Kitchen waste treatment machine capable of efficiently removing peculiar smell and control method of kitchen waste treatment machine

Abstract

The invention relates to the technical field of solid waste treatment, and discloses a kitchen waste treatment machine capable of efficiently removing peculiar smell and a control method of the kitchen waste treatment machine. An energy supply module and a control module are fixedly mounted on the lower surface of the bottom plate; the waste barrel is arranged above the bottom plate, a cutter assembly is arranged in the waste barrel and comprises a fixed cutter and a rotary cutter, the fixed cutter is fixed to the inner side wall of the waste barrel, the rotary cutter is rotatably connected to the inner bottom face of the waste barrel, the middle of the rotary cutter is connected with the energy supply module, and a force sensor is arranged on the surface of the rotary cutter; the filtering assembly comprises a first filter, a second filter and a negative pressure fan, and the filtering assembly is arranged on one side of the waste barrel; the control module is connected with the energy supply module and the force sensor and comprises an acquisition unit, an analysis unit, a processing unit and an adjustment unit. According to the kitchen garbage treatment system, efficient and intelligent kitchen garbage treatment is achieved, and the problems of high energy consumption, low efficiency and poor peculiar smell removal effect are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of solid waste treatment, and in particular to a highly efficient odor-removing kitchen waste treatment machine and a control method thereof. Background Art

[0002] As a device that can quickly process kitchen waste in households and the catering industry, food waste processors have been widely used in recent years. Such devices usually crush the food waste through a cutter assembly. However, the existing technology still has certain problems in actual use.

[0003] First of all, the food waste disposers currently on the market often lack targeted optimization mechanisms when dealing with food waste of different types and qualities. The tool speed is usually fixed or can only be simply adjusted manually. When faced with food waste of different qualities, it is difficult for the equipment to achieve efficient and accurate processing, resulting in low processing efficiency or excessive energy consumption. The existing food waste disposers have a relatively simple analysis of the comprehensive operating parameters of the energy supply module and the tool assembly during operation, and have failed to effectively integrate historical operating data for intelligent optimization and regulation, resulting in a deviation between the operating parameters and actual needs, further exacerbating the contradiction between equipment energy consumption and work efficiency. In addition, the current existing machines usually use simple filter elements to remove odors, which is poor, resulting in a poor user experience.

[0004] Therefore, it is necessary to design a highly efficient odor-removing food waste disposer and a control method thereof to solve the problems existing in the current technology. Summary of the invention

[0005] In view of this, the present invention proposes an efficient odor removal food waste disposer and a control method thereof, aiming to solve the problems that current food waste disposers lack a targeted optimization mechanism, fail to effectively integrate historical operation data, and have a poor user experience.

[0006] In one aspect, the present invention provides a highly efficient odor-removing food waste processor, comprising:

[0007] A housing assembly, comprising a bottom housing, a middle housing and a top housing;

[0008] A base plate, the lower surface of which is fixedly mounted with an energy supply module and a control module;

[0009] A waste bucket is arranged above the bottom plate, a tool assembly is arranged in the waste bucket, the tool assembly includes a fixed tool and a rotating tool, the fixed tool is fixed on the inner wall of the waste bucket, the rotating tool is rotatably connected to the inner bottom surface of the waste bucket, and the middle part of the rotating tool is connected to the energy supply module, and a force sensor is arranged on the surface of the rotating tool;

[0010] A filter assembly, comprising a first filter, a second filter and a negative pressure fan, wherein the filter assembly is arranged on one side of the waste barrel;

[0011] The control module is connected to the energy supply module and the force sensor, and the control module includes a collection unit, an analysis unit, a processing unit and an adjustment unit;

[0012] The collecting unit is configured to collect waste material quality data, and determine a corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed;

[0013] The parsing unit is configured to collect multiple historical energy supply records of the energy supply module, parse the historical energy supply records, and divide the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the parsing results;

[0014] The processing unit is configured to calculate a first historical energy supply deviation coefficient of the energy supply module according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record; the processing unit is also configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool speed and the historical energy supply record; calculate the comprehensive historical deviation coefficient of the energy supply module based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient;

[0015] The adjustment unit is configured to compare the comprehensive historical deviation coefficient with the historical adjustment scheme, determine the energy supply adjustment coefficient according to the comparison result to adjust the initial tool speed, and control the energy supply module to operate at the adjusted tool speed, wherein the historical adjustment scheme includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

[0016] Further, when the parsing unit divides the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records and historical low abnormal energy supply records based on the parsing result, it includes:

[0017] The parsing unit obtains corresponding historical initial load data according to the historical energy supply record, obtains a load difference according to the historical initial load data and a load threshold, wherein the load difference is the difference between the historical initial load data and the load threshold, and divides the historical energy supply record into a historical high abnormal energy supply record, a historical normal energy supply record, and a historical low abnormal energy supply record according to the load difference;

[0018] When the load difference is less than or equal to zero, the analysis unit will classify the corresponding historical energy supply record into the historical normal energy supply record; when the load difference is greater than zero and less than or equal to a times the load threshold, the analysis unit will classify the corresponding historical energy supply record into the historical low abnormal energy supply record; when the load difference is greater than a times the load threshold, the analysis unit will classify the corresponding historical energy supply record into the historical high abnormal energy supply record.

[0019] Further, when the processing unit calculates the first historical energy supply deviation coefficient of the energy supply module according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record, it includes:

[0020] The processing unit counts the historical high abnormal energy supply records and records them as the first energy supply data, counts the historical normal energy supply records and records them as the second energy supply data, and counts the historical low abnormal energy supply records and records them as the third energy supply data; the processing unit obtains the first historical energy supply deviation coefficient according to the first energy supply data, the second energy supply data and the third energy supply data;

[0021]

[0022] Among them, y1 represents the first historical energy supply deviation coefficient, s1 represents the first energy supply data, s2 represents the second energy supply data, and s3 represents the third energy supply data.

[0023] Further, when the processing unit calculates the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool rotation speed and the historical energy supply record, it includes:

[0024] The processing unit constructs a historical energy supply curve, the historical energy supply curve includes a plurality of groups to be analyzed, each of the groups to be analyzed includes a historical initial tool speed and corresponding historical initial load data, and the number of the groups to be analyzed is the same as the historical energy supply record;

[0025] The processing unit arbitrarily extracts two of the groups to be analyzed to obtain the first historical initial load data, the second historical initial load data, the first historical initial tool speed, and the second historical initial tool speed;

[0026] Calculate the load difference between the first historical initial load data and the second historical initial load data, record the absolute value of the load difference as the first load difference, extract the maximum historical initial load data and the minimum historical initial load data from all the groups to be analyzed, calculate the difference between the maximum historical initial load data and the minimum historical initial load data, record it as the maximum load difference; calculate the difference between the maximum load difference and the first load difference, record it as the absolute value of the load;

[0027] Calculate the speed difference between the first historical initial tool speed and the second historical initial tool speed, record the absolute value of the speed difference as the first speed difference, extract the maximum historical initial tool speed and the minimum historical initial tool speed from all the groups to be analyzed, calculate the difference between the maximum historical initial tool speed and the minimum historical initial tool speed, record it as the maximum speed difference; calculate the difference between the maximum speed difference and the first speed difference, record it as the absolute value of the speed;

[0028] The product of the absolute value of the load and the absolute value of the speed is used as the sub-energy supply deviation coefficient of the energy supply module, the sub-energy supply deviation coefficients corresponding to each two remaining groups to be analyzed are calculated, and the second historical energy supply deviation coefficient is obtained according to all the sub-energy supply deviation coefficients.

[0029] Further, when the processing unit obtains the second historical energy supply deviation coefficient according to all the sub-energy supply deviation coefficients, it includes:

[0030] The processing unit obtains a sub-energy supply deviation coefficient mean value according to all the sub-energy supply deviation coefficients, classifies all sub-energy supply deviation coefficients that are less than or equal to the sub-energy supply deviation coefficient mean value into a first sub-energy supply deviation set; and classifies all sub-energy supply deviation coefficients that are greater than the sub-energy supply deviation coefficient mean value into a second sub-energy supply deviation set;

[0031] The processing unit calculates a first energy supply deviation coefficient difference between each of the sub-energy supply deviation coefficients in the first sub-energy supply deviation set and an average of the sub-energy supply deviation coefficients, and establishes a first energy supply deviation coefficient difference set based on all of the first energy supply deviation coefficient differences; calculates a second energy supply deviation coefficient difference between each of the sub-energy supply deviation coefficients in the second sub-energy supply deviation set and an average of the sub-energy supply deviation coefficients, and establishes a second energy supply deviation coefficient difference set based on all of the second energy supply deviation coefficient differences;

[0032] The processing unit randomly combines first energy supply deviation coefficient differences in the first energy supply deviation coefficient difference set with second energy supply deviation coefficient differences in the second energy supply deviation coefficient difference set in pairs to obtain a plurality of sub-energy supply deviation coefficient difference sets;

[0033] The processing unit obtains a second historical energy supply deviation coefficient of the energy supply module according to all the sub-energy supply deviation coefficient difference sets.

[0034] Further, when the processing unit obtains the second historical energy supply deviation coefficient of the energy supply module according to all the sub-energy supply deviation coefficient difference sets, it includes:

[0035]

[0036] Wherein, y2 represents the second historical energy supply deviation coefficient, n represents the number of sub-energy supply deviation coefficient difference value sets, c1i represents the first energy supply deviation coefficient difference value in the i-th sub-energy supply deviation coefficient difference value set, c2i represents the second energy supply deviation coefficient difference value in the i-th sub-energy supply deviation coefficient difference value set, ((c1i-c2i) 2 )min for all (c1i-c2i) 2 The minimum value among ((c1i-c2i) 2 )max is all (c1i-c2i) 2 The maximum value in Δs 2 For all (c1 i -c2 i ) 2 The variance of .

[0037] Further, when the processing unit calculates the comprehensive historical deviation coefficient of the energy supply module based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient, it includes:

[0038] Y = a1 × y1 + a2 × y2;

[0039] Among them, Y represents the comprehensive historical deviation coefficient, y1 represents the first historical energy supply deviation coefficient, y2 represents the second historical energy supply deviation coefficient, a1 and a2 are weight coefficients, and a1+a2=1, a1>a2.

[0040] Furthermore, when the adjustment unit determines the energy supply adjustment coefficient according to the comparison result to adjust the initial tool rotation speed, it includes:

[0041] When there is data in the historical adjustment scheme that the historical comprehensive historical deviation coefficient is the same as the comprehensive historical deviation coefficient, the adjustment unit uses the historical adjustment coefficient as the adjustment coefficient, obtains the product of the adjustment coefficient and the initial tool speed, and obtains the adjusted tool speed;

[0042] When all the historical comprehensive historical deviation coefficients in the historical adjustment scheme are different from the comprehensive historical deviation coefficient, the adjustment unit selects the historical comprehensive historical deviation coefficients in the historical adjustment scheme whose differences with the comprehensive deviation coefficient are within the range of b% as an approximate set, and determines the adjustment coefficient according to the historical adjustment coefficients corresponding to the historical comprehensive historical deviation coefficients in the approximate set to adjust the initial tool speed.

[0043] Further, when the adjustment unit determines the adjustment coefficient to adjust the initial tool rotation speed according to the historical adjustment coefficient corresponding to the historical comprehensive historical deviation coefficient in the approximate set, it includes:

[0044]

[0045] Among them, T represents the adjustment coefficient, Tj represents the jth historical comprehensive historical deviation coefficient in the approximate set, T0 represents the mean of the historical comprehensive historical deviation coefficients in the approximate set, and M represents the number of historical comprehensive historical deviation coefficients in the approximate set.

[0046] Compared with the prior art, the beneficial effects of the present invention are: the waste quality data is collected by the collection unit of the control module, and the initial tool speed is determined in combination with the preset corresponding table to ensure that the working parameters of the tool assembly match the waste characteristics, thereby improving the processing efficiency and reducing energy consumption. The analysis unit deeply analyzes the historical energy supply records of the energy supply module, divides the records into three types: high abnormality, normal and low abnormality, and calculates the comprehensive historical deviation coefficient through the processing unit, thereby realizing the accurate evaluation and regulation of the operating status of the energy supply module. The adjustment unit dynamically adjusts the tool speed by comparing the comprehensive historical deviation coefficient with the historical adjustment scheme to ensure that the equipment can operate at the best efficiency under different working conditions. In addition, the filter component effectively improves the deodorization effect and improves the user experience through the synergistic effect of the first filter, the second filter and the negative pressure fan. Efficient and intelligent kitchen waste treatment is realized, solving the problems of high energy consumption, low efficiency and poor deodorization effect existing in the prior art.

[0047] On the other hand, the present application also provides a control method for a food waste disposer with high efficiency in removing odors, which is used to apply the above-mentioned food waste disposer with high efficiency in removing odors, comprising:

[0048] Collecting waste material quality data, and determining a corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed;

[0049] Collecting multiple historical energy supply records of the energy supply module, parsing the historical energy supply records, and dividing the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the parsing results;

[0050] The first historical energy supply deviation coefficient of the energy supply module is calculated according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record; the processing unit is also configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool speed and the historical energy supply record; the comprehensive historical deviation coefficient of the energy supply module is calculated based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient;

[0051] The comprehensive historical deviation coefficient is compared with the historical adjustment plan, and the energy supply adjustment coefficient is determined according to the comparison result to adjust the initial tool speed, and the energy supply module is controlled to operate at the adjusted tool speed, wherein the historical adjustment plan includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

[0052] It is understandable that the above-mentioned high-efficiency odor-removing food waste disposer and control method thereof have the same beneficial effects and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0054] Figure 1 A schematic diagram of the structure of a highly efficient odor-removing kitchen waste disposer provided by an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the structure of a kitchen waste disposer with high efficiency in removing odors and removing the outer shell assembly provided by an embodiment of the present invention;

[0056] Figure 3 A front view of a housing assembly of a food waste disposer with high efficiency in removing odors provided by an embodiment of the present invention;

[0057] Figure 4 A side view of a housing assembly of a food waste disposer with high efficiency in removing odors provided by an embodiment of the present invention;

[0058] Figure 5 A top view of a housing assembly of a food waste disposer with high efficiency in removing odors provided by an embodiment of the present invention;

[0059] Figure 6 A flow chart of a method for controlling a food waste disposer with high efficiency for removing odors provided in an embodiment of the present invention.

[0060] Among them, 100, a highly efficient odor-removing food waste disposer; 110, a shell assembly; 111, a bottom shell; 112, a middle shell; 113, a top shell; 120, a bottom plate; 121, a power supply module; 122, a control module; 130, a waste bin; 131, a fixed tool; 132, a rotating tool; 133, a force sensor; 140, a filter assembly; 141, a first filter; 142, a second filter; 143, a negative pressure fan. DETAILED DESCRIPTION

[0061] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0062] In some embodiments of the present application, see Figure 1-5 As shown, the highly efficient odor removal food waste treatment machine 100 comprises:

[0063] The housing assembly 110 includes a bottom housing 111 , a middle housing 112 and a top housing 113 .

[0064] The bottom plate 120 has a power supply module 121 and a control module 122 fixedly mounted on its lower surface.

[0065] The waste bucket 130 is arranged above the base plate 120. A tool assembly is arranged in the waste bucket 130. The tool assembly includes a fixed tool 131 and a rotating tool 132. The fixed tool 131 is fixed on the inner wall of the waste bucket 130. The rotating tool 132 is rotatably connected to the inner bottom surface of the waste bucket 130, and the middle part of the rotating tool 132 is connected to the energy supply module 121. A force sensor 133 is arranged on the surface of the rotating tool 132.

[0066] The filter assembly 140 includes a first filter 141 , a second filter 142 and a negative pressure fan 143 . The filter assembly 140 is disposed on one side of the waste barrel 130 .

[0067] The control module 122 is connected to the energy supply module 121 and the force sensor 133 , and includes a collection unit, an analysis unit, a processing unit, and an adjustment unit.

[0068] The collecting unit is configured to collect waste material quality data, and determine the corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed.

[0069] The parsing unit is configured to collect multiple historical energy supply records of the energy supply module 121, parse the historical energy supply records, and divide the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the parsing results.

[0070] The processing unit is configured to calculate a first historical energy supply deviation coefficient of the energy supply module 121 according to the historical high abnormal energy supply record, the historical normal energy supply record, and the historical low abnormal energy supply record. The processing unit is also configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module 121 according to the historical initial tool speed and the historical energy supply record. The comprehensive historical deviation coefficient of the energy supply module 121 is calculated based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient.

[0071] The adjustment unit is configured to compare the comprehensive historical deviation coefficient with the historical adjustment plan, determine the energy supply adjustment coefficient according to the comparison result to adjust the initial tool speed, and control the energy supply module 121 to operate at the adjusted tool speed, wherein the historical adjustment plan includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

[0072] Specifically, the housing assembly 110 includes a bottom housing 111, a middle housing 112 and a top housing 113. Its main function is to provide a sturdy and airtight structure to prevent garbage and odor leakage and ensure the safe operation of the equipment. The bottom plate 120 is located at the lower part of the equipment, and the energy supply module 121 and the control module 122 are fixedly installed on its lower surface. The energy supply module 121 is responsible for providing power to the tool assembly so that the rotating tool 132 can operate efficiently to dispose of garbage. The control module 122 is responsible for monitoring the working status of the equipment and making adjustments to ensure that the equipment operates under optimal conditions. The waste bucket 130 is arranged above the bottom plate 120, and has a built-in tool assembly, including a fixed tool 131 and a rotating tool 132. The fixed tool 131 is fixed on the inner wall of the waste bucket 130, and is used to cooperate with the rotating tool 132 to crush garbage. The rotating tool 132 is rotatably connected to the inner bottom surface of the waste bucket 130, and is connected to the middle of the energy supply module 121 to provide rotational power. In addition, a force sensor 133 is installed on the surface of the rotating tool 132, which can monitor the working state of the tool and the load it is subjected to in real time. The filter assembly 140 includes a first filter 141, a second filter 142 and a negative pressure fan 143, which are arranged on one side of the waste barrel 130. The negative pressure fan 143 generates negative pressure, sucks the odor generated in the waste barrel 130, and purifies it through the first filter 141. The internal channel of the first filter 141 adopts an S-shaped enlarged path, and adsorbed carbon is set in the first filter 141. When the hot steam in the waste barrel 130 and the cold air in the cover interlayer form a mixed gas, it enters the first filter 141 under the negative pressure of the negative pressure fan 143. Through the lengthened path, the temporarily stored moisture is slowly discharged from the S-shaped filter element to achieve the effect of removing odor.

[0073] Specifically, the control module 122 connects the energy supply module 121 and the force sensor 133, and includes an acquisition unit, an analysis unit, a processing unit and an adjustment unit. The acquisition unit collects the quality data of the waste in real time, and determines the initial tool speed according to the preset mapping table and the waste quality data. In this way, the tool speed can be adjusted according to the characteristics of different wastes (such as quality, density, etc.) to achieve accurate processing. The analysis unit collects multiple historical energy supply records of the energy supply module 121, analyzes these records, and analyzes the abnormal energy supply conditions therein. Through analysis, the historical energy supply records are divided into three categories: high abnormality, normal and low abnormality, which helps to identify the working state of the energy supply module 121. The processing unit calculates the historical energy supply deviation coefficient of the energy supply module 121 based on the analysis results of the analysis unit. The processing unit will further calculate the second historical energy supply deviation coefficient based on the historical energy supply records and their corresponding tool speeds. The comprehensive historical deviation coefficient of the energy supply module 121 is calculated based on the two deviation coefficients. The adjustment unit adjusts the rotation speed of the tool according to the comparison result of the comprehensive historical deviation coefficient and the historical adjustment scheme to ensure that the energy supply module 121 can operate in the best state and avoid excessive energy consumption or insufficient operation.

[0074] It is understandable that by introducing an intelligent adjustment mechanism and historical data feedback analysis, the food waste disposer is able to achieve efficient adaptability in different waste treatment processes. The acquisition and analysis unit can adjust the tool speed in real time according to the waste quality and historical energy supply records, avoiding the low energy efficiency and low processing efficiency caused by fixed speed or simple adjustment of traditional equipment. The stability and service life of the equipment are further guaranteed by the coordinated monitoring of the force sensor 133. The addition of the filter component 140 effectively solves the odor problem and improves the user experience. The processing capacity of the equipment is optimized and energy consumption is reduced.

[0075] In some embodiments of the present application, when the parsing unit divides the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records and historical low abnormal energy supply records based on the parsing results, it includes: the parsing unit obtains the corresponding historical initial load data according to the historical energy supply records, obtains the load difference according to the historical initial load data and the load threshold, the load difference is the difference between the historical initial load data and the load threshold, and divides the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records and historical low abnormal energy supply records according to the load difference.

[0076] Specifically, when the load difference is less than or equal to zero, the parsing unit classifies the corresponding historical energy supply record into the historical normal energy supply record. When the load difference is greater than zero and less than or equal to a times the load threshold, the parsing unit classifies the corresponding historical energy supply record into the historical low abnormal energy supply record. When the load difference is greater than a times the load threshold, the parsing unit classifies the corresponding historical energy supply record into the historical high abnormal energy supply record.

[0077] In some embodiments of the present application, when the processing unit calculates the first historical energy supply deviation coefficient of the energy supply module 121 according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record, it includes:

[0078] The processing unit collects historical high abnormal energy supply records and records them as first energy supply data, collects historical normal energy supply records and records them as second energy supply data, collects historical low abnormal energy supply records and records them as third energy supply data. The processing unit obtains the first historical energy supply deviation coefficient according to the first energy supply data, the second energy supply data and the third energy supply data.

[0079]

[0080] Among them, y1 represents the first historical energy supply deviation coefficient, s1 represents the first energy supply data, s2 represents the second energy supply data, and s3 represents the third energy supply data.

[0081] Specifically, by introducing load difference analysis and combining the detailed classification of historical energy supply records, the adjustment accuracy of the energy supply module 121 is effectively improved. The calculation of load threshold and deviation coefficient provides a basis for the dynamic adjustment of the equipment. The parsing and processing unit can discover potential abnormal operation modes through the analysis of historical data and make timely adjustments to maintain the efficient operation of the equipment.

[0082] It is understandable that by more accurately classifying and analyzing historical energy supply records, a detailed view of the operating status of the energy supply module 121 is provided. The parsing unit can perform intelligent optimization for different working conditions by calculating the load difference and dividing the energy supply records into three categories (high abnormality, normal, and low abnormality). The working stability of the energy supply module 121 is improved, and equipment damage caused by overload or insufficient energy is effectively avoided. The processing unit further optimizes the working parameters of the energy supply module 121 by calculating the energy supply deviation coefficient to ensure that the equipment maintains efficient and stable operation. This embodiment can dynamically respond to historical data, avoid the inefficiency problems caused by traditional fixed speeds and simple adjustments, and improve overall energy efficiency and service life.

[0083] In some embodiments of the present application, when the processing unit calculates the second historical energy supply deviation coefficient of the energy supply module 121 according to the historical initial tool speed and the historical energy supply record, it includes:

[0084] The processing unit constructs a historical energy supply curve, which includes a number of groups to be analyzed. Each group to be analyzed includes historical initial tool speed and corresponding historical initial load data, and the number of groups to be analyzed is the same as the historical energy supply record.

[0085] The processing unit randomly extracts two groups to be analyzed, and obtains the first historical initial load data, the second historical initial load data, the first historical initial tool speed, and the second historical initial tool speed.

[0086] The load difference between the first historical initial load data and the second historical initial load data is calculated, and the absolute value of the load difference is recorded as the first load difference. The maximum historical initial load data and the minimum historical initial load data are extracted from all the groups to be analyzed, and the difference between the maximum historical initial load data and the minimum historical initial load data is calculated and recorded as the maximum load difference. The difference between the maximum load difference and the first load difference is calculated and recorded as the absolute value of the load.

[0087] Calculate the speed difference between the first historical initial tool speed and the second historical initial tool speed, record the absolute value of the speed difference as the first speed difference, extract the maximum historical initial tool speed and the minimum historical initial tool speed from all the groups to be analyzed, calculate the difference between the maximum historical initial tool speed and the minimum historical initial tool speed, and record it as the maximum speed difference. Calculate the difference between the maximum speed difference and the first speed difference, and record it as the absolute value of the speed.

[0088] The product of the absolute value of the load and the absolute value of the speed is used as the sub-energy supply deviation coefficient of the energy supply module 121, and the sub-energy supply deviation coefficients corresponding to each two remaining groups to be analyzed are calculated. The second historical energy supply deviation coefficient is obtained according to all the sub-energy supply deviation coefficients.

[0089] In some embodiments of the present application, when the processing unit obtains the second historical energy supply deviation coefficient based on all sub-energy supply deviation coefficients, it includes: the processing unit obtains the mean of the sub-energy supply deviation coefficient based on all the sub-energy supply deviation coefficients, and classifies all the sub-energy supply deviation coefficients that are less than or equal to the mean of the sub-energy supply deviation coefficients as a first sub-energy supply deviation set. All sub-energy supply deviation coefficients that are greater than the mean of the sub-energy supply deviation coefficients are classified as a second sub-energy supply deviation set. The processing unit calculates the first energy supply deviation coefficient difference between each sub-energy supply deviation coefficient in the first sub-energy supply deviation set and the mean of the sub-energy supply deviation coefficient, and establishes a first energy supply deviation coefficient difference set based on all the first energy supply deviation coefficient differences. Calculate the second energy supply deviation coefficient difference between each sub-energy supply deviation coefficient in the second sub-energy supply deviation set and the mean of the sub-energy supply deviation coefficient, and establish a second energy supply deviation coefficient difference set based on all the second energy supply deviation coefficient differences. The processing unit randomly combines the first energy supply deviation coefficient differences in the first energy supply deviation coefficient difference set and the second energy supply deviation coefficient differences in the second energy supply deviation coefficient difference set in pairs to obtain a plurality of sub-energy supply deviation coefficient difference sets.

[0090] The processing unit obtains the second historical energy supply deviation coefficient of the energy supply module 121 according to all sub-energy supply deviation coefficient difference sets.

[0091] In some embodiments of the present application, when the processing unit obtains the second historical energy supply deviation coefficient of the energy supply module 121 according to all sub-energy supply deviation coefficient difference sets, it includes:

[0092]

[0093] Among them, y2 represents the second historical energy supply deviation coefficient, n represents the number of sub-energy supply deviation coefficient difference sets, c1 i represents the first energy supply deviation coefficient difference in the i-th sub-energy supply deviation coefficient difference set, c2 i is the second energy supply deviation coefficient difference in the ith sub-energy supply deviation coefficient difference set, ((c1i-c2i) 2 )min for all (c1i-c2i) 2 The minimum value among ((c1i-c2i) 2 )max is all (c1i-c2i) 2 The maximum value in Δs 2 For all (c1 i -c2 i ) 2 The variance of .

[0094] In some embodiments of the present application, when the processing unit calculates the comprehensive historical deviation coefficient of the energy supply module 121 based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient, it includes:

[0095] Y = a1 × y1 + a2 × y2;

[0096] Among them, Y represents the comprehensive historical deviation coefficient, y1 represents the first historical energy supply deviation coefficient, y2 represents the second historical energy supply deviation coefficient, a1 and a2 are weight coefficients, and a1+a2=1, a1>a2.

[0097] Specifically, by introducing a series of factors such as load difference, speed difference, sub-power supply deviation coefficient, etc., the historical operating status of the power supply module 121 is carefully monitored and analyzed. By calculating the differences between multiple historical groups to be analyzed, the performance of the power supply module 121 under different working conditions can be accurately evaluated, and the accuracy of the calculation can be further improved through the difference set. The refined data processing method enables the system to optimize the adjustment parameters of the power supply module 121 under different load and speed conditions and improve the overall operating efficiency.

[0098] It is understandable that through in-depth analysis of historical energy supply records, the accuracy of deviation coefficient calculation is improved, and the energy supply module 121 is optimized and adjusted under different operating conditions. By accurately calculating the load and speed differences, and combining the sub-energy supply deviation coefficient difference set, more intelligent adjustments can be made based on historical data, avoiding the efficiency loss that may be caused by overly simple adjustment methods. The introduction of comprehensive historical deviation coefficients further improves the comprehensive evaluation capabilities of the energy supply module 121, ensuring that the equipment can always operate in the best performance state, and improving the overall energy efficiency and service life. Improve the operating stability and processing efficiency of the equipment.

[0099] In some embodiments of the present application, when the adjustment unit determines the energy supply adjustment coefficient according to the comparison result to adjust the initial tool rotation speed, it includes:

[0100] When there is data in the historical adjustment scheme that the historical comprehensive historical deviation coefficient is the same as the comprehensive historical deviation coefficient, the adjustment unit uses the historical adjustment coefficient as the adjustment coefficient, obtains the product of the adjustment coefficient and the initial tool speed, and obtains the adjusted tool speed.

[0101] When all historical comprehensive historical deviation coefficients in the historical adjustment plan are different from the comprehensive historical deviation coefficient, the adjustment unit selects the historical comprehensive historical deviation coefficients in the historical adjustment plan whose difference with the comprehensive deviation coefficient is within the range of b% as the approximate set, and determines the adjustment coefficient according to the historical adjustment coefficients corresponding to the historical comprehensive historical deviation coefficients in the approximate set to adjust the initial tool speed.

[0102] In some embodiments of the present application, when the adjustment unit determines the adjustment coefficient to adjust the initial tool rotation speed according to the historical adjustment coefficient corresponding to the historical comprehensive historical deviation coefficient in the approximation set, it includes:

[0103]

[0104] Among them, T represents the adjustment coefficient, Tj represents the jth historical comprehensive historical deviation coefficient in the approximate set, T0 represents the mean of the historical comprehensive historical deviation coefficients in the approximate set, and M represents the number of historical comprehensive historical deviation coefficients in the approximate set.

[0105] Specifically, by finding the historical data closest to the current comprehensive historical deviation coefficient in the historical adjustment scheme, the adjustment error caused by the inability to find completely matching data is reduced. By selecting historical adjustment data with a difference of b% from the current deviation coefficient and determining the adjustment coefficient based on these data, the adjustment process is refined. In particular, when there is no completely matching historical data, a suitable "approximate" set can still be found, ensuring the smooth transition and rationality of the adjustment process.

[0106] It is understandable that when adjusting the tool speed, more accurate adjustment can be achieved by intelligently matching the difference between the historical comprehensive historical deviation coefficient and the current comprehensive historical deviation coefficient. By introducing the "approximate set" mechanism, performance fluctuation problems caused by missing or incomplete matching of historical data are avoided. The adaptability and robustness of the system are improved, ensuring that the tool speed is reasonably adjusted under various loads and operating conditions, thereby optimizing equipment operating efficiency and energy consumption. This embodiment makes the adjustment of the energy supply module 121 more flexible and precise, improves the level of intelligence and adaptability, and further improves the processing efficiency and stability of the food waste processor.

[0107] It is understandable that when the device is used for the first time, since historical data has not yet been accumulated, the adjustment unit cannot directly compare and adjust according to the historical comprehensive historical deviation coefficient. At this time, the tool speed will be initially adjusted based on the preset default parameters or the set initial assumptions. The energy supply module 121 will be started according to the initial operating status of the equipment, the type of waste, and the basic information of the working environment through the set standards or experience values. The set standards and experience values ​​can be manually set according to actual use requirements, and gradually start running. During the operation process, according to the actual load data and tool speed feedback, real-time adjustments and optimizations will be continuously performed to accumulate the first round of operation data. After the system obtains a certain number of historical records, it can make more precise adjustments and optimizations based on the actual data.

[0108] In the above embodiment, the waste quality data is collected by the collection unit of the control module, and the initial tool speed is determined in combination with the preset corresponding table to ensure that the working parameters of the tool assembly match the waste characteristics, thereby improving the processing efficiency and reducing energy consumption. The analysis unit deeply analyzes the historical energy supply records of the energy supply module, divides the records into three types: high abnormality, normal and low abnormality, and calculates the comprehensive historical deviation coefficient through the processing unit, thereby realizing the accurate evaluation and regulation of the operating status of the energy supply module. The adjustment unit compares the comprehensive historical deviation coefficient with the historical adjustment scheme to dynamically adjust the tool speed to ensure that the equipment can operate at optimal efficiency under different working conditions. In addition, the filter component effectively improves the deodorization effect and improves the user experience through the synergistic effect of the first filter, the second filter and the negative pressure fan. Efficient and intelligent kitchen waste treatment is achieved, solving the problems of high energy consumption, low efficiency and poor deodorization effect in the prior art.

[0109] In another preferred embodiment based on the above embodiment, refer to Figure 6 As shown, this embodiment provides a control method for a food waste disposer with high efficiency in removing odors, which is applied to the above-mentioned food waste disposer with high efficiency in removing odors, and includes:

[0110] S100: collecting waste material quality data, and determining a corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed;

[0111] S200: Collect multiple historical energy supply records of the energy supply module, analyze the historical energy supply records, and divide the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the analysis results;

[0112] S300: Calculate a first historical energy supply deviation coefficient of the energy supply module according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record; the processing unit is further configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool speed and the historical energy supply record; calculate the comprehensive historical deviation coefficient of the energy supply module based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient;

[0113] S400: Compare the comprehensive historical deviation coefficient with the historical adjustment plan, determine the energy supply adjustment coefficient according to the comparison result to adjust the initial tool speed, and control the energy supply module to operate at the adjusted tool speed, wherein the historical adjustment plan includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

[0114] It is understandable that the waste quality data is collected by the acquisition unit of the control module, and the initial tool speed is determined in combination with the preset corresponding table to ensure that the working parameters of the tool assembly match the waste characteristics, thereby improving the processing efficiency and reducing energy consumption. The analysis unit deeply analyzes the historical energy supply records of the energy supply module, divides the records into three types: high abnormality, normal and low abnormality, and calculates the comprehensive historical deviation coefficient through the processing unit, thereby realizing the accurate evaluation and regulation of the operating status of the energy supply module. The adjustment unit compares the comprehensive historical deviation coefficient with the historical adjustment plan to dynamically adjust the tool speed to ensure that the equipment can operate at optimal efficiency under different working conditions. In addition, the filter component effectively improves the deodorization effect and improves the user experience through the synergistic effect of the first filter, the second filter and the negative pressure fan. Efficient and intelligent kitchen waste treatment is achieved, solving the problems of high energy consumption, low efficiency and poor deodorization effect in the prior art.

[0115] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0116] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0118] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A highly efficient odor removal kitchen waste processor, characterized in that: include: A housing assembly, comprising a bottom housing, a middle housing and a top housing; A base plate, the lower surface of which is fixedly mounted with an energy supply module and a control module; A waste bucket is arranged above the bottom plate, a tool assembly is arranged in the waste bucket, the tool assembly includes a fixed tool and a rotating tool, the fixed tool is fixed on the inner wall of the waste bucket, the rotating tool is rotatably connected to the inner bottom surface of the waste bucket, and the middle part of the rotating tool is connected to the energy supply module, and a force sensor is arranged on the surface of the rotating tool; A filter assembly, comprising a first filter, a second filter and a negative pressure fan, wherein the filter assembly is arranged on one side of the waste barrel; The control module is connected to the energy supply module and the force sensor, and the control module includes a collection unit, an analysis unit, a processing unit and an adjustment unit; The collecting unit is configured to collect waste material quality data, and determine a corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed; The parsing unit is configured to collect multiple historical energy supply records of the energy supply module, parse the historical energy supply records, and divide the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the parsing results; The processing unit is configured to calculate a first historical energy supply deviation coefficient of the energy supply module according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record; the processing unit is also configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool speed and the historical energy supply record; calculate the comprehensive historical deviation coefficient of the energy supply module based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient; The adjustment unit is configured to compare the comprehensive historical deviation coefficient with the historical adjustment scheme, determine the energy supply adjustment coefficient according to the comparison result to adjust the initial tool speed, and control the energy supply module to operate at the adjusted tool speed, wherein the historical adjustment scheme includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

2. The highly efficient odor-removing food waste processor according to claim 1, characterized in that: When the parsing unit divides the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records and historical low abnormal energy supply records based on the parsing result, it includes: The parsing unit obtains corresponding historical initial load data according to the historical energy supply record, obtains a load difference according to the historical initial load data and a load threshold, wherein the load difference is the difference between the historical initial load data and the load threshold, and divides the historical energy supply record into a historical high abnormal energy supply record, a historical normal energy supply record, and a historical low abnormal energy supply record according to the load difference; When the load difference is less than or equal to zero, the analysis unit will classify the corresponding historical energy supply record into the historical normal energy supply record; when the load difference is greater than zero and less than or equal to a times the load threshold, the analysis unit will classify the corresponding historical energy supply record into the historical low abnormal energy supply record; when the load difference is greater than a times the load threshold, the analysis unit will classify the corresponding historical energy supply record into the historical high abnormal energy supply record.

3. The highly efficient odor-removing food waste processor according to claim 2, characterized in that: When the processing unit calculates the first historical energy supply deviation coefficient of the energy supply module according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record, it includes: The processing unit counts the historical high abnormal energy supply records and records them as the first energy supply data, counts the historical normal energy supply records and records them as the second energy supply data, and counts the historical low abnormal energy supply records and records them as the third energy supply data; the processing unit obtains the first historical energy supply deviation coefficient according to the first energy supply data, the second energy supply data and the third energy supply data; Among them, y1 represents the first historical energy supply deviation coefficient, s1 represents the first energy supply data, s2 represents the second energy supply data, and s3 represents the third energy supply data.

4. The highly efficient odor-removing food waste processor according to claim 3, characterized in that: When the processing unit calculates the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool rotation speed and the historical energy supply record, it includes: The processing unit constructs a historical energy supply curve, the historical energy supply curve includes a plurality of groups to be analyzed, each of the groups to be analyzed includes a historical initial tool speed and corresponding historical initial load data, and the number of the groups to be analyzed is the same as the historical energy supply record; The processing unit arbitrarily extracts two of the groups to be analyzed to obtain the first historical initial load data, the second historical initial load data, the first historical initial tool speed, and the second historical initial tool speed; Calculate the load difference between the first historical initial load data and the second historical initial load data, record the absolute value of the load difference as the first load difference, extract the maximum historical initial load data and the minimum historical initial load data from all the groups to be analyzed, calculate the difference between the maximum historical initial load data and the minimum historical initial load data, record it as the maximum load difference; calculate the difference between the maximum load difference and the first load difference, record it as the absolute value of the load; Calculate the speed difference between the first historical initial tool speed and the second historical initial tool speed, record the absolute value of the speed difference as the first speed difference, extract the maximum historical initial tool speed and the minimum historical initial tool speed from all the groups to be analyzed, calculate the difference between the maximum historical initial tool speed and the minimum historical initial tool speed, record it as the maximum speed difference; calculate the difference between the maximum speed difference and the first speed difference, record it as the absolute value of the speed; The product of the absolute value of the load and the absolute value of the speed is used as the sub-energy supply deviation coefficient of the energy supply module, the sub-energy supply deviation coefficients corresponding to each two remaining groups to be analyzed are calculated, and the second historical energy supply deviation coefficient is obtained according to all the sub-energy supply deviation coefficients.

5. The highly efficient odor-removing food waste processor according to claim 4, characterized in that: When the processing unit obtains the second historical energy supply deviation coefficient according to all the sub-energy supply deviation coefficients, it includes: The processing unit obtains a sub-energy supply deviation coefficient mean value according to all the sub-energy supply deviation coefficients, classifies all sub-energy supply deviation coefficients that are less than or equal to the sub-energy supply deviation coefficient mean value into a first sub-energy supply deviation set; and classifies all sub-energy supply deviation coefficients that are greater than the sub-energy supply deviation coefficient mean value into a second sub-energy supply deviation set; The processing unit calculates a first energy supply deviation coefficient difference between each of the sub-energy supply deviation coefficients in the first sub-energy supply deviation set and an average of the sub-energy supply deviation coefficients, and establishes a first energy supply deviation coefficient difference set based on all of the first energy supply deviation coefficient differences; calculates a second energy supply deviation coefficient difference between each of the sub-energy supply deviation coefficients in the second sub-energy supply deviation set and an average of the sub-energy supply deviation coefficients, and establishes a second energy supply deviation coefficient difference set based on all of the second energy supply deviation coefficient differences; The processing unit randomly combines first energy supply deviation coefficient differences in the first energy supply deviation coefficient difference set with second energy supply deviation coefficient differences in the second energy supply deviation coefficient difference set in pairs to obtain a plurality of sub-energy supply deviation coefficient difference sets; The processing unit obtains a second historical energy supply deviation coefficient of the energy supply module according to all the sub-energy supply deviation coefficient difference sets.

6. The highly efficient odor-removing food waste processor according to claim 5, characterized in that: When the processing unit obtains the second historical energy supply deviation coefficient of the energy supply module according to all the sub-energy supply deviation coefficient difference sets, it includes: Among them, y2 represents the second historical energy supply deviation coefficient, n represents the number of sub-energy supply deviation coefficient difference sets, c1 i represents the first energy supply deviation coefficient difference in the i-th sub-energy supply deviation coefficient difference set, c2 i is the second energy supply deviation coefficient difference in the ith sub-energy supply deviation coefficient difference set, ((c1i-c2i) 2 )min for all (c1i-c2i) 2 The minimum value among ((c1i-c2i) 2 )max is all (c1i-c2i) 2 The maximum value in Δs 2 For all (c1 i -c2 i ) 2 The variance of .

7. The highly efficient odor-removing food waste processor according to claim 6, characterized in that: When the processing unit calculates the comprehensive historical deviation coefficient of the energy supply module based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient, it includes: Y = a1 × y1 + a2 × y2; Among them, Y represents the comprehensive historical deviation coefficient, y1 represents the first historical energy supply deviation coefficient, y2 represents the second historical energy supply deviation coefficient, a1 and a2 are weight coefficients, and a1+a2=1, a1>a2.

8. The highly efficient odor-removing food waste processor according to claim 7, characterized in that: When the adjustment unit determines the energy supply adjustment coefficient according to the comparison result to adjust the initial tool rotation speed, it includes: When there is data in the historical adjustment scheme that the historical comprehensive historical deviation coefficient is the same as the comprehensive historical deviation coefficient, the adjustment unit uses the historical adjustment coefficient as the adjustment coefficient, obtains the product of the adjustment coefficient and the initial tool speed, and obtains the adjusted tool speed; When all the historical comprehensive historical deviation coefficients in the historical adjustment scheme are different from the comprehensive historical deviation coefficient, the adjustment unit selects the historical comprehensive historical deviation coefficients in the historical adjustment scheme whose differences with the comprehensive deviation coefficient are within the range of b% as an approximate set, and determines the adjustment coefficient according to the historical adjustment coefficients corresponding to the historical comprehensive historical deviation coefficients in the approximate set to adjust the initial tool speed.

9. The highly efficient odor-removing food waste processor according to claim 8, characterized in that: When the adjustment unit determines the adjustment coefficient to adjust the initial tool rotation speed according to the historical adjustment coefficient corresponding to the historical comprehensive historical deviation coefficient in the approximate set, it includes: Among them, T represents the adjustment coefficient, Tj represents the jth historical comprehensive historical deviation coefficient in the approximate set, T0 represents the mean of the historical comprehensive historical deviation coefficients in the approximate set, and M represents the number of historical comprehensive historical deviation coefficients in the approximate set.

10. A control method for a highly efficient odor-removing food waste disposer, applied to the highly efficient odor-removing food waste disposer as claimed in any one of claims 1 to 9, characterized in that: include: Collecting waste material quality data, and determining a corresponding initial tool speed in a preset corresponding table according to the waste material quality data, wherein the corresponding table includes a mapping relationship between the waste material quality data and the corresponding initial tool speed; Collecting multiple historical energy supply records of the energy supply module, parsing the historical energy supply records, and dividing the historical energy supply records into historical high abnormal energy supply records, historical normal energy supply records, and historical low abnormal energy supply records based on the parsing results; The first historical energy supply deviation coefficient of the energy supply module is calculated according to the historical high abnormal energy supply record, the historical normal energy supply record and the historical low abnormal energy supply record; the processing unit is also configured to collect the historical initial tool speed corresponding to each historical energy supply record, and calculate the second historical energy supply deviation coefficient of the energy supply module according to the historical initial tool speed and the historical energy supply record; the comprehensive historical deviation coefficient of the energy supply module is calculated based on the first historical energy supply deviation coefficient and the second historical energy supply deviation coefficient; The comprehensive historical deviation coefficient is compared with the historical adjustment plan, and the energy supply adjustment coefficient is determined according to the comparison result to adjust the initial tool speed, and the energy supply module is controlled to operate at the adjusted tool speed, wherein the historical adjustment plan includes the historical comprehensive historical deviation coefficient and the corresponding historical adjustment coefficient.

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