Automatic cleaning method and system for rice wine brewing tank

Abstract

The invention provides an automatic cleaning method and system for a rice wine brewing tank. A wine dirt adhesion area is recognized through a residue distribution image on the inner wall of the rice wine brewing tank; identifying a targeted cleaning path of the rice wine brewing tank according to the geometrical characteristics and the viscosity coefficient of the wine dirt adhesion area, and performing targeted pretreatment on the wine dirt adhesion area according to the targeted cleaning path; determining the resonant frequency offset of the rice wine brewing tank after the targeted pretreatment, and identifying the adhesion state of the wine dirt adhesion object according to the resonant frequency offset; identifying a falling critical point of wine dirt stickers in the rice wine brewing tank by combining the adhesion state with a flushing fluid turbidity change curve monitored by the rice wine brewing tank in real time, and further generating a gradient pressure reduction instruction; and in response to a gradient pressure reduction instruction, activating an annular air curtain generator in a low-pressure turbulence mode to adsorb and clean fine particles on the inner wall of the rice wine brewing tank. According to the technical scheme, precise matching of cleaning power and wine dirt removing requirements can be achieved in the cleaning process of the interior of the rice wine brewing tank.

Description

Technical Field

[0001] This application relates to the field of tank cleaning technology, and more specifically, to an automatic cleaning method and system for rice wine brewing tanks. Background Technology

[0002] As core storage and transportation equipment in industries such as chemical, food, and pharmaceutical, the cleanliness of tanks directly affects product quality and production safety. Traditional cleaning methods mostly rely on manual wiping or high-pressure water jet rinsing, which have problems such as incomplete cleaning, residue in dead corners, and chemical cleaning agent contamination. In particular, the cleaning effect is limited for irregularly shaped tanks or high-viscosity media residues. With the upgrading of industry standards, higher requirements are placed on the automation, residue-free, and low-pollution of tank cleaning. In recent years, technologies such as CIP (clean-in-place) technology, high-pressure water jet cleaning, and ultrasonic cleaning have been gradually promoted. Achieving high efficiency and environmental protection in the cleaning process through intelligent control has become the main development direction of tank cleaning.

[0003] In existing tank cleaning methods, decontamination is mostly achieved through the synergistic effect of mechanical force, chemical action, and heat. Mechanically, high-pressure water jets impact the tank walls to remove attached residues, while rotating spray balls utilize centrifugal force to form a fan-shaped water curtain covering the inner surface of the tank. In some cases, ultrasonic vibration is combined, using liquid cavitation to generate micro-jet streams that penetrate deep into crevices to remove stubborn stains. However, in cleaning rice wine brewing tanks, the dynamic changes in the adhesion strength and residual state of the internal residue lead to a mismatch between cleaning power and the need for residue removal. This can easily result in incomplete cleaning and secondary contamination. Therefore, achieving a precise match between cleaning power and residue removal needs during the cleaning of rice wine brewing tanks has become a challenge for the industry. Summary of the Invention

[0004] This application provides an automatic cleaning method and system for rice wine brewing tanks, which can achieve precise matching between cleaning power and the needs for removing rice wine stains during the internal cleaning process of rice wine brewing tanks.

[0005] In a first aspect, this application provides an automatic cleaning method for rice wine brewing tanks, comprising the following steps: Images of the residue distribution on the inner wall of the rice wine brewing tank are collected, and the areas of wine residue adhesion on the inner wall of the rice wine brewing tank are identified based on the residue distribution images. Based on the geometric characteristics and viscosity coefficient of the wine stain adhesion area, a targeted cleaning analysis is performed on the rice wine brewing tank to obtain the targeted cleaning path of the rice wine brewing tank. Then, based on the targeted cleaning path, the rotary spray mechanism is driven to perform targeted pretreatment on the wine stain adhesion area in high-pressure rinsing mode. The resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment is determined, and the adhesion state of the wine residue on the inner wall of the rice wine brewing tank is identified based on the resonant frequency shift. By combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time in the rice wine brewing tank, the critical point for the detachment of the wine residue in the rice wine brewing tank is identified, and then a gradient pressure reduction command is triggered during the cleaning of the rice wine brewing tank based on the detachment critical point. In response to the gradient pressure reduction command, the flushing pressure of the rotary spray mechanism is switched from high-pressure flushing mode to low-pressure turbulence mode, and in the low-pressure turbulence mode, the annular air curtain generator is activated to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0006] In some embodiments, identifying the areas of wine stain adhesion on the inner wall of the rice wine brewing tank based on the residue distribution image specifically includes: The image of the residue distribution is preprocessed to obtain a preprocessed image; The preprocessed image is binarized based on an adaptive threshold to obtain a binarized image; Morphological operations are performed on the binarized image to extract multiple connected regions; Calculate the geometric feature parameters of each connected region, and mark the connected regions whose geometric feature parameters meet the preset wine stain feature conditions as wine stain adhesion regions.

[0007] In some embodiments, the targeted cleaning analysis of the rice wine brewing tank is performed based on the geometric characteristics and viscosity coefficient of the wine stain adhesion zone, and the targeted cleaning path of the rice wine brewing tank specifically includes: Extract the geometric features and viscosity coefficients of each wine stain adhesion zone, wherein the geometric features include centroid coordinates and circumscribed rectangle dimensions; The cleaning priority weight for the corresponding wine stain adhesion area is determined based on the viscosity coefficient; Based on the centroid coordinates and cleaning priority weights of each wine stain adhesion zone, the cleaning sequence of the rice wine brewing tank is planned to obtain the regional cleaning sequence of the rice wine brewing tank. The outer rectangular dimension of each wine stain adhesion area is used as the coverage area for cleaning the wine stain adhesion area; The targeted cleaning path for the rice wine brewing tank is generated by the regional cleaning sequence and the coverage cleaning range of each wine stain adhesion area.

[0008] In some embodiments, the targeted pretreatment of the wine stain adhesion area by the rotary spray mechanism driven by the targeted cleaning path in high-pressure rinsing mode specifically includes: The targeted cleaning path is parsed into a sequence of motion coordinates of the rotary spray mechanism; The drive control signal for the rotary jet mechanism is generated based on the motion coordinate sequence; In response to the drive control signal, the rotary spray mechanism is driven to move according to the motion coordinate sequence; During the movement of the rotary spray mechanism, high-pressure flushing is initiated to rinse the wine stain adhesion area, thereby completing the targeted pretreatment of the wine stain adhesion area.

[0009] In some embodiments, determining the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment specifically includes: The ultrasonic generator was activated to apply ultrasonic excitation to the rice wine brewing tank after the targeted pretreatment, and the vibration frequency signal of the rice wine brewing tank under the action of ultrasonic waves was collected. The vibration frequency signal is subjected to Fourier transform, and then the actual resonant frequency of the rice wine brewing tank is extracted. The reference resonant frequency of the rice wine brewing tank under no-load conditions was determined. The resonant frequency offset of the rice wine brewing tank under ultrasonic action after targeted pretreatment is determined based on the actual resonant frequency and the reference resonant frequency.

[0010] In some embodiments, identifying the adhesion state of the wine residue adhering to the inner wall of the rice wine brewing tank based on the resonant frequency offset specifically includes: Establish the mapping relationship between the resonant frequency shift and the adhesion strength of wine stains; Based on the mapping relationship, extract the wine stain adhesion strength value corresponding to the resonant frequency offset; The adhesion strength value of the wine stains is compared with the adhesion strength threshold range, and then the adhesion state of the wine stains on the inner wall of the rice wine brewing tank is determined based on the comparison results.

[0011] In some embodiments, identifying the critical point for the detachment of the rice wine residue in the rice wine brewing tank by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time in the rice wine brewing tank specifically includes: The turbidity change curve of the rinsing fluid is calculated by performing the first derivative operation to obtain the turbidity change rate curve; Extract the turbidity change rate curve segment corresponding to the adhesion state satisfying the preset state from the turbidity change rate curve; Identify the maximum turbidity change rate value and the corresponding time point in the turbidity change rate curve segment; The time point corresponding to the maximum turbidity change rate is marked as the critical point for the shedding of wine stains.

[0012] In some embodiments, triggering a gradient depressurization command during cleaning of the rice wine brewing tank based on the detachment critical point specifically includes: Using the aforementioned detachment critical point as the starting point, the time interval and pressure gradient parameters for gradient depressurization are set. Calculate the target pressure value corresponding to each time node in the time interval based on the pressure gradient parameter, and generate a pressure control sequence; The pressure control sequence is converted into a gradient depressurization command.

[0013] In some embodiments, a high-definition industrial camera mounted on a multi-degree-of-freedom robotic arm is used to capture images of the residue distribution on the inner wall of the rice wine brewing tank.

[0014] Secondly, this application provides an automatic cleaning system for rice wine brewing tanks, comprising: The acquisition module is used to acquire images of the residue distribution on the inner wall of the rice wine brewing tank, and to identify the areas of wine stain adhesion on the inner wall of the rice wine brewing tank based on the residue distribution images. The processing module is used to perform targeted cleaning analysis on the rice wine brewing tank based on the geometric characteristics and viscosity coefficient of the wine stain adhesion area, obtain the targeted cleaning path of the rice wine brewing tank, and then drive the rotary spray mechanism to perform targeted pretreatment on the wine stain adhesion area in high-pressure rinsing mode according to the targeted cleaning path. The processing module is also used to determine the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment, and to identify the adhesion state of the wine residue on the inner wall of the rice wine brewing tank based on the resonant frequency shift. The processing module is also used to identify the critical point of detachment of the wine residue in the rice wine brewing tank by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time, and then trigger a gradient pressure reduction command during cleaning of the rice wine brewing tank based on the detachment critical point. The execution module is used to respond to the gradient pressure reduction command, switch the flushing pressure of the rotary spray mechanism from high-pressure flushing mode to low-pressure turbulence mode, and activate the annular air curtain generator in the low-pressure turbulence mode to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The automatic cleaning method and system for rice wine brewing tanks provided in this application first acquires an image of the residue distribution on the inner wall of the rice wine brewing tank, and identifies the areas of wine stain adhesion on the inner wall of the rice wine brewing tank based on the residue distribution image; secondly, it performs targeted cleaning analysis on the rice wine brewing tank according to the geometric characteristics and viscosity coefficient of the wine stain adhesion areas to obtain the targeted cleaning path of the rice wine brewing tank, and then drives a rotary spray mechanism to perform targeted pretreatment on the wine stain adhesion areas in a high-pressure rinsing mode according to the targeted cleaning path; furthermore, it determines the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment, and then... The adhesion state of the wine stains on the inner wall of the rice wine brewing tank is identified based on the resonant frequency offset. Then, the critical point for the detachment of the wine stains in the rice wine brewing tank is identified by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time. Based on the detachment critical point, a gradient pressure reduction command is triggered during the cleaning of the rice wine brewing tank. Finally, in response to the gradient pressure reduction command, the rinsing pressure of the rotary spray mechanism is switched from high-pressure rinsing mode to low-pressure turbulence mode. In the low-pressure turbulence mode, the annular air curtain generator is activated to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0016] Therefore, this application can achieve a precise match between cleaning power and the needs for removing rice wine stains during the cleaning process inside rice wine brewing tanks. First, by acquiring images of residue distribution and identifying stain adhesion areas, the cleaning target can be accurately located, avoiding ineffective cleaning of stain-free areas and reducing water and energy waste. Second, based on the geometric characteristics and viscosity coefficient of the stain adhesion areas, a targeted cleaning path is generated and a rotary spray mechanism is driven for high-pressure pretreatment. This allows the high-pressure water flow to accurately act on areas with dense stains, enhancing the initial loosening effect on the stains, while reducing unnecessary impact of high pressure on stain-free areas of the tank. Furthermore, by determining the resonant frequency offset to identify the adhesion state of the stains, a quantitative assessment of the bonding strength between the stains and the tank is achieved, providing a scientific reference for the dynamic adjustment of subsequent cleaning parameters. This effectively avoids stain residue due to insufficient cleaning intensity or energy waste caused by excessive cleaning intensity. Finally, by combining the adhesion state with the turbidity change curve of the rinsing liquid, the detachment critical point is identified and a gradient descent is triggered. The pressure command enables precise synchronization between the adjustment of cleaning pressure and the critical stage of residue removal. As residue detaches on a large scale, the pressure is gradually reduced, ensuring smooth removal of the detached residue. This achieves a precise match between cleaning power and residue removal requirements, avoiding the mismatch between cleaning power and residue removal needs caused by dynamic changes in the adhesion strength and residual state of internal residue during the cleaning process inside the rice wine brewing tank. This balances cleaning efficiency and equipment protection. Finally, in response to the gradient pressure reduction command, the system switches to a low-pressure turbulence mode and activates the annular air curtain generator. The low-pressure turbulence utilizes the disturbance effect of turbulence to further peel off the remaining loose residue, while the adsorption effect of the bubble clusters effectively removes fine particles from dead corners and tiny crevices in the tank, preventing secondary pollution. Ultimately, this achieves efficient cleaning throughout the entire process, from deep cleaning to fine adsorption, in the rice wine brewing tank. In summary, the technical solution provided in this application can achieve a precise match between cleaning power and residue removal requirements during the cleaning process inside the rice wine brewing tank. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of an application scenario architecture for an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application; Figure 2 This is an exemplary flowchart of an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application; Figure 3 This is an exemplary flowchart illustrating the determination of a targeted cleaning path according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an automatic cleaning system for rice wine brewing tanks according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device for implementing an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application. Detailed Implementation

[0018] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] refer to Figure 1 This figure is a schematic diagram of an application scenario architecture for an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application. The application scenario architecture includes a data acquisition terminal, a communication network, and a server. The data acquisition terminal and the server are directly or indirectly connected through the communication network. The data acquisition terminal acquires images of the residue distribution on the inner wall of the rice wine brewing tank and uploads them to the server. The server identifies areas of wine stain adhesion on the inner wall of the rice wine brewing tank based on the residue distribution images. Based on the geometric characteristics and viscosity coefficient of the wine stain adhesion areas, the server performs targeted cleaning analysis on the rice wine brewing tank to obtain a targeted cleaning path. Then, based on the targeted cleaning path, the server drives a rotary spray mechanism to clean the wine stain adhesion areas in a high-pressure rinsing mode. Targeted pretreatment is performed; the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment is determined, and the adhesion state of the wine residue adhering to the inner wall of the rice wine brewing tank is identified based on the resonant frequency shift; the adhesion state is combined with the turbidity change curve of the rinsing liquid monitored in real time to identify the detachment critical point of the wine residue adhering to the rice wine brewing tank, and then a gradient pressure reduction command is triggered during the cleaning of the rice wine brewing tank based on the detachment critical point; in response to the gradient pressure reduction command, the rinsing pressure of the rotary spray mechanism is switched from high-pressure rinsing mode to low-pressure turbulence mode, and in the low-pressure turbulence mode, the annular air curtain generator is activated to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0020] refer to Figure 2 The figure is an exemplary flowchart of an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application. The automatic cleaning method for rice wine brewing tanks mainly includes the following steps: In step 101, an image of the residue distribution on the inner wall of the rice wine brewing tank is acquired, and the residue adhesion area on the inner wall of the rice wine brewing tank is identified based on the residue distribution image.

[0021] In a specific implementation, a high-definition industrial camera mounted on a multi-degree-of-freedom robotic arm can be used to collect images of the residue distribution on the inner wall of the rice wine brewing tank. When the high-definition industrial camera is collecting images of the residue distribution, it is supplemented by a ring LED mounted on the multi-degree-of-freedom robotic arm. This will not be elaborated here. In addition, in other embodiments, other acquisition devices can be used to collect images of the residue distribution on the inner wall of the rice wine brewing tank. This is not limited here.

[0022] It should be noted that the residue distribution image in this application refers to the spatial distribution image of residual wine stains on the inner wall surface of the rice wine brewing tank. The residue distribution image contains visual information such as the location, shape, area, thickness and degree of aggregation of the residues. By determining the residue distribution image, an intuitive visual basis can be provided for the subsequent identification of the wine stain adhesion area. By analyzing the geometric features and distribution patterns of the residues in the image, the areas that need to be cleaned can be accurately located, avoiding blindness in the cleaning process. At the same time, it provides basic data support for targeted cleaning path planning and cleaning parameter adjustment.

[0023] In some embodiments, identifying the areas of rice wine residue adhesion on the inner wall of the rice wine brewing tank based on the residue distribution image is achieved through the following steps: The image of the residue distribution is preprocessed to obtain a preprocessed image; The preprocessed image is binarized based on an adaptive threshold to obtain a binarized image; Morphological operations are performed on the binarized image to extract multiple connected regions; Calculate the geometric feature parameters of each connected region, and mark the connected regions whose geometric feature parameters meet the preset wine stain feature conditions as wine stain adhesion regions.

[0024] In specific implementation, firstly, the image of the residue distribution is preprocessed to obtain a preprocessed image, that is, Gaussian filtering is used to remove noise from the image of the residue distribution. Secondly, the preprocessed image is binarized based on an adaptive threshold to obtain a binarized image, that is, a 3×3 rectangular window is set, and the preprocessed image is divided into multiple local sub-regions through the rectangular window. The mean and standard deviation of the pixel grayscale corresponding to each local sub-region are calculated, and the mean pixel grayscale minus one standard deviation is used as the local threshold. The relationship between the grayscale value of each pixel and the local threshold of its local sub-region is judged pixel by pixel. If the pixel grayscale value is greater than the local threshold, the pixel corresponding to the pixel grayscale value is marked as foreground (assigned a value of 255). If the pixel grayscale value is less than or equal to the local threshold, the pixel corresponding to the pixel grayscale value is marked as background (assigned a value of 0). A binarized image is then obtained, which is an image with only two pixel values. Then, the erosion operation in morphological operations is used to eliminate small noise and protrusions in the binarized image. Next, the dilation operation is used to fill holes and broken connections in the binarized image, thereby extracting multiple connected regions. A connected region is a region in the image composed of interconnected pixels. Finally, the geometric feature parameters of each connected region are calculated, including area, perimeter, and roundness. Each feature parameter is compared with preset wine stain feature conditions. Connected regions that meet the wine stain feature conditions are marked as wine stain adhesion areas. The wine stain feature conditions are area, perimeter, and roundness feature ranges set by machine learning simulation based on all wine stain feature data in the wine stain database; these will not be elaborated further here.

[0025] It should be noted that, in this application, the area where the wine stains adhere refers to the area on the inner wall of the rice wine brewing tank where wine stains are attached. Identifying the area where the wine stains adhere can accurately pinpoint the areas on the inner wall of the rice wine brewing tank that need to be cleaned, avoiding blind cleaning and waste of resources during the cleaning process, making the cleaning operation more targeted, and ensuring that the cleaning force is concentrated on the area where the wine stains are attached, thereby improving cleaning efficiency and effectiveness and reducing unnecessary wear on the non-adhesive areas of the tank.

[0026] In step 102, the rice wine brewing tank is subjected to targeted cleaning analysis based on the geometric characteristics and viscosity coefficient of the wine stain adhesion area to obtain the targeted cleaning path of the rice wine brewing tank. Then, the rotary spray mechanism is driven to perform targeted pretreatment on the wine stain adhesion area in high-pressure rinsing mode according to the targeted cleaning path.

[0027] In some embodiments, reference Figure 3As shown in the figure, this is an exemplary flowchart of determining a targeted cleaning path according to some embodiments of this application. In this embodiment, the targeted cleaning analysis of the rice wine brewing tank is performed based on the geometric characteristics and viscosity coefficient of the wine stain adhesion area. The targeted cleaning path of the rice wine brewing tank can be obtained by the following steps: First, in step 1021, the geometric features and viscosity coefficients of each wine stain adhesion zone are extracted. The geometric features include the centroid coordinates and the size of the circumscribed rectangle. Secondly, in step 1022, the cleaning priority weight of the corresponding wine stain adhesion area is determined based on the viscosity coefficient; Furthermore, in step 1023, the cleaning sequence is planned based on the centroid coordinates and cleaning priority weights of each wine stain adhesion area to obtain the regional cleaning sequence of the rice wine brewing tank; Then, in step 1024, the outer rectangular dimension of each wine stain adhesion area is used as the coverage cleaning range of the wine stain adhesion area; Finally, in step 1025, a targeted cleaning path for the rice wine brewing tank is generated by the area cleaning sequence and the coverage cleaning range of each wine stain adhesion area.

[0028] In specific implementation, firstly, the centroid coordinates and circumscribed rectangle dimensions of each wine stain adhesion area are read using the image analysis tool OpenCV. The centroid coordinates are the coordinates of the geometric center of the wine stain adhesion area, and the circumscribed rectangle dimensions are the length and width of the smallest rectangle that can completely enclose the wine stain adhesion area. Simultaneously, the average viscosity value of the wine stain adhesion area is measured using a viscometer as the viscosity coefficient, thus obtaining the viscosity coefficient of each wine stain adhesion area. The viscosity coefficient is a physical quantity characterizing the flow resistance of the wine stain adhesion. Secondly, the viscosity coefficient of each wine stain adhesion area is normalized using min-max normalization, and the normalized viscosity coefficient is used as the cleaning priority weight for the corresponding wine stain adhesion area. The cleaning priority weight refers to the value reflecting the degree to which the wine stain adhesion area needs to be cleaned first. Furthermore, when planning the cleaning sequence based on the centroid coordinates and cleaning priority weights of each wine stain adhesion area, a cleaning priority weight is selected. The rice wine brewing tank is first cleaned by selecting the area with the highest priority for stain adhesion and using its centroid coordinates as the starting point. Then, the remaining areas with stain adhesion closest to the current area's centroid coordinates are selected as the next cleaning target, and so on, forming a regional cleaning sequence. This regional cleaning sequence refers to a set of stain adhesion areas arranged in order of cleaning priority. Next, the outer rectangle size of each stain adhesion area is used as the coverage cleaning range of that area, which is the area that needs to be cleaned to remove the stain adhesion. Finally, when generating a targeted cleaning path using the regional cleaning sequence and the coverage cleaning range of each stain adhesion area, the coverage cleaning range of the stain adhesion areas in the regional cleaning sequence is connected by a smooth curve using the connection method in path planning, forming a continuous and non-repeating trajectory, thus obtaining the targeted cleaning path for the rice wine brewing tank.

[0029] It should be noted that the targeted cleaning path in this application refers to the motion trajectory followed by the rotary spray mechanism when performing targeted cleaning operations. The determination of the targeted cleaning path can provide precise motion trajectory guidance for the cleaning equipment of the rice wine brewing tank, ensuring that the cleaning operation is strictly carried out according to the preset route, avoiding repeated work or missed areas during the cleaning process, thereby significantly improving cleaning efficiency. In addition, the precise targeted cleaning path can ensure that the wine stains are thoroughly removed, ensuring that the cleanliness of the tank meets the brewing hygiene standards, and providing a basic condition for the stable quality of subsequent rice wine brewing.

[0030] In some embodiments, the targeted pretreatment of the wine stain adhesion area by the rotary spray mechanism driven by the targeted cleaning path in high-pressure rinsing mode is achieved by the following steps: The targeted cleaning path is parsed into a sequence of motion coordinates of the rotary spray mechanism; The drive control signal for the rotary jet mechanism is generated based on the motion coordinate sequence; In response to the drive control signal, the rotary spray mechanism is driven to move according to the motion coordinate sequence; During the movement of the rotary spray mechanism, high-pressure flushing is initiated to rinse the wine stain adhesion area, thereby completing the targeted pretreatment of the wine stain adhesion area.

[0031] In specific implementation, firstly, when resolving the targeted cleaning path into a motion coordinate sequence of the rotary spraying mechanism, the cleaning path can be discretized into a series of sequentially arranged spatial coordinate points, and the discretized spatial coordinate points are combined into a motion coordinate sequence. Existing path resolution algorithms can be used to discretize the cleaning path; no limitation is made here. The motion coordinate sequence refers to the set of position coordinates of the rotary spraying mechanism arranged in motion sequence. Secondly, when generating the drive control signal for the rotary spraying mechanism based on the motion coordinate sequence, a quadratic interpolation algorithm is used to smooth the motion trajectory between adjacent coordinate points. The displacement and velocity of the rotary spraying mechanism at each spatial position point are calculated using the data processing tool Python. Then, the displacement... The motion speed is converted into an electrical signal, which is an electrical signal used to control the movement of the rotary spraying mechanism. Then, in response to the drive control signal, when the rotary spraying mechanism moves according to the motion coordinate sequence, the drive control signal is received by the servo driver and converted into an operating command for the drive motor, so that the motor drives the mechanical arm of the rotary spraying mechanism to move according to the motion coordinate sequence. The servo driver is an electronic device used to control the operation of the servo motor. Finally, during the movement of the rotary spraying mechanism, the output pressure of the high-pressure water source is adjusted by the pressure control valve, so that the high-pressure water flows through the nozzle of the rotary spraying mechanism and is sprayed onto the wine stain adhesion area, thereby achieving targeted pretreatment of the wine stain adhesion area during the movement.

[0032] It should be noted that in this application, targeted pretreatment refers to the preliminary targeted rinsing process in preparation for subsequent deep cleaning. In this embodiment, the targeted cleaning path is parsed into a motion coordinate sequence and combined with an interpolation algorithm, so that the movement trajectory of the rotary spray mechanism can accurately match the geometric features of the wine stain adhesion area, thereby achieving "targeted rinsing". This solves the problem of local over-rinsing or inadequate cleaning caused by the mismatch between the cleaning path and the actual dirt distribution in the prior art.

[0033] In step 103, the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment is determined, and the adhesion state of the wine residue on the inner wall of the rice wine brewing tank is identified based on the resonant frequency shift.

[0034] In some embodiments, determining the resonant frequency shift of the rice wine brewing tank under ultrasonic waves after targeted pretreatment is achieved by the following steps: The ultrasonic generator was activated to apply ultrasonic excitation to the rice wine brewing tank after the targeted pretreatment, and the vibration frequency signal of the rice wine brewing tank under the action of ultrasonic waves was collected. The vibration frequency signal is subjected to Fourier transform, and then the actual resonant frequency of the rice wine brewing tank is extracted. The reference resonant frequency of the rice wine brewing tank under no-load conditions was determined. The resonant frequency offset of the rice wine brewing tank under ultrasonic action after targeted pretreatment is determined based on the actual resonant frequency and the reference resonant frequency.

[0035] In practice, firstly, when the ultrasonic generator is activated to apply ultrasonic excitation to the pre-treated rice wine brewing tank, the transducer of the ultrasonic generator is placed close to the outer wall of the brewing tank, and ultrasonic vibrations are output at a preset frequency. Simultaneously, a vibration sensor collects the vibration frequency signal of the rice wine brewing tank under ultrasonic action. This vibration frequency signal refers to the electrical signal reflecting the speed of vibration of an object. Secondly, a fast Fourier transform algorithm is used to convert the vibration frequency signal in the time domain into a frequency domain signal, and the frequency value with the largest amplitude is identified from the frequency domain signal as the actual resonant frequency of the rice wine brewing tank. This actual resonant frequency refers to the vibration frequency of the rice wine brewing tank to be cleaned when its amplitude reaches its maximum under forced vibration. Then, the pre-determined resonant frequency when the rice wine brewing tank is free of wine residue and rinsing liquid is read from the storage unit during the rice wine brewing tank cleaning process. This reference resonant frequency refers to the inherent resonant frequency of an object when there is no load. Finally, the resonant frequency offset of the pre-treated rice wine brewing tank under ultrasonic action is determined based on the difference between the actual resonant frequency and the reference resonant frequency.

[0036] It should be noted that the resonant frequency offset in this application refers to the difference between the actual resonant frequency of the object and the reference resonant frequency. The determination of the resonant frequency offset can accurately reflect the residual state and bonding strength of the wine stains adhering to the inner wall of the rice wine brewing tank after targeted pretreatment. Its numerical change can serve as a physical quantity basis for judging whether the wine stains have been effectively loosened. At the same time, this offset provides key parameter support for subsequent identification of the adhesion state of the wine stains. By comparing with the reference resonant frequency, the change in the bonding state between the wine stains and the tank under the action of ultrasound can be intuitively reflected, providing a quantitative reference for the adjustment of subsequent cleaning strategies (such as the optimization of parameters such as pressure and time), ensuring that the cleaning process is more targeted and effective, and thus ensuring that the final cleaning effect meets the hygiene requirements of rice wine brewing.

[0037] In some embodiments, the identification of the adhesion state of the wine residue adhering to the inner wall of the rice wine brewing tank based on the resonant frequency offset is achieved by the following steps: Establish the mapping relationship between the resonant frequency shift and the adhesion strength of wine stains; Based on the mapping relationship, extract the wine stain adhesion strength value corresponding to the resonant frequency offset; The adhesion strength value of the wine stains is compared with the adhesion strength threshold range, and then the adhesion state of the wine stains on the inner wall of the rice wine brewing tank is determined based on the comparison results.

[0038] In specific implementation, firstly, when establishing the mapping relationship between the resonant frequency offset and the adhesion strength of the wine stain, resonant frequency offset data under different wine stain adhesion strengths are obtained through controlled experiments. A polynomial fitting algorithm is then used to fit the resonant frequency offset data under different wine stain adhesion strengths with the resonant frequency offset as the independent variable and the wine stain adhesion strength as the dependent variable, obtaining the mapping relationship between the resonant frequency offset and the wine stain adhesion strength. This mapping relationship refers to the quantitative correspondence between the resonant frequency offset and the wine stain adhesion strength. Secondly, when extracting the wine stain adhesion strength value corresponding to the resonant frequency offset based on this mapping relationship, the actually measured resonant frequency offset is used... Substituting the frequency offset into the mapping relationship, the corresponding wine stain adhesion strength value is calculated from the mapping. The wine stain adhesion strength value refers to a physical quantity characterizing the degree of adhesion between the wine stain and the inner wall of the rice wine brewing tank. Finally, when comparing the wine stain adhesion strength value with the adhesion strength threshold range to determine the adhesion state, the adhesion strength threshold range is determined through a large amount of experimental data statistics, which will not be elaborated here. The adhesion strength threshold range includes the intensity intervals corresponding to strong adhesion, medium adhesion, and weak adhesion. The calculated wine stain adhesion strength value is matched with different mild intervals in the adhesion strength threshold range to determine the adhesion state of the wine stain.

[0039] It should be noted that, in this application, "adhesion state" refers to the degree of firmness of the adhesion between the wine stains and the inner wall of the rice wine brewing tank. Determining the adhesion state allows for precise control over the strength of the adhesion between the wine stains and the tank, providing a direct basis for formulating subsequent cleaning strategies. For wine stains with strong adhesion, the cleaning intensity can be increased or the action time extended, while for wine stains with weak adhesion, the cleaning parameters can be appropriately reduced to avoid wasting resources. At the same time, the result can reflect the changes in the degree of adhesion of the wine stains in real time during the cleaning process, facilitating dynamic adjustment of the cleaning plan and providing quantitative guidance for the standardized cleaning of rice wine brewing tanks.

[0040] In step 104, the critical point for the detachment of the wine residue in the rice wine brewing tank is identified by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time. Then, a gradient pressure reduction command is triggered during the cleaning of the rice wine brewing tank based on the detachment critical point.

[0041] In some embodiments, the critical point for the detachment of the rice wine residue adhering to the rice wine brewing tank is identified by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time in the rice wine brewing tank, using the following steps: The turbidity change curve of the rinsing fluid is calculated by performing the first derivative operation to obtain the turbidity change rate curve; Extract the turbidity change rate curve segment corresponding to the adhesion state satisfying the preset state from the turbidity change rate curve; Identify the maximum turbidity change rate value and the corresponding time point in the turbidity change rate curve segment; The time point corresponding to the maximum turbidity change rate is marked as the critical point for the shedding of wine stains.

[0042] In specific implementation, firstly, when performing first-order derivative calculations on the turbidity change curve of the flushing fluid to obtain the turbidity change rate curve, a numerical differential algorithm is used to calculate the ratio of the turbidity difference to the time difference between two adjacent points on the turbidity change curve, thus obtaining the turbidity change rate corresponding to each time point, thereby forming a continuous turbidity change rate curve. This turbidity change rate curve reflects the rate of change of turbidity in the flushing fluid over time. Secondly, when extracting the turbidity change rate curve segment corresponding to the adhesion state meeting a preset state from the turbidity change rate curve, the preset state is set as the stage of transition from strong adhesion to medium adhesion. The turbidity change rate curve segment corresponding to the adhesion state meeting the preset state is extracted by time axis matching. The turbidity change rate curve segment refers to a local curve in the turbidity change rate curve that corresponds to the preset adhesion state stage. Then, an extreme value search algorithm is used to traverse all data points on the turbidity change rate curve segment to find the value with the largest turbidity change rate and its corresponding time point on the time axis. The maximum turbidity change rate value refers to the turbidity change rate with the largest value in the turbidity change rate curve segment, and the corresponding time point refers to the specific time when the maximum turbidity change rate value appears. Finally, the time point corresponding to the maximum turbidity change rate value is marked as the critical point for the detachment of wine stains. The time point with the largest turbidity change rate is usually the time point when the wine stains detach the fastest, and this time point is determined as the starting time of large-scale detachment of wine stains.

[0043] It should be noted that the detachment critical point in this application refers to the time point at which the wine sludge begins to detach from the inner wall of the rice wine brewing tank on a large scale. Determining the detachment critical point can accurately capture the key time point at which the wine sludge begins to detach from the inner wall of the rice wine brewing tank on a large scale, providing a core basis for the dynamic control of the cleaning process. Using this as a boundary, the cleaning mode can be switched in a timely manner (such as from high-pressure rinsing to low-pressure turbulence), avoiding premature switching that leads to incomplete cleaning or switching too late that causes energy waste and tank wear. At the same time, this critical point marks the beginning of the stage with the highest efficiency of wine sludge detachment. Optimizing subsequent cleaning parameters (such as pressure, duration, etc.) based on this can significantly improve cleaning efficiency and ensure that the wine sludge is efficiently removed in the shortest possible time, providing a key time benchmark for the standardized cleaning process of rice wine brewing tanks.

[0044] In some embodiments, the gradient pressure reduction command triggered during the cleaning of the rice wine brewing tank based on the detachment critical point is implemented using the following steps: Using the aforementioned detachment critical point as the starting point, the time interval and pressure gradient parameters for gradient depressurization are set. Calculate the target pressure value corresponding to each time node in the time interval based on the pressure gradient parameter, and generate a pressure control sequence; The pressure control sequence is converted into a gradient depressurization command.

[0045] In specific implementation, firstly, when setting the time interval and pressure gradient parameters for gradient pressure reduction with the detachment critical point as the starting point, the time interval is the duration from the detachment critical point to the preset end point of the cleaning process. The pressure gradient parameter is the reduction rate of rinsing pressure per unit time, specifically set according to the characteristics of wine stain detachment, for example, it can be set to 1-3 MPa, without limitation here. The pressure gradient parameter refers to the parameter characterizing the rate of decrease of rinsing pressure over time. Then, when calculating the target pressure value corresponding to each time node in the time interval to generate a pressure control sequence based on the pressure gradient parameter, the time interval is divided into multiple equal time nodes using a time discretization method, and the target pressure value is calculated based on the detachment critical point. Using the initial pressure at the critical point as a reference, the pressure value of each node is calculated sequentially according to the pressure gradient parameters. These pressure values ​​and their corresponding time nodes are arranged in order to form a pressure control sequence. The pressure control sequence is an ordered dataset consisting of time nodes and their corresponding target pressure values. A lower limit is set for the pressure values. When the lower limit is reached, the subsequent pressures all use the lower limit as the target pressure value. Finally, when converting the pressure control sequence into a gradient pressure reduction command, the digital pressure control sequence is converted into an analog voltage signal by the DA conversion unit of the embedded controller, thereby obtaining the gradient pressure reduction command. The amplitude change of the gradient pressure reduction command is linearly related to the change of the target pressure value.

[0046] It should be noted that the gradient pressure reduction command in this application refers to the electrical signal used to drive the pressure regulating device to change the flushing pressure according to a preset rule. By determining the gradient pressure reduction command, the cleaning pressure can be reduced in an orderly manner according to a preset gradient when the wine stains reach the critical point of detachment. This avoids incomplete detachment or residue of wine stains due to a sudden drop in pressure, while also preventing damage to the tank caused by excessive flushing due to continuous high pressure. It also achieves a balance between high efficiency and energy saving in the cleaning process, providing a reliable pressure control basis for the safe and economical cleaning of rice wine brewing tanks.

[0047] In step 105, in response to the gradient pressure reduction command, the flushing pressure of the rotary spray mechanism is switched from high-pressure flushing mode to low-pressure turbulence mode, and in the low-pressure turbulence mode, the annular air curtain generator is activated to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0048] In some embodiments, switching the flushing pressure of the rotary jet mechanism from a high-pressure flushing mode to a low-pressure turbulence mode in response to the gradient pressure reduction command is achieved by the following steps: Receive the gradient depressurization command and parse the pressure switching parameters, which include the target low pressure value and the switching time threshold; The opening of the hydraulic control valve of the rotary spraying mechanism is adjusted according to the target low pressure value, and the actual output pressure of the rotary spraying mechanism is monitored in real time within the switching time threshold. When the actual output pressure reaches the target low pressure value, the flushing fluid is made into a turbulent state by the turbulence generator, thus completing the switch to the low-pressure turbulence mode.

[0049] In specific implementation, firstly, when receiving the gradient pressure reduction command and parsing the pressure switching parameters, the PLC controller's command decoding module reads the target low-pressure value and switching time threshold contained in the gradient pressure reduction command. The target low-pressure value refers to the stable output pressure that the swirl jet mechanism needs to achieve in low-pressure turbulence mode, and the switching time threshold refers to the maximum allowable time to complete the switch from high pressure to low pressure. Secondly, when adjusting the opening of the hydraulic control valve of the swirl jet mechanism according to the target low-pressure value and monitoring the actual output pressure in real time within the switching time threshold, PID control is used to compare the target low-pressure value with the actual output pressure fed back by the pressure sensor in real time. After calculating the deviation, the PID control is applied through proportional gain control. The integral and derivative adjustment output control signal is used to drive the stepper motor of the hydraulic control valve to change the opening degree of the hydraulic control valve according to the control signal. The actual output pressure of the rotary spray mechanism is monitored in real time within the switching time threshold. The hydraulic control valve is a device that controls the output pressure by adjusting the flow rate of the hydraulic system by changing the valve opening. Finally, when the actual output pressure reaches the target low pressure value, the impeller rotation mechanism of the turbulence generator is triggered. The high-speed rotation mechanism of the impeller applies shear force to the flushing fluid to make the flushing fluid form a turbulent state, thus completing the switching of the low-pressure turbulence mode. The turbulent state refers to the flow state in which the trajectories of particles in the fluid are disordered and mixed.

[0050] It should be noted that the low-pressure turbulence mode in this application refers to a cleaning mode in which the rotary spray mechanism outputs at a target low pressure value and the rinsing fluid is in a turbulent state. The determination of the low-pressure turbulence mode can form a turbulent rinsing fluid at a lower pressure when the wine stains enter the stage of large-scale shedding. With the help of the irregular vortex motion and shear force of the turbulence, the loose wine stains remaining on the inner wall of the tank can be efficiently peeled off and carried away, avoiding excessive wear on the tank body caused by continuous high-pressure rinsing. At the same time, this mode and the high-pressure rinsing mode form a stepped combination, which significantly reduces energy consumption while ensuring the cleaning effect. Moreover, the disturbance effect of turbulence can reduce the residue of wine stains in the dead corners of the tank, further improving the uniformity and thoroughness of cleaning, and providing a reliable guarantee for the subsequent hygiene standards of rice wine brewing tanks to be met.

[0051] In some embodiments, the activation of the annular air curtain generator to emit a cluster of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank under the low-pressure turbulence mode is achieved through the following steps: The startup parameters of the annular air curtain generator are obtained under the low-pressure turbulence mode, including the bubble diameter range and the air flow rate. The annular gas curtain generator is activated according to the start-up parameters, and the annular gas curtain generator releases a group of bubbles that conform to the bubble diameter range along the inner wall of the rice wine brewing tank; The fine particles on the inner wall of the rice wine brewing tank are adsorbed by the surface tension of the bubble cluster, thus completing the adsorption and cleaning of the fine particles on the inner wall of the rice wine brewing tank.

[0052] In specific implementation, when obtaining the start-up parameters of the annular air curtain generator in low-pressure turbulence mode, the rice wine brewing tank cleaning system calls a pre-stored parameter library to extract the bubble diameter range and gas flow rate that match the characteristics of the current fine particles of rice wine residue, based on previous cleaning experiment data. This yields the start-up parameters of the annular air curtain generator. The bubble diameter range refers to the size interval of bubbles in the bubble group, and the gas flow rate refers to the volume of gas output by the annular air curtain generator per unit time. Next, the annular air curtain generator is activated according to the start-up parameters, and it releases gas along the inner wall of the rice wine brewing tank that conforms to the bubble diameter range. When generating a bubble cluster, the gas flow rate entering the annular gas curtain generator is adjusted by a gas flow control valve. Simultaneously, the microporous structure of the annular gas curtain generator is used to control the bubble diameter to conform to the bubble diameter range, so that the bubble cluster is evenly released along the circumference of the inner wall of the rice wine brewing tank and forms an annular gas curtain. The annular gas curtain generator is a device that can release annularly distributed bubble cluster along the circumference of the tank. Finally, the surface tension of the bubble cluster adsorbs the fine particulate matter on the inner wall of the rice wine brewing tank to complete the adsorption and cleaning. The surface tension refers to the tension generated on the surface of the liquid due to the uneven molecular attraction, which acts on any boundary line along the surface.

[0053] It should be noted that the adsorption cleaning of fine particles in this application refers to the process of adhering to and removing tiny wine stain particles remaining on the inner wall of the tank through air bubbles. Adsorption cleaning utilizes the surface tension of the air bubble cluster to precisely capture and adhere to the fine particles remaining on the inner wall of the rice wine brewing tank. It can effectively remove tiny wine stain particles that are difficult to remove under high-pressure rinsing and low-pressure turbulence modes, especially residual impurities in dead corners and gaps of the tank. At the same time, the adsorbed particles flowing with the air bubbles or rinsing liquid can be completely carried out of the tank, avoiding the problem of incomplete cleaning caused by secondary deposition of fine particles. This further improves the comprehensiveness and cleanliness of the tank cleaning, providing a more hygienic environment for subsequent rice wine brewing and reducing the potential contamination of the wine or its flavor caused by residual impurities.

[0054] In another aspect, in some embodiments, this application provides an automatic cleaning system for rice wine brewing tanks, see reference. Figure 4 The figure is a schematic diagram of an automatic cleaning system for rice wine brewing tanks according to some embodiments of this application. The automatic cleaning system for rice wine brewing tanks includes: a data acquisition module 201, a processing module 202, and an execution module 203, which are described below: The acquisition module 201 in this application is mainly used to acquire images of the residue distribution on the inner wall of the rice wine brewing tank, and to identify the wine stain adhesion area on the inner wall of the rice wine brewing tank based on the residue distribution images. Processing module 202, in this application, is mainly used to perform targeted cleaning analysis on the rice wine brewing tank based on the geometric characteristics and viscosity coefficient of the wine stain adhesion area, obtain the targeted cleaning path of the rice wine brewing tank, and then drive the rotary spray mechanism to perform targeted pretreatment on the wine stain adhesion area in high-pressure rinsing mode according to the targeted cleaning path. The processing module 202 is also used to determine the resonant frequency shift of the rice wine brewing tank under ultrasonic action after targeted pretreatment, and to identify the adhesion state of the wine residue on the inner wall of the rice wine brewing tank based on the resonant frequency shift. In addition, the processing module 202 is also used to identify the critical point of detachment of the wine residue in the rice wine brewing tank by combining the adhesion state with the turbidity change curve of the rinsing liquid monitored in real time, and then trigger a gradient pressure reduction command during cleaning of the rice wine brewing tank based on the detachment critical point. The execution module 203 in this application is mainly used to respond to the gradient pressure reduction command, switch the flushing pressure of the rotary spray mechanism from high pressure flushing mode to low pressure turbulence mode, and activate the annular air curtain generator in the low pressure turbulence mode to emit a group of bubbles to adsorb and clean the fine particulate matter on the inner wall of the rice wine brewing tank.

[0055] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to acquire the code and execute the above-described automatic cleaning method for rice wine brewing tanks.

[0056] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device for implementing an automatic cleaning method for rice wine brewing tanks according to some embodiments of this application. The automatic cleaning method for rice wine brewing tanks in the above embodiments can be achieved through... Figure 5 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0057] The processor 301 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the automatic cleaning method for rice wine brewing tanks in this application.

[0058] The communication bus 302 can be used to transmit information between the aforementioned components.

[0059] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0060] The memory 303 stores program code for executing the solution of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the determination of the automatic cleaning method for rice wine brewing tanks can be achieved by the processor 301 and one or more software modules in the program code in the memory 303.

[0061] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0062] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0063] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0064] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described automatic cleaning method for rice wine brewing tanks.

[0065] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0066] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for automatically cleaning a sake brewing tank, characterized by, The method comprises the following steps: Collecting a residue distribution image of the inner wall of the rice wine brewing tank, and identifying a wine scale adhesion area of the inner wall of the rice wine brewing tank based on the residue distribution image; Performing targeted cleaning analysis on the rice wine brewing tank according to the geometric features and viscosity coefficients of the wine scale adhesion area, obtaining a targeted cleaning path of the rice wine brewing tank, and then driving a rotary spraying mechanism to perform targeted pretreatment on the wine scale adhesion area in a high-pressure flushing mode according to the targeted cleaning path; Determining a resonance frequency offset of the rice wine brewing tank under the action of ultrasonic waves after the targeted pretreatment, and identifying the adhesion state of the wine scale adhesion on the inner wall of the rice wine brewing tank according to the resonance frequency offset; Identifying a critical point of wine scale adhesion falling in the rice wine brewing tank by combining the adhesion state with a real-time monitored change curve of the turbidity of a flushing liquid of the rice wine brewing tank, and then triggering a gradient pressure reduction instruction for cleaning the rice wine brewing tank based on the critical point of wine scale adhesion falling; In response to the gradient pressure reduction instruction, the flushing pressure of the rotary spraying mechanism is switched from the high-pressure flushing mode to the low-pressure turbulent flow mode, and a ring-shaped air curtain generator is activated to emit a bubble group to perform adsorption cleaning of fine particulate matter on the inner wall of the rice wine brewing tank in the low-pressure turbulent flow mode.

2. The method of claim 1, wherein, The method for identifying the wine scale adhesion area of the inner wall of the rice wine brewing tank based on the residue distribution image comprises the following steps: Preprocessing the residue distribution image to obtain a preprocessed image; Performing binaryzation segmentation on the preprocessed image based on an adaptive threshold to obtain a binaryzation image; Performing morphological operation on the binaryzation image, and then extracting a plurality of connected regions; Calculating geometric feature parameters of each connected region, and marking a connected region whose geometric feature parameters meet a preset wine scale feature condition as a wine scale adhesion area.

3. The method of claim 1, wherein, The method for performing targeted cleaning analysis on the rice wine brewing tank according to the geometric features and viscosity coefficients of the wine scale adhesion area comprises the following steps: Extracting geometric features and viscosity coefficients of each wine scale adhesion area, wherein the geometric features include a centroid coordinate and an inscribed rectangle size; Determining a cleaning priority weight of a corresponding wine scale adhesion area according to the viscosity coefficient; Planning a cleaning sequence based on the centroid coordinate and the cleaning priority weight of each wine scale adhesion area to obtain a regional cleaning sequence of the rice wine brewing tank; Taking the inscribed rectangle size of each wine scale adhesion area as a coverage cleaning range of the wine scale adhesion area; Generating a targeted cleaning path of the rice wine brewing tank through the regional cleaning sequence and the coverage cleaning range of each wine scale adhesion area.

4. The method of claim 1, wherein, The method for driving the rotary spraying mechanism to perform targeted pretreatment on the wine scale adhesion area in the high-pressure flushing mode according to the targeted cleaning path comprises the following steps: Analyzing the targeted cleaning path into a motion coordinate sequence of the rotary spraying mechanism; Generating a driving control signal of the rotary spraying mechanism according to the motion coordinate sequence; In response to the driving control signal, driving the rotary spraying mechanism to move according to the motion coordinate sequence; During the movement of the rotary spraying mechanism, starting high-pressure flushing to flush the wine scale adhesion area, and then completing the targeted pretreatment of the wine scale adhesion area.

5. The method of claim 1, wherein, The method for determining a resonance frequency offset of the rice wine brewing tank under the action of ultrasonic waves after the targeted pretreatment comprises the following steps: The ultrasonic generator is started to apply ultrasonic excitation to the rice wine brewing tank after targeted pretreatment, and vibration frequency signals of the rice wine brewing tank under the action of ultrasonic waves are collected. The vibration frequency signals are subjected to Fourier transform, and then the actual resonance frequency of the rice wine brewing tank is extracted. The reference resonance frequency of the rice wine brewing tank when it is unloaded is retrieved. The resonance frequency offset of the rice wine brewing tank after targeted pretreatment under the action of ultrasonic waves is determined according to the actual resonance frequency and the reference resonance frequency.

6. The method of claim 1, wherein, The adhesion state of the wine scale adhesion on the inner wall of the rice wine brewing tank is identified according to the resonance frequency offset, specifically including: A mapping relationship between the resonance frequency offset and the wine scale adhesion strength is established. The wine scale adhesion strength value corresponding to the resonance frequency offset is extracted based on the mapping relationship. The wine scale adhesion strength value is compared with the adhesion strength threshold range, and then the adhesion state of the wine scale adhesion on the inner wall of the rice wine brewing tank is determined according to the comparison result.

7. The method of claim 1, wherein, The shedding critical point of the wine scale adhesion in the rice wine brewing tank is identified through the adhesion state combined with the real-time monitoring of the rinse liquid turbidity change curve of the rice wine brewing tank, specifically including: The first derivative operation is performed on the rinse liquid turbidity change curve to obtain a turbidity change rate curve. The turbidity change rate curve segment corresponding to the adhesion state meeting the preset state is extracted from the turbidity change rate curve. The maximum turbidity change rate value and the corresponding time point in the turbidity change rate curve segment are identified. The time point corresponding to the maximum turbidity change rate value is marked as the shedding critical point of the wine scale adhesion.

8. The method of claim 1, wherein, The gradient pressure reduction instruction for cleaning the rice wine brewing tank is triggered based on the shedding critical point, specifically including: The time interval of gradient pressure reduction and the pressure gradient parameter are set with the shedding critical point as the time starting point. The target pressure value corresponding to each time node in the time interval is calculated according to the pressure gradient parameter to generate a pressure control sequence. The pressure control sequence is converted into a gradient pressure reduction instruction.

9. The method of claim 1, wherein, A high-definition industrial camera is carried by a multi-degree-of-freedom mechanical arm to collect a residual distribution image of the inner wall of the rice wine brewing tank.

10. An automatic cleaning system for rice wine brewing tanks, characterized in that, It includes: A collection module is used to collect a residual distribution image of the inner wall of the rice wine brewing tank, and identify a wine scale adhesion area on the inner wall of the rice wine brewing tank based on the residual distribution image; A processing module is used to perform targeted cleaning analysis on the rice wine brewing tank according to the geometric characteristics and viscosity coefficient of the wine scale adhesion area, obtain a targeted cleaning path of the rice wine brewing tank, and then drive a rotary spraying mechanism to perform targeted pretreatment on the wine scale adhesion area in a high-pressure flushing mode according to the targeted cleaning path; The processing module is also used to determine the resonance frequency offset of the rice wine brewing tank after targeted pretreatment under the action of ultrasonic waves, and identify the adhesion state of the wine scale adhesion on the inner wall of the rice wine brewing tank according to the resonance frequency offset; The processing module is also used to identify the shedding critical point of the wine scale adhesion in the rice wine brewing tank through the adhesion state combined with the real-time monitoring of the rinse liquid turbidity change curve of the rice wine brewing tank, and then trigger the gradient pressure reduction instruction for cleaning the rice wine brewing tank based on the shedding critical point. The execution module is configured to switch the flushing pressure of the rotary jet mechanism from a high-pressure flushing mode to a low-pressure turbulent flow mode in response to the gradient pressure reduction instruction, and activate a ring-shaped air curtain generator to emit bubble groups to adsorb and clean fine particles on the inner wall of the rice wine brewing tank in the low-pressure turbulent flow mode.

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