Kitchen waste treatment device and method

Abstract

The present invention provides a kitchen waste treatment device and method, characterized in that the device includes a housing, a heating device, a sensor, and a processor, and the method can be executed by the processor: obtaining temperature data of a treatment inner drum and garbage weight data through the sensor; determining the heating time and heating power of the treatment inner drum based on the temperature data and the garbage weight data; generating a stop heating instruction and sending it to the heating device in response to the heating time and the heating power meeting preset conditions; and / or generating a separation instruction and sending it to the separation device.

Description

Technical Field

[0001] The present invention relates to the field of waste treatment, and in particular to a device and method for treating kitchen waste. Background Art

[0002] Kitchen waste is the largest type of waste generated in people's daily lives. The composition of kitchen waste is complex, including not only food residues, but also mixtures such as plastics and additives. Kitchen waste with different hardness and fiber content can easily cause kitchen waste treatment devices to jam and stop and produce odor.

[0003] In order to solve the problem that different hardness and fiber content can easily cause the kitchen waste treatment device to get stuck and stop, CN113083486B proposes a control method for a kitchen waste disposer, which sets a program mode selection module to select the corresponding execution mode instruction according to the type of kitchen waste input to execute the corresponding crushing action, thereby avoiding damage to the tool and the kitchen waste disposer getting stuck or malfunctioning. However, this method requires the user to perform the most appropriate treatment according to the type of kitchen waste input (for example, if it is determined that there are bones in the garbage, the bone crushing mode is manually selected), that is, it is necessary to manually adjust the instructions frequently, and the degree of intelligence is low. In addition, this method cannot realize the automatic cleaning of the kitchen waste disposer, and the residual particles or grease of the kitchen waste will affect the working efficiency and treatment effect of the device.

[0004] Therefore, there is an urgent need to propose a kitchen waste treatment device and method to achieve automated and intelligent treatment of kitchen waste, efficiently separate residues and liquids, and facilitate the treatment and recycling of kitchen waste. Summary of the invention

[0005] The invention content includes a kitchen waste treatment device, which includes a box body, a heating device, a sensor, and a processor; the box body includes a feed port, a discharge port and a separation device; the feed port and the discharge port are both connected to the separation device; the separation device includes a treatment inner cylinder, a collection outer cylinder, a collection box, a filter screen, a suction component and a matching pipeline; the treatment inner cylinder is configured to separate and treat the kitchen waste; the collection outer cylinder is arranged around the outside of the treatment inner cylinder, and the collection outer cylinder is configured to collect a first liquid flowing out of the treatment inner cylinder; one end of the suction component is connected to the collection outer cylinder, and the other end is connected to the collection box, and the suction component is configured to collect a second liquid in the collection outer cylinder The waste is sucked into a collection box; a filter is arranged in the suction component, and the filter is configured to filter and absorb grease in the liquid; a heating device is connected to the processing inner cylinder to heat the processing inner cylinder; the processor is configured to: obtain temperature data and garbage weight data of the processing inner cylinder through a sensor; based on the temperature data and the garbage weight data, determine the heating time and heating power of the processing inner cylinder; in response to the heating time and the heating power meeting the preset conditions, generate a stop heating instruction and send it to the heating device; and / or generate a separation instruction and send it to the separation device; wherein the separation instruction is used to control the suction component to separate the first liquid at a preset suction power.

[0006] The invention content includes a method for treating kitchen waste, which is executed based on a kitchen waste treatment device, including: obtaining temperature data and garbage weight data of a treatment inner drum; determining the heating time and heating power of the treatment inner drum based on the temperature data and the garbage weight data; in response to the heating time and the heating power meeting preset conditions, generating a stop heating instruction and sending it to the heating device; and / or generating a separation instruction and sending it to the separation device; wherein the separation instruction is used to control the suction component to separate the first liquid at a preset suction power.

[0007] The invention includes a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes a method for processing kitchen waste.

[0008] The beneficial effects brought by the above invention include but are not limited to: (1) It helps to crush and separate kitchen waste, improve the processing efficiency of kitchen waste, and realize resource recovery; through automatic cleaning and automatic gas discharge during the processing, it avoids the residual grease and other foreign matter affecting the working efficiency of the device during the treatment of garbage, and can also discharge harmful gases and odorous gases in time to avoid interfering with people's normal life. The entire processing process is highly intelligent, and the device can automatically and adaptively adjust the kitchen waste according to different application scenarios to efficiently process kitchen waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0010] Figure 1 is a schematic diagram of a kitchen waste treatment device according to some embodiments of the present specification;

[0011] Figure 2 is an exemplary flow chart of a method for treating kitchen waste according to some embodiments of this specification;

[0012] Figure 3 is an exemplary schematic diagram of generating exhaust instructions according to some embodiments of the present specification;

[0013] Figure 4 It is an exemplary schematic diagram of determining the power adjustment amount according to some embodiments of this specification. DETAILED DESCRIPTION

[0014] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0017] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0018] Figure 1 It is a schematic diagram of a kitchen waste treatment device according to some embodiments of the present specification.

[0019] In some embodiments, Figure 1 As shown, the food waste treatment device 100 may include a housing 110 , a heating device 120 , a sensor 130 and a processor 140 .

[0020] In some embodiments, the food waste treatment device 100 can be used in a variety of application scenarios for food waste treatment. For example, the food waste treatment device 100 can be applied to large kitchens (e.g., restaurants, pre-prepared food processing plants, etc.). For another example, the food waste treatment device 100 can also be applied to home kitchen scenarios. The processor of the food waste treatment device 100 can control the other components in the food waste treatment device 100 to achieve food waste treatment by implementing the methods and / or processes disclosed in this application.

[0021] In some embodiments, the box body 110 may include a feed port 111 , a discharge port 112 , and a separation device 113 . The feed port 111 and the discharge port 112 are both connected to the separation device 113 .

[0022] The feed port 111 is an inlet for inputting kitchen waste. The discharge port 112 is an outlet for outputting processed materials (e.g., residues, wastewater, etc.). There may be one or more feed ports 111 and discharge ports 112. In some embodiments, the discharge port 112 may also be connected to a sewer, or may be connected to a storage device (e.g., a storage bag, etc.) for collecting the discharged materials.

[0023] The separation device 113 is a device for processing kitchen waste. For example, the separation device 113 can process kitchen waste by solid-liquid separation, water-oil separation, etc. The separation device 113 may include a processing inner cylinder 113-1, a collection outer cylinder 113-2, a collection box 113-3, a filter screen 113-4, a suction component 113-5, and a supporting pipeline ( Figure 1 not shown).

[0024] The processing inner cylinder 113-1 is a component for processing kitchen waste. In some embodiments, the processing inner cylinder 113-1 can be configured to separate and process the kitchen waste. For example, the processing inner cylinder 113-1 can separate solid waste from liquid waste in the kitchen waste, and convert solid waste (e.g., solid grease, etc.) that can be converted into liquid by heating into liquid, so as to facilitate solid-liquid separation. In some embodiments, a plurality of small holes can be provided on the cylinder wall of the processing inner cylinder 113-1, and the small holes are used to discharge the liquid in the processing inner cylinder 113-1.

[0025] The collecting outer cylinder 113-2 may be configured to collect the first liquid flowing out of the processing inner cylinder 113-1. In some embodiments, the collecting outer cylinder 113-2 may be arranged around the outside of the processing inner cylinder 113-1. For example, the collecting outer cylinder 113-2 may be arranged outside the processing inner cylinder 113-1. The first liquid refers to the liquid part obtained after solid-liquid separation. For example, the first liquid may include components such as oil and water.

[0026] The suction component 113-5 is a component for sucking liquid. In some embodiments, the suction component 113-5 can be connected to the collection outer cylinder 113-2 at one end and connected to the collection box 113-3 at one end. The suction component 113-5 can include components such as a suction conduit and an aspirator.

[0027] In some embodiments, the suction component 113-5 can be configured to suck the second liquid into the collection box 113-3. The second liquid refers to a part of the liquid sucked from the first liquid. For example, when the first liquid includes water and oil, the second liquid can include water. For another example, when the first liquid includes water and oil, the second liquid can include oil-water.

[0028] The filter 113-4 is a component for filtering grease. In some embodiments, during the suction process of the suction component 113-5, the filter 113-4 can absorb the grease in the first liquid. In some embodiments, during the suction process of the suction component 113-5, the filter 113-4 can filter small solid particles in the first liquid. The filter 113-4 can be arranged in the suction component 113-5. The suction component 113-5 sucks the first liquid, and when the first liquid passes through the filter 113-4, the grease therein will be adsorbed by the filter 113-4; and / or, the small solid particles therein (for example, small solid particles with a size smaller than the small holes in the wall of the treatment inner cylinder 113-1 and flowing out of the small holes with the first liquid) will be filtered out by the filter 113-4. The liquid part passing through the filter 113-4 is mainly water.

[0029] In some embodiments, the filter screen 113-4 may have a certain thickness. For example, the filter screen 113-4 may be a multi-layer mesh structure. By increasing the number of layers of the mesh structure, the thickness of the filter screen 113-4 may be increased. By increasing the thickness of the filter screen 113-4, the filtering efficiency of the filter screen 113-4 for grease and / or small solid particles may be improved.

[0030] In some embodiments, the heating device 120 can be connected to the inner cylinder 113-1 to heat the inner cylinder 113-1. For example, when the kitchen waste is put into the inner cylinder 113-1, the heating device 120 can start heating to melt the solid fat in the kitchen waste into liquid oil for solid-liquid separation.

[0031] Sensor 130 can be used to collect various types of data. In some embodiments, sensor 130 may include a gravity sensor and a temperature sensor. There may be multiple sensors 130. In some embodiments, a gravity sensor may be disposed on the outer wall of the inner cylinder 113-1 for processing to collect weight data of kitchen waste. In some embodiments, a temperature sensor may be disposed on the outer wall of the inner cylinder 113-1 for processing to collect temperature data of kitchen waste. In some embodiments, sensor 130 may also include a force sensor. The force sensor may be disposed in a crushing component to obtain resistance data on the crushing component. For more information on crushing components and resistance data, please refer to the relevant content below.

[0032] In some embodiments, the processor 140 may be configured to obtain temperature data and garbage weight data of the inner cylinder 113-1 through the sensor 130; determine the heating time and heating power of the inner cylinder 113-1 based on the temperature data and the garbage weight data; generate a stop heating instruction and send it to the heating device 120 in response to the heating time and / or heating power meeting the preset conditions; and / or generate a separation instruction and send it to the separation device. For more information on generating a stop heating instruction and a separation instruction, see Figure 2 and its related contents.

[0033] In some embodiments, the food waste treatment device 100 may further include a cleaning component. Figure 1 (not shown) can be configured to periodically clean the suction component 113-5. For more information on periodically cleaning the suction component 113-5, see Figure 2 and its related contents.

[0034] In some embodiments, the food waste treatment device 100 may further include an exhaust component ( Figure 1 (not shown). In some embodiments, the exhaust component can be disposed inside the separation device 113 (e.g., the processing inner cylinder 113-1). The exhaust component can be configured to exhaust gas. In some embodiments, the exhaust component can exhaust gas generated by heating and / or gas generated by microbial degradation in the kitchen waste. For more information on exhaust gas, see Figure 3 and its related contents.

[0035] In some embodiments, the food waste treatment device 100 may further include a crushing component ( Figure 1 (not shown). The crushing component may be configured to crush the kitchen waste. The crushing component may include a plurality of crushing teeth. The crushing component may be disposed inside the inner cylinder 113-1. For more information on crushing the kitchen waste, see Figure 4and its related contents.

[0036] In some embodiments, the kitchen waste treatment device 100 may further include an image acquisition component ( Figure 1 (not shown). The image acquisition component may include a camera device, etc. The image acquisition component may be provided in the separation device 113 (for example, at least one of the processing inner cylinder 113-1, the collecting outer cylinder 113-2, the collecting box 113-3, and the suction component 113-5, etc.) to collect image data related to the kitchen waste treatment process. In some embodiments, the processor 140 may identify the density of the kitchen waste based on the image data. For more information on identifying the density of the kitchen waste, see Figure 4 and its related contents.

[0037] In some embodiments, the food waste treatment device 100 may further include a power supply component ( Figure 1 (not shown). The power supply assembly can be used to supply power to the food waste treatment device 100 to drive one or more components in the food waste treatment device 100 to operate.

[0038] In some embodiments, the food waste treatment device 100 may further include a touch screen ( Figure 1 (not shown). The touch screen can be used for interaction between the device and the operator. For example, the operator can understand the working conditions of each component by viewing the touch screen. For another example, the operator can input control instructions for the kitchen waste treatment device 100 through the touch screen.

[0039] In some embodiments of the present specification, by setting up multiple components in the kitchen waste treatment device, it is possible to achieve the crushing, solid-liquid separation and other treatments of kitchen waste, and the device can also complete automatic cleaning and gas exhaust. The entire treatment process is highly intelligent, and the device can automatically adapt to the kitchen waste according to different scenarios, which not only completes the scientific treatment of kitchen waste, but also realizes the recycling of resources and avoids problems such as odor that interferes with normal life.

[0040] Figure 2 is an exemplary flow chart of a method for treating kitchen waste according to some embodiments of this specification. Figure 2 As shown, the process 200 includes the following steps. In some embodiments, the process 200 can be executed by a processor of a food waste treatment device.

[0041] Step 210, obtaining temperature data and garbage weight data of the inner barrel.

[0042] In some embodiments, the temperature data may be an average temperature of the inner cylinder during a preset time period. In some embodiments, the temperature data may be a temperature feature vector composed of temperature values ​​of multiple points of the inner cylinder. The temperature data may be acquired based on a temperature sensor disposed in the inner cylinder. The preset time period may be manually preset.

[0043] In some embodiments, the garbage weight data may be the total weight of the food waste put into the inner barrel. In some embodiments, the garbage weight data may be the total amount of food waste contained in the inner barrel during the processing. In some embodiments, the garbage weight data may also be the weight of the solid waste remaining in the inner barrel after the inner barrel is processed. The garbage weight data may be obtained based on a gravity sensor provided in the inner barrel.

[0044] Step 220, based on the temperature data and the garbage weight data, determine the heating time and heating power of the inner drum.

[0045] In some embodiments, the processor can determine the heating time and heating power of the inner drum by querying a first preset table based on the temperature data and the garbage weight data. The first preset table includes the correspondence between different reference temperature data, different reference garbage weight data, different reference heating times, and different reference heating powers. The first preset table can be determined based on historical data or prior knowledge.

[0046] In some embodiments, the processor can also determine the heating time and heating power of the inner drum based only on the garbage weight data. For example, the heating time and the heating power are positively correlated with the garbage weight data, respectively. The greater the garbage weight, the longer the heating time and the greater the heating power. For another example, the processor can determine the garbage weight proportion coefficient corresponding to the garbage weight data based on the garbage weight data; and determine the heating time and the heating power based on the garbage weight proportion coefficient and the product of the preset heating time and the preset heating power, respectively. The garbage weight proportion coefficient can be determined based on the garbage weight data and the preset garbage weight. For example, the garbage weight proportion coefficient can be the proportion of the garbage weight data to the preset garbage weight. The preset garbage weight, preset heating time and preset heating power can be based on manual preset.

[0047] In some embodiments, the processor can adjust the heating power and heating time of the heating device in different time stages. In some embodiments, the processor can divide a day into multiple time stages, and each time stage can correspond to a preset different heating time and heating power. In some embodiments, the processor can determine the heating time and heating power of the previous time stage as the preset heating time and preset heating power of the current time stage based on the current time stage. By dividing the time stage into multiple stages, the heating time and heating power can be dynamically adjusted in stages. For more information about dynamic adjustment, please refer to Figure 3 and its related contents.

[0048] In some embodiments, the processor may also determine the heating time and heating power of the inner barrel based only on the humidity of the food waste. For example, the heating time and heating power are positively correlated with the humidity of the food waste. The greater the humidity of the food waste, the greater the heating power. The humidity of the food waste may be obtained based on a humidity sensor or the like provided in the inner barrel.

[0049] In some embodiments, the processor can also determine the heating time and heating power of the inner barrel based on the garbage weight data and the grease content data. Figure 3 and its related contents.

[0050] Step 230, in response to the heating time and the heating power satisfying the preset conditions, generating a stop heating instruction and sending it to the heating device; and / or generating a separation instruction and sending it to the separation device.

[0051] In some embodiments, the preset condition may be that the heating time is greater than a time threshold, and the heating power is greater than a power threshold. The time threshold and the power threshold may be system preset values, manually preset values, and the like.

[0052] The stop heating instruction is used to control the heating device to stop heating the separation device (e.g., the processing inner cylinder). The separation instruction is used to control the suction component to separate the first liquid at a preset suction power. The preset suction power refers to the power at which the preset suction component works. The preset suction power can be determined based on historical data, etc. For example, the processor can determine the historical suction filter in the previous suction process as the preset suction filter.

[0053] In some embodiments, when the heating time and the heating power meet preset conditions, the processor can directly generate a stop heating instruction.

[0054] In some embodiments, when the heating time and the heating power meet the preset conditions, the processor can generate a stop heating instruction. Further, after the heating device stops heating and reaches a preset time (a preset value or a system preset value, etc.), the processor can generate a separation instruction.

[0055] In some embodiments, when the heating time and the heating power meet the preset conditions, the processor can directly generate a separation instruction. At this time, the heating device can continue to heat the separation device (e.g., the processing inner cylinder).

[0056] In some embodiments, in response to the heating time and heating power satisfying preset conditions, the processor can determine the suction power and suction time of the suction component based on the garbage weight change characteristics within a preset time period; and generate a separation instruction based on the suction power and suction time.

[0057] The garbage weight change feature refers to the weight change of the kitchen waste within a preset time period. The preset time period can be manually set, for example, one hour.

[0058] In some embodiments, the garbage weight variation feature may include the degree of fluctuation of the garbage weight variation, etc. For example, the garbage weight variation feature may represent the degree of fluctuation of the garbage weight variation by the mean or variance of the weight variation of the kitchen waste within a preset time period.

[0059] In some embodiments, the garbage weight change feature may include the slope of the garbage weight change curve within a preset time period. The garbage weight change curve may be drawn based on weight data at multiple time points. The slope may be the tangent slope of the corresponding curve at a certain time point. A larger slope of the garbage weight change curve indicates that the weight changes faster at that time point. When the slope of the garbage weight change curve is a positive number, it indicates that the weight of the kitchen waste is increasing.

[0060] In some embodiments, the garbage weight change feature may further include a garbage weight change rate, which may be the weight change of the kitchen waste per unit time.

[0061] In some embodiments, the processor can determine the suction power and suction time in a variety of ways based on the garbage weight change characteristics within a preset period of time. For example, when the garbage weight is increasing, the suction power or suction time can be increased; when the garbage weight is decreasing, the suction power or suction time can be reduced. The increasing trend or decreasing trend of the garbage weight can be determined based on the slope of the garbage weight change curve.

[0062] In some embodiments, the processor may determine the suction power based on the garbage weight change rate within a preset period and the preset suction power; and determine the suction time based on the garbage weight change rate within a preset period and the preset suction time. For example, the suction power and the suction time may be determined by formula (1) and formula (2), respectively:

[0063]

[0064] Among them, p s is the suction power, p s0 is the preset suction power, t s is the suction time, t s0 To preset the suction time, is the rate of change of garbage weight, and k and m are preset coefficients. The preset suction power and the preset suction time can be determined based on manual experience. k and m can be adjusted manually based on the actual application scenario. For example, k and m can be different for the kitchens of pre-prepared food processing plants and small stores. For pre-prepared food processing plants, the amount of kitchen waste that needs to be processed is larger, and the suction component needs to work harder, so k and m are larger; while for the kitchens of small stores, the amount of kitchen waste that needs to be processed is relatively small, and the suction component works less hard, so k and m can be smaller.

[0065] In some embodiments, in response to the heating device stopping heating, the processor may generate a separation instruction to control the suction component to separate the first liquid according to the currently determined suction power and suction time.

[0066] In some embodiments of this specification, the suction power and suction time of the suction component are determined based on the characteristics of the change in garbage weight, and the suction power and suction time can be adjusted based on the change in garbage weight to ensure the solid-liquid separation efficiency of the garbage and ensure the efficient operation of the device. For example, when the total weight of the garbage increases, the suction power or suction time can be increased to improve the efficiency of solid-liquid separation; when the total weight of the garbage decreases, the suction power or suction time can be reduced to save energy.

[0067] Some embodiments of the present specification control heating and separation in real time and automatically according to the weight of the kitchen waste and the temperature of the inner processing drum, and are highly intelligent. When the working intensity of the device is high and the heating power and heating time meet the preset conditions, the heating device is promptly controlled to stop heating and / or the separation device is promptly controlled to perform separation treatment, so as to avoid equipment damage, energy consumption and hidden dangers caused by long-term high-power heating, and to separate the heated kitchen waste in time to improve the separation efficiency.

[0068] In some embodiments, the food waste treatment device further includes a cleaning component. For more information about the cleaning component, see Figure 1 The processor may be configured to determine a cleaning cycle based on the characteristics of garbage weight change and grease content change within a preset period of time.

[0069] The grease content variation characteristic refers to the variation of the grease content adsorbed in the filter within a preset time period. The grease content variation characteristic can be obtained based on the grease content data.

[0070] In some embodiments, the grease content change characteristics may include one or more of the degree of fluctuation of the grease content change within a preset time period, the slope of the grease content change curve, the grease content change rate, etc. The degree of fluctuation of the grease content change is similar to the degree of fluctuation of the garbage weight change, the slope of the grease content change curve is similar to the slope of the garbage weight change curve, and the grease content change rate is similar to the garbage weight change rate. For more explanations, refer to the above. The grease content can be determined based on a gravity sensor set in the filter.

[0071] The cleaning cycle refers to the cycle for cleaning the suction components.

[0072] In some embodiments, the processor can determine the cleaning cycle in a variety of ways based on the characteristics of garbage weight changes within a preset period of time. For example, when the garbage weight is increasing, the cleaning cycle can be reduced; when the garbage weight is decreasing, the cleaning cycle can be increased.

[0073] In some embodiments, the processor can determine the cleaning cycle in a variety of ways based on the grease content variation characteristics within a preset period of time. For example, when the grease content is increasing, the more grease the suction component contacts, the more grease remains inside the component, and more frequent cleaning is required, resulting in a shorter cleaning cycle.

[0074] In some embodiments, the processor can determine the cleaning cycle by querying a second preset table based on the grease content change characteristics and the garbage weight change characteristics. The second preset table contains the correspondence between different reference grease content change rates, different reference garbage weight change rates and different reference cleaning cycles. The second preset table can be determined based on historical data or prior knowledge.

[0075] In some embodiments, the processor may also determine the cleaning cycle based on a cycle determination model.

[0076] The cycle determination model may be a machine learning model, for example, a deep neural network (DNN) model.

[0077] In some embodiments, the input of the cycle determination model may include garbage weight change characteristics and grease content change characteristics; and the output may be a cleaning cycle.

[0078] In some embodiments, the processor may determine the model based on a large number of first samples with first labels and a training cycle. The first sample includes characteristics of sample garbage weight changes and sample grease content changes in a sample time period. The sample time period may be a historical time period in which the grease in the kitchen waste is fully adsorbed by the filter. Whether the filter has achieved sufficient adsorption can be determined based on the grease content in the second liquid. When the grease content in the second liquid is lower than a preset content threshold, it can be considered that the filter has achieved sufficient adsorption. The first label may be the actual cleaning cycle corresponding to the first sample. The first label may be determined by querying historical data or by manual labeling.

[0079] In some embodiments, the cleaning cycle may also be determined by manual presetting or the like.

[0080] The suction component needs to frequently come into contact with grease and absorb it into the interior of the component (for example, the filter). If the suction component is not cleaned for a long time, grease will accumulate more and more, directly affecting its suction efficiency and garbage disposal effect. In some embodiments of this specification, based on the weight of garbage and the grease content, the cycle of cleaning the suction component can be determined accordingly to maintain the efficient operation of the device. By training a large amount of historical data to obtain a cycle determination model, the self-learning ability of the machine learning model can be used to find patterns from a large amount of historical data, obtain the correlation between the characteristics of garbage weight changes and grease content changes, and improve the accuracy and efficiency of determining the cleaning cycle.

[0081] Figure 3 is an exemplary schematic diagram of generating exhaust instructions according to some embodiments of the present specification.

[0082] In some embodiments, the food waste treatment device further comprises an exhaust component. For more information about the exhaust component, see Figure 1 and its related contents.

[0083] In some embodiments, Figure 3 As shown, the processor can be configured to obtain the grease content data 310 of the filter screen; based on the garbage weight data 320 and the grease content data 310, determine the heating time 330 and the heating power 340 of the inner cylinder; in response to the heating time and the heating power meeting the preset conditions, generate an exhaust instruction 360 and send it to the exhaust component. For more information about the garbage weight data, grease content data, heating time and heating power, please refer to Figure 2 and its related contents.

[0084] In some embodiments, the processor can determine the heating time and heating power of the inner cylinder based only on the grease content data. For example, the heating time and heating power are positively correlated with the grease content data, respectively. The greater the grease content, the longer the heating time and the greater the heating power. For another example, the processor can determine the grease content proportional coefficient corresponding to the grease content data based on the grease content data; and, based on the product of the grease content proportional coefficient and the preset heating time and the preset heating power, determine the current heating time and heating power. The grease content proportional coefficient can be determined based on the grease content and the preset grease content. For example, the grease content proportional coefficient can be the ratio of the current grease content to the preset grease content. The preset grease content can be based on manual preset. For more information about the preset heating time and the preset heating power, see Figure 2 and its related description.

[0085] In some embodiments, the processor can jointly determine the heating time and the heating power based on the garbage weight data and the grease content data. In some embodiments, the processor can determine the grease ratio based on the garbage weight data and the grease content data; determine the grease ratio coefficient based on the grease ratio; and determine the heating time and the heating power based on the garbage weight ratio coefficient and the grease ratio coefficient. For example, the heating time and the heating power can be determined based on formulas (3) and (4), respectively:

[0086] t h =μ1×α×t h0 +μ2×b×t h0 (3)

[0087] P h =μ1×a×p h0 +μ2×b×P h0 (4)

[0088] Among them, t h is the heating time, p h is the heating power, μ1 is the garbage weight ratio coefficient corresponding to the garbage weight data, μ2 is the grease ratio coefficient corresponding to the grease ratio, t h0 is the preset heating time, p h0 is the preset heating power, a and b are weight coefficients (the weight corresponding to the garbage weight data and the weight corresponding to the grease content data, respectively).

[0089] In some embodiments, a and b can be manually set based on different application scenarios and processing requirements. For example, for application scenarios such as large hotels and canteens, the garbage weight is large, and the corresponding garbage weight data has a larger weight a; for application scenarios such as meat food processing plants, the grease content in the kitchen waste is large, and the corresponding grease content data has a larger weight b.

[0090] In some embodiments, the processor may generate an exhaust instruction for controlling the exhaust component to exhaust in response to the heating time and the heating power satisfying the preset conditions, and send the exhaust instruction to the exhaust component. The exhaust instruction may be used to control the exhaust component to exhaust the device. The preset conditions that the heating time and the heating power need to satisfy may be referred to in Figure 2 and its related contents.

[0091] In some embodiments of the present specification, an exhaust instruction is generated when the heating time and heating power of the heating equipment meet preset conditions, so that harmful gases that may be generated in the treatment process, such as gases generated by microbial degradation, gases generated during the heating process, etc., can be discharged in time to avoid the risk of poisoning caused by gas accumulation, and the odor generated by the gas can also be evacuated in time.

[0092] In some embodiments, the processor can dynamically adjust the heating time and heating power based on the characteristics of garbage weight change and grease content change within a preset period of time. For more information about the characteristics of garbage weight change and grease content change, please refer to Figure 2 and its related contents.

[0093] In some embodiments, the processor can adjust the heating time and heating power in a variety of ways. For example, the processor can adjust the heating time and heating power according to a preset heating time adjustment amount and a preset heating power adjustment amount. As an example only, the total weight of garbage in the morning may be relatively small, and the heating time and heating power are relatively small, so the heating time and heating power can be adjusted down according to the preset heating time adjustment amount and the preset heating power adjustment amount; and during the lunch period when the amount of garbage is large, the heating time and heating power need to be increased to ensure the efficiency of garbage disposal, so the heating time and heating power can be adjusted up according to the preset heating time adjustment amount and the preset heating power adjustment amount. In some embodiments, the processor can adjust the heating time and heating power based on different time stages. For example, a day (24 hours) is divided into multiple time stages, and the heating time and heating power of the heating device are determined in the manner described above according to the garbage weight change characteristics and grease content change characteristics of each time stage, and adjusted based on this.

[0094] In some embodiments, the processor can adjust the heating time and heating power by dynamically adjusting the model. The dynamic adjustment model can be a machine learning model. For example, the dynamic adjustment model can be a DNN model, etc.

[0095] In some embodiments, the input of the dynamic adjustment model may include the characteristics of garbage weight change and grease content change within a preset period; the output may be the heating time and heating power at a certain time after the preset period. For example, when the preset period is a historical period, the certain time after the preset period may be the current time or a certain time after the current time.

[0096] In some embodiments, the processor may train the dynamic adjustment model based on a large number of second samples with second labels. The second sample may be the same as the first sample. For more information about the first sample, see Figure 2 The second tag may be the historical heating time and the historical heating power of the second sample at a certain time after the sample time period. The second tag may be acquired based on historical data.

[0097] In some embodiments of this specification, based on the characteristics of garbage weight change and grease content change within a time period, the heating time and heating power at a certain time after the time period can be dynamically adjusted by real-time monitoring of the garbage processing situation, so as to ensure that the kitchen waste can be fully processed as much as possible and improve the working efficiency of the device. By dynamically adjusting the model to process the characteristics of garbage weight change and grease content change within a certain time period, the heating time and heating power at a certain time after the time period can be efficiently and accurately determined, and a more appropriate heating time and heating power can be obtained, thereby improving the grease adsorption rate and garbage processing efficiency.

[0098] Figure 4 It is an exemplary schematic diagram of determining the power adjustment amount according to some embodiments of this specification.

[0099] In some embodiments, the food waste treatment device further comprises a crushing component. For more information about the crushing component, see Figure 1 and its related contents.

[0100] In some embodiments, Figure 4 As shown, the processor can determine the initial crushing strength 420 based on the solid waste weight data 410 and send it to the crushing component; obtain the resistance change characteristics 430 of the crushing component during the crushing process; and determine the power adjustment amount 450 of the crushing component based on the resistance change characteristics 430, the waste weight change characteristics 440 during the crushing process, and the initial crushing strength 420. For more information on the waste weight change characteristics, please refer to Figure 2 and related instructions.

[0101] Solid waste weight data refers to the weight data of solid waste. In some embodiments, in response to the separation process being completed in the processing inner cylinder, the processor may obtain the solid waste weight data based on a gravity sensor provided in the processing inner cylinder. The processor may determine whether the separation process is completed in the processing inner cylinder in a variety of ways. For example, a weight sensor may be provided in the collecting outer cylinder, and when it is detected that the change in the weight of the first liquid in the collecting outer cylinder over a period of time is less than a change threshold, it may be determined that the separation process is completed in the processing inner cylinder. The change threshold may be a system preset value, a manually preset value, or the like. For more information on the hardness and density of kitchen waste, please refer to the relevant description below.

[0102] The initial crushing strength refers to the crushing strength initially used to crush the solid waste. In some embodiments, the processor can determine the initial crushing strength based on the solid waste weight data and the preset crushing coefficient. For example, the product of the solid waste weight data and the preset crushing coefficient can be determined as the initial crushing strength. In some embodiments, the preset crushing coefficient can be preset by the system or manually. In some embodiments, the processor can determine the preset crushing coefficient based on the hardness and density of the kitchen waste. For example, the processor can determine the preset crushing coefficient based on a table lookup. The method of determining the preset crushing coefficient based on a table lookup is similar to the method of determining the cleaning cycle based on the second preset table. For more information, see Figure 2 and its related description.

[0103] The resistance variation characteristic refers to the variation of the resistance of the crushing component. One or more force sensors may be provided at multiple points of the crushing component. The resistance variation characteristic may include one or more of the resistance average value, resistance variance, resistance standard deviation, etc. at multiple points.

[0104] In some embodiments, the processor can manually preset and assign corresponding weights to the force sensors set at different points, and obtain the resistance change characteristics by weighted summing the resistance data obtained by multiple force sensors. The weight corresponding to each force sensor is related to the position where the force sensor is placed, which can be based on manual preset. For example, if the resistance of the crushing component close to the discharge port is large, it means that there are still large hard objects in the garbage, and the power of the crushing component needs to be increased. Therefore, the weight corresponding to the force sensor placed at the discharge port of the crushing component is large.

[0105] The power adjustment value refers to the value for adjusting the working power of the crushing component. In some embodiments, the power adjustment value can be determined based on the resistance change characteristics and the garbage weight change characteristics during the crushing process. For example, the processor can determine the power adjustment value by looking up a table based on the average resistance value in the resistance change characteristics and the average garbage weight value in the garbage weight change characteristics. The method of determining the power adjustment based on the table lookup is similar to the method of determining the cleaning cycle based on the second preset table. For more information, see Figure 2 and its related description.

[0106] In some embodiments, the processor may determine the power adjustment amount through a power adjustment model.

[0107] The power adjustment model may be a machine learning model. For example, the power adjustment model may be a DNN model, etc. In some embodiments, the input of the power adjustment model may include resistance change characteristics, garbage weight change characteristics during the crushing process, and initial crushing strength; and the output may be a power adjustment amount.

[0108] In some embodiments, the processor may train the power adjustment model based on a large number of third samples with third labels. The third sample may include the sample resistance change characteristics, the sample garbage weight change characteristics and the sample initial crushing strength during the sample crushing process, and the third label may be the historical power adjustment amount corresponding to the sample crushing process. In some embodiments, the processor may determine the historical crushing process in which the resistance decreases steadily and the garbage weight decreases steadily as the sample crushing process. The third sample and the third label may be determined based on historical data.

[0109] In some embodiments, the processor may determine a crushing stop time based on a power change trend of the crushing component; based on the crushing stop time, generate a crushing stop instruction and send it to the crushing component.

[0110] The power change trend refers to the change of the crushing power of the crushing component over a period of time. The power change trend can be obtained based on the statistical analysis of the crushing power at multiple time points. For example, the power change trend can be reflected by a change curve.

[0111] The crushing stop time refers to the time when the damaged part stops working. In some embodiments, the processor can determine it based on the slope of the power change curve corresponding to the power change trend. The processor can use the time point when the slope is greater than the slope threshold as the crushing stop time. The slope threshold refers to the minimum value of the slope when the crushing needs to be stopped, which can be based on the system or manually preset.

[0112] The stop crushing instruction can be used to control the crushing component to stop the crushing process of the kitchen waste. In some embodiments, the processor can generate a stop crushing instruction based on the current moment being the crushing stop time, and send it to the crushing component.

[0113] In some embodiments of this specification, a stop crushing instruction is generated based on the power change trend of the crushing component, so that the resistance change of the crushing device can be monitored in real time, and the effect of garbage crushing can be accurately grasped, so as to adjust the power of the crushing device in time to achieve the best crushing effect, while avoiding energy waste, thereby saving energy. At the same time, the change of resistance of the crushing component can help to timely detect whether the component is operating abnormally, and issue a stop crushing instruction in time to stop the crushing component, so as to ensure the normal operation of the device and avoid device failure.

[0114] In some embodiments, the food waste treatment device further includes an image acquisition component. For more information about the image acquisition component, see Figure 1 and its related contents.

[0115] In some embodiments, the processor can be used to obtain the garbage density characteristic in response to the resistance change characteristic satisfying the first judgment condition; in response to the garbage density characteristic satisfying the second judgment condition, issue an alarm and generate a stop crushing instruction.

[0116] The first judgment condition is a condition that the resistance change characteristic needs to meet when determining whether the garbage density can be obtained. The first judgment condition may be that the average resistance value in the resistance change characteristic is greater than the resistance threshold. The resistance threshold may be manually preset.

[0117] Garbage density characteristics are parameters used to characterize garbage density. Garbage density characteristics may include the density size and density change rate of garbage in the inner barrel.

[0118] In some embodiments, the processor can obtain the garbage density feature based on the image acquisition component. The processor can obtain the garbage image in the crushing process through the image acquisition component, and determine the garbage density feature by performing image recognition and other processing on the garbage image. For example, the processor can use the ratio of the area occupied by the garbage part in the garbage image to the image size as the density size in the garbage density feature. Based on the garbage images collected at different time points, the garbage density size at different time points can be determined, and then the density change rate can be determined.

[0119] In some embodiments, the processor may also determine the hardness of the garbage based on the density change rate in the garbage density feature. For example, the processor may determine the hardness of the garbage by looking up a table. The method of determining the hardness of the garbage based on the table is similar to the method of determining the cleaning cycle based on the second preset table. For more information, see Figure 2 and its related description.

[0120] The second judgment condition is the condition that the garbage density feature needs to meet when judging whether to issue an alarm. The second judgment condition can be that the density size in the garbage density feature is not within the preset density range. The preset density range can be based on system or manual preset.

[0121] In some embodiments, the alarm may be issued in a variety of ways. For example, the processor may issue an alarm to remind the operator that there is too much garbage being processed and adjustments need to be made. The alarm may be in the form of a text pop-up window, sound, or flash.

[0122] In some embodiments, the processor may issue a stop crushing instruction to the crushing component in response to the garbage density feature satisfying the second judgment condition. The stop crushing instruction may be used to control the crushing component to stop working.

[0123] In some embodiments of the present specification, by real-time monitoring of the change in resistance of the crushing components, the crushing effect of the garbage can be accurately grasped, so as to adjust the crushing power of the crushing components in a timely manner to achieve the best crushing effect, while avoiding energy waste, thereby saving energy. The garbage density is determined based on the resistance change, and the workload of the crushing components is determined by analyzing the garbage density. According to the change in garbage density, the working power of the crushing components is adjusted to ensure the normal crushing work.

[0124] Some embodiments of the present specification provide a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the above-mentioned method for processing kitchen waste.

[0125] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0126] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0127] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0128] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0129] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0130] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A kitchen waste treatment device, characterized in that: The device comprises a box, a heating device, a sensor, a processor, and an image acquisition component; the box comprises a feed port, a discharge port, and a separation device; the feed port and the discharge port are both connected to the separation device; The separation equipment includes a processing inner cylinder, a collecting outer cylinder, a collecting box, a filter screen, a suction component and a matching pipeline; The processing inner cylinder is configured to separate and process the kitchen waste; the processing inner cylinder also includes a crushing component, and the crushing component is configured to crush the kitchen waste; The collecting outer cylinder is disposed around the outside of the processing inner cylinder, and the collecting outer cylinder is configured to collect the first liquid flowing out of the processing inner cylinder; One end of the suction component is connected to the collection outer cylinder, and the other end is connected to the collection box, and the suction component is configured to suck the second liquid in the collection outer cylinder into the collection box; The filter screen is disposed in the suction component, and the filter screen is configured to filter and absorb grease in the liquid; The heating device is connected to the processing inner cylinder to perform heating treatment on the processing inner cylinder; The image acquisition component is configured to acquire image data related to the kitchen waste treatment process; The processor is configured to: Acquiring temperature data and garbage weight data of the processing inner barrel through the sensor; Based on the temperature data and the garbage weight data, determining the heating time and heating power of the inner treatment drum; In response to the heating time and the heating power satisfying a preset condition, generating a stop heating instruction and sending it to the heating device; and / or generating a separation instruction and sending it to the separation device; wherein the separation instruction is used to control the suction component to separate the first liquid at a preset suction power; The processor is further configured to: Based on the solid waste weight data, determine the initial crushing strength and send it to the crushing component; Obtaining resistance variation characteristics of the crushing component during the crushing process; Based on the resistance variation characteristics, the garbage weight variation characteristics during the crushing process and the initial crushing strength, a power adjustment amount of the crushing component is determined by a power adjustment model, wherein the power adjustment model is a machine learning model; Determine the crushing stop time based on the power change trend of the crushing component; generate a crushing stop instruction based on the crushing stop time and send it to the crushing component; In response to the resistance change characteristic satisfying the first judgment condition, the image of the garbage in the crushing process is acquired by the image acquisition component, and image recognition is performed on the garbage image to acquire the garbage density characteristic; In response to the garbage density characteristic satisfying the second judgment condition, an alarm is issued, and the stop crushing instruction is generated and sent to the crushing component.

2. The device according to claim 1, characterized in that The device further comprises an exhaust component, the exhaust component is disposed inside the processing inner cylinder, and the exhaust component is configured to exhaust gas; The processor is further configured to: Obtaining grease content data of the filter; Determining the heating time and the heating power of the inner treatment drum based on the garbage weight data and the grease content data; In response to the heating time and the heating power satisfying the preset conditions, an exhaust instruction is generated and sent to the exhaust component.

3. The device according to claim 1, characterized in that The processor is further configured to: In response to the heating time and the heating power satisfying the preset condition, Determining the suction power and suction time of the suction component based on the garbage weight change characteristics within a preset period of time; The separation instruction is generated based on the puff power and the puff time.

4. The device according to claim 1, characterized in that The device further includes a cleaning component, which is configured to periodically clean the suction component; and the processor is further configured to: The cleaning cycle is determined based on the change characteristics of the total weight of garbage and the change characteristics of the grease content within a preset period of time.

5. A method for treating kitchen waste based on the kitchen waste treating device according to any one of claims 1 to 4, characterized in that: The method is executed by a processor, comprising: Obtain the temperature data and garbage weight data of the inner barrel; Based on the temperature data and the garbage weight data, determining the heating time and heating power of the inner treatment drum; In response to the heating time and the heating power satisfying a preset condition, Generate a stop heating instruction and send it to the heating device; and / or generating a separation instruction and sending it to a separation device; wherein the separation instruction is used to control the suction component to separate the first liquid at a preset suction power; The method further comprises: Based on the solid waste weight data, the initial crushing strength is determined and sent to the crushing component; Obtaining resistance variation characteristics of the crushing component during the crushing process; Based on the resistance variation characteristics, the garbage weight variation characteristics during the crushing process and the initial crushing strength, a power adjustment amount of the crushing component is determined by a power adjustment model, wherein the power adjustment model is a machine learning model; In response to the resistance change characteristic satisfying the first judgment condition, an image of the garbage in the crushing process is acquired through an image acquisition component, and image recognition is performed on the garbage image to acquire a garbage density characteristic; In response to the garbage density characteristic satisfying the second judgment condition, an alarm is issued, and the stop crushing instruction is generated and sent to the crushing component.

6. The method according to claim 5, characterized in that Based on the temperature data and the garbage weight data, determining the heating time and heating power of the inner treatment drum further comprises: Obtaining grease content data of the filter; Determining the heating time and the heating power of the inner treatment drum based on the garbage weight data and the grease content data; In response to the heating time and the heating power satisfying the preset conditions, an exhaust instruction is generated and sent to an exhaust component.

7. The method according to claim 5, characterized in that The generating separation instruction comprises: In response to the heating time and the heating power satisfying the preset condition, Determining the suction power and suction time of the suction component based on the garbage weight change characteristics within a preset period of time; The separation instruction is generated based on the puff power and the puff time.

8. The method according to claim 5, characterized in that The method further comprises: The cleaning cycle of the cleaning components is determined based on the total weight change characteristics of the garbage and the grease content change characteristics within a preset time period.

9. A computer-readable storage medium storing computer instructions, characterized in that: After the computer reads the computer instructions in the storage medium, the computer executes the kitchen waste treatment method as described in any one of claims 5-8 above.

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