaning device, stress data of a cleaning rotating device inside the cleaning device is acquired; stress features are extracted based on the stress data; wherein the stress features comprise a stress peak sequence and a phase distribution feature; Mel-frequency cepstrum coefficients of the stress data are extracted as a first feature vector, kurtosis parameters and waveform factors of the stress data are extracted as a second feature vector, the first feature vector and the second feature vector are input into a pre-constructed support vector machine, and an operating mode of the cleaning rotating device is obtained; wherein the operating mode comprises normal operation, vibration anomaly, load imbalance, and mechanical wear, and the vibration anomaly indicates that the cleaning rotating device has vibration exceeding a normal range during operation; According to a matching result of the stress features and preset abnormal stress features and the operating mode, a working parameter of a cleaning program is adjusted, comprising: In the load imbalance operating mode, a target preset abnormal stress feature is determined according to the matching result of the stress features and the preset abnormal stress features, a possible range of a mass eccentricity is preliminarily determined according to the target preset abnormal stress feature, the mass eccentricity is adjusted in the possible range according to the current stress features based on a theoretical model of rotor dynamics by using a least square method, so that an error between a theoretically calculated stress feature and the current stress feature is minimized, and thus the mass eccentricity is obtained; A load mass inside the cleaning rotating device is acquired, and a rotating speed in the working parameter of the cleaning program is determined according to the mass eccentricity and the load mass; wherein the preset abnormal stress features comprise at least one of over-washing stress features, under-washing stress features, material winding stress features, and foam abnormal stress features; and the working parameter comprises the rotating speed, a rotating period, a program running time, and an auxiliary part usage; After the rotating speed in the working parameter of the cleaning program is determined according to the mass eccentricity and the load mass, a kurtosis parameter of the stress data is calculated, a stress area of the cleaning rotating device is acquired in a case where the kurtosis parameter exceeds a preset kurtosis threshold, a mutation gradient of the stress data is calculated, a size of a counteracting force is determined according to the stress area and the mutation gradient, and a damping device is determined to be used in the cleaning program to provide the counteracting force.

2. The process control method of a cleaning apparatus based on stress characteristics according to claim 1, characterized by, According to the matching result of the stress features and the preset abnormal stress features, the working parameter of the cleaning program is adjusted, comprising: A target working parameter adjustment strategy is determined according to a matching degree of the stress features and each preset abnormal stress feature, and a pre-constructed correlation between the preset abnormal stress features and the working parameter adjustment strategy; wherein the preset abnormal stress features comprise at least one of over-washing stress features, under-washing stress features, material winding stress features, and foam abnormal stress features; A current working parameter of the cleaning program is acquired, and an adjusted working parameter of the cleaning program is determined according to the current working parameter and the target working parameter adjustment strategy.

3. A program control device for a cleaning apparatus based on stress characteristics, characterized by, The device comprises: The stress data acquisition module is configured to acquire stress data of the cleaning rotating device inside the cleaning device during operation of the cleaning device. The stress feature extraction module is configured to extract stress features based on the stress data, wherein the stress features include a stress peak value sequence and a phase distribution feature. The working condition mode determination module is configured to extract a mel-frequency cepstrum coefficient of the stress data as a first feature vector, extract a kurtosis parameter and a waveform factor of the stress data as a second feature vector, input the first feature vector and the second feature vector into a pre-constructed support vector machine, and obtain a working condition mode of the cleaning rotating device, wherein the working condition mode includes normal operation, vibration anomaly, load imbalance, and mechanical wear, and the vibration anomaly indicates that the cleaning rotating device has vibration exceeding a normal range during operation. The working parameter adjustment module is configured to adjust a working parameter of a cleaning program according to a matching result of the stress features and preset abnormal stress features and the working condition mode, including: In the load imbalance working condition mode, a target preset abnormal stress feature is determined according to the matching result of the stress features and the preset abnormal stress features, a possible range of the mass eccentricity is preliminarily determined according to the target preset abnormal stress feature, the mass eccentricity is adjusted in the possible range according to the current stress features based on a theoretical model of rotor dynamics by using a least square method, so that an error between a theoretically calculated stress feature and the current stress feature is minimized, and thus the mass eccentricity is obtained. A load mass inside the cleaning rotating device is acquired, and a rotating speed in the working parameter of the cleaning program is determined according to the mass eccentricity and the load mass, wherein the preset abnormal stress features include at least one of over-washing stress features, under-washing stress features, material winding stress features, and foam abnormal stress features, and the working parameter includes the rotating speed, a rotating period, a program running time, and a use of auxiliary parts. After the rotating speed in the working parameter of the cleaning program is determined according to the mass eccentricity and the load mass, a kurtosis parameter of the stress data is calculated, a stress area of the cleaning rotating device is acquired when the kurtosis parameter exceeds a preset kurtosis threshold, a mutation gradient of the stress data is calculated, a size of a counteracting force is determined according to the stress area and the mutation gradient, and a damping device is determined to be used to provide the counteracting force in the cleaning program.

4. A cleaning apparatus characterized by, A processor, a memory, and a program or instructions stored on the memory and executable on the processor are included, and the program or instructions are executed by the processor to implement the steps of the program control method of the cleaning device based on stress features according to any one of claims 1-2.

5. A readable storage medium characterized by, A program or instructions are stored on the readable storage medium, and the program or instructions are executed by the processor to implement the steps of the program control method of the cleaning device based on stress features according to any one of claims 1-2.

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