Intelligent control system and method of shared washing machine

Abstract

The invention relates to the technical field of washing machine control, in particular to an intelligent control system and method for shared washing machines. The use intensity indexes of the washing machines are obtained by analyzing the use states of the washing machines, and whether the washing machines need to be intelligently shared and regulated or not is judged accordingly, so that the washing machines are prevented from being in an idle or overloaded state; the operation parameters of the washing machine are monitored in real time, the operation state of the washing machine is monitored and analyzed accordingly, the health state of the washing machine can be comprehensively known, and data support is provided for precise regulation and control of the washing machine; the sorting values are obtained by comprehensively analyzing the number of the cleaning tasks, the risk indexes, the spacing distances and the cleaning efficiency values, the washing machines are sorted and displayed according to the sequence of the corresponding sorting values from large to small, personalized washing machine selection suggestions are provided for each user, the satisfaction degree and the use experience of the user are improved, and the user experience is improved. Cleaning efficiency of the washing machine is improved, and waiting time of users is shortened.

Description

Technical Field

[0001] The present invention relates to the technical field of washing machine control, and specifically to an intelligent control system and method for shared washing machines. Background Art

[0002] Due to the modern fast-paced life and the fact that hand-washing clothes is time-consuming and laborious, washing machines have become a necessity for modern people; the placement of shared washing machines in public places not only solves the problem of washing machine storage but also reduces the economic burden on students and residents in other public places (such as schools, staff dormitories, etc.) for personal purchase and maintenance of washing machines. In addition, shared washing machines are usually charged per use, and users can pay as needed without having to bear the high purchase cost of washing machines, which conforms to the flexible and economical consumption concept of modern people;

[0003] At present, due to the high-frequency use of some washing machines for a long time, the wear is aggravated, and long-term overloading or uneven use easily leads to frequent failures of key components of the equipment (such as motors, drainage systems, etc.). Washing machines with a higher usage frequency will have large differences in washing effects due to equipment aging, reduced cleaning power, or program failures; when washing clothes, users have to find idle washing machines by themselves or queue up to wash clothes. Washing machines with a high usage rate will be selected more frequently, while less-used equipment will be idle. Over time, this will further exacerbate the uneven wear of the equipment, affect the reasonable allocation of the entire shared laundry resources, and reduce the efficiency of the washing machines. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent control system and method for shared washing machines to solve the problems mentioned in the above background art.

[0005] According to one aspect of the present application, an intelligent control system for shared washing machines is provided, including: a user terminal and a washing machine sharing platform; wherein the washing machine sharing platform includes: a server, a demand analysis module, a monitoring and analysis module, and an intelligent control module;

[0006] The server is communicatively connected to the shared washing machines and various types of sensors mounted on the shared washing machines to collect the operating parameters of the washing machines in real time. The specific operating parameters include the vibration amplitude, noise value, voltage, and load of the washing machines;

[0007] The demand analysis module analyzes based on the usage status of each washing machine to determine whether intelligent sharing control of the washing machine is required. If so, a regulation instruction is generated and sent to the monitoring and analysis module;

[0008] The monitoring and analysis module monitors and analyzes the operating status of the washing machine based on the received regulation instruction to determine the operating status of the washing machine, and accordingly obtains a risk index; the risk index is sent to the intelligent control module;

[0009] The intelligent control module conducts intelligent regulation on the cleaning tasks of each washing machine based on the received risk coefficient. The specific steps are as follows:

[0010] Step 1: Mark the numbers and locations of each washing machine on the park map, send a location acquisition instruction to the user terminal to obtain the real-time location of the user, and calculate the interval distance between the user and each washing machine in the park, denoted as H1;

[0011] Step 2: Set each washing machine to correspond to a cleaning efficiency value, extract the washing machine number, and compare it with all the set washing machine numbers respectively to match the corresponding cleaning efficiency value, denoted as Ra; obtain the number of cleaning tasks of the washing machine in real time and denote it as H2; normalize the risk index VB, the interval distance H1, the cleaning efficiency value Ra, and the number of cleaning tasks H2 and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain the sorting value RH. The specific calculation formula is:

[0012]

[0013] where γ1, γ2, γ3, and γ4 are respectively the set weight constants; thus, the sorting values between the user and each washing machine in the park can be obtained. When the user logs in and submits a cleaning task, the washing machines are sorted in descending order according to their corresponding sorting values and displayed for the user to select. At the same time, the user can view the number of cleaning tasks of each washing machine in real time; when the user selects one of the washing machines, the number of cleaning tasks of that washing machine increases by one, and that washing machine is marked as the target washing machine of the user terminal;

[0014] Step 3: Whenever a washing machine completes a cleaning task, the number of cleaning tasks in the task list of the corresponding washing machine decreases by one, and a cleaning record is formed. The specific cleaning record includes the cleaning start time, the cleaning end time, and the cleaning weight; every time a cleaning task is completed, cleaning cumulative analysis is performed to obtain the cleaning efficiency value, the number of cleaning tasks and the cleaning efficiency value of each washing machine are updated in real time, and they are sent to Step 2;

[0015] Step 4: Retrieve the distance between each user terminal and the target washing machine, multiply it by the set serial number coefficient to obtain the reminder serial number, extract the serial number of the cleaning task of the user terminal in the task list, and if it is less than the reminder serial number value, then integrate the task list of the target washing machine into a cleaning reminder and send it to the user terminal;

[0016] Step 5: Repeat the above steps until all the cleaning tasks in the task list of the washing machine are completed.

[0017] Preferably, the specific steps of the cleaning cumulative analysis are as follows:

[0018] Retrieve the historical cleaning records of the washing machine, as well as the cleaning start time, cleaning end time, and cleaning weight corresponding to each record. Calculate the time difference between the cleaning start time and the cleaning end time to obtain the cleaning duration. Thus, the cleaning duration and cleaning weight corresponding to each cleaning record can be obtained, and they are denoted as Q1 and Q2 respectively. Normalize the cleaning duration Q1 and the cleaning weight Q2 and take their numerical values, and perform a formula-based calculation on the numerical values to obtain the cleaning value Qb corresponding to each cleaning record. The specific calculation formula is:

[0019]

[0020] where b1 and b2 are respectively set weight constants;

[0021] Compare and analyze the cleaning value with the set cleaning range. When the cleaning value is greater than the upper limit of the set cleaning range, count one high-efficiency cleaning; when the cleaning value is within the set cleaning range, count one medium-efficiency cleaning; when the cleaning value is less than the lower limit of the set cleaning range, count one low-efficiency cleaning. Respectively count the cumulative times of high-efficiency cleaning, medium-efficiency cleaning, and low-efficiency cleaning;

[0022] Calculate the mean value of the cleaning values corresponding to each cleaning record to obtain the cleaning mean value denoted as And perform a numerical calculation and analysis on it with the cumulative number R1 of high-efficiency cleaning, the cumulative number R2 of medium-efficiency cleaning, and the cumulative number R3 of low-efficiency cleaning to obtain the cleaning efficiency value Ra. The specific calculation formula is:

[0023]

[0024] where a1, a2, and a3 are respectively set weight constants, and a1 > a2 > a3 > 1.

[0025] Preferably, the specific process of analyzing and judging based on the usage status of each washing machine is as follows:

[0026] Retrieve the load and the number of cleaning tasks in the task list of the washing machine at each collection moment, and denote them as Fj and Nj respectively; where j = 1, 2, 3... J, J belongs to positive integers, J represents the total number of collection moments, and j represents the number of any one collection moment. Normalize the load Fj and the number of cleaning tasks Nj in the task list and take their numerical values, and perform a formula-based calculation and analysis on the numerical values to obtain the usage value FNj at each collection moment. The specific calculation formula is:

[0027] FNj = c1 × Fj + c2 × Nj

[0028] where c1 and c2 are respectively set weight coefficients;

[0029] Construct a two-dimensional rectangular coordinate system with time as the abscissa and usage value as the ordinate. Input the usage values into the coordinate axes according to the corresponding acquisition times, and mark the positions of the usage values in the coordinate axes as usage points. Connect the usage points in sequence with line segments to obtain a usage value change line graph. Perform image analysis on the usage value change line graph to obtain the usage intensity index of the washing machine;

[0030] Compare and analyze the intensity intervals set for the usage intensity indexes of each washing machine. If the usage intensity value is greater than the upper limit of the set intensity interval, then mark the washing machine corresponding to the usage intensity value as a high-intensity washing machine; if the usage intensity value is within the set intensity interval, then mark the washing machine corresponding to the usage intensity value as a medium-intensity washing machine; if the usage intensity value is less than the lower limit of the set intensity interval, then mark the washing machine corresponding to the usage intensity value as a low-intensity washing machine. Count the numbers of high-intensity washing machines, medium-intensity washing machines, and low-intensity washing machines respectively, and record them as M1, M2, and M3; respectively. If M3≥M1+M2, there is no need for intelligent regulation; otherwise, generate an intelligent regulation instruction to the monitoring and analysis module.

[0031] Preferably, the specific process of performing image analysis on the usage value change line graph is as follows:

[0032] Retrieve the usage value change line graph, and mark the line segment formed by two adjacent usage points as Use data fitting to calculate the slope of the line segment. Draw perpendicular lines from the two endpoints of each line segment to the horizontal axis and intersect with the horizontal axis. Thus, the enclosed area formed by the line segment, the perpendicular lines of the two endpoints, and the horizontal axis is marked as Sum the slopes greater than zero to obtain the usage increase degree and record it as Y1, and sum the slopes less than zero and then take the absolute value to calculate the usage decrease degree and record it as Y2;

[0033] Perform normalization processing on the usage increase degree Y1, the usage decrease degree Y2, and the enclosed area Take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain the usage intensity index SY of the washing machine; the specific calculation formula is:

[0034]

[0035] where c3 and c4 are respectively set weight constants, and the specific values are set by those skilled in the art according to the specific details of the washing machine.

[0036] Preferably, monitor and analyze the operating state of the washing machine to judge the operating state of the washing machine. The specific monitoring and analysis process is as follows:

[0037] Retrieve the operating parameters of the washing machine at each acquisition moment. The specific operating parameters include the vibration amplitude, noise value, voltage, and load of the washing machine, and record them as Dj, Zj, Vj, and Fj respectively; normalize the vibration amplitude Dj, noise value Zj, and load Fj and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain the operating value DFj of the washing machine at each acquisition moment; the specific calculation formula is:

[0038]

[0039] where β1, β2, and β3 are respectively set weight constants;

[0040] Construct a two-dimensional rectangular coordinate system with time as the abscissa and the operating value as the ordinate. Input the operating value into the coordinate axis according to its corresponding acquisition moment, and record the position of the operating value in the coordinate axis as the operating point. Connect each operating point in sequence with a smooth curve to obtain the operating value change curve graph; analyze the change trend of the operating value based on the operating value change curve graph to obtain the risk index; thus, the risk index of each washing machine can be obtained and sent to the intelligent control module.

[0041] Preferably, the specific process of analyzing the change trend of the operating value based on the operating value change curve graph is as follows:

[0042] At each operating point, make a curve tangent line, use data fitting to calculate the tangent line expression, and perform derivative calculation on the tangent line expression to obtain the operating derivative, denoted as Bj; sum the operating derivatives greater than zero to obtain the operating increase, denoted as Y3, and sum the operating derivatives less than zero and then take the absolute value to calculate the operating decrease, denoted as Y4;

[0043] Normalize and take the numerical values of the voltage Vj, operating value DFj, operating derivative Bj, operating increase Y3, and operating decrease Y4 at each acquisition moment, and perform formula-based calculation on the numerical values to obtain the risk index VB; the specific calculation formula is:

[0044] where α1, α2, α3, and α4 are respectively set weight constants, is the average voltage value at each acquisition moment, is the average value of each operating derivative.

[0045] According to another aspect of the present application, an intelligent control method for shared washing machines is provided, including the following steps:

[0046] Step1: Analyze based on the usage status of each washing machine to determine whether intelligent shared control of the washing machine is required. If so, generate a regulation instruction and send it to Step2;

[0047] Step 2: Monitor and analyze the operating status of the washing machine based on the received control instructions to determine the operating status of the washing machine, and obtain a risk index accordingly; send the risk index to Step 3;

[0048] Step 3: Intelligently control the cleaning tasks of each washing machine based on the received risk coefficient. The specific steps are as follows:

[0049] Step 1: Mark the numbers and locations of each washing machine on the park map, send a location acquisition instruction to the user terminal to obtain the user's real-time location, and calculate the interval distance between the user and each washing machine in the park, denoted as H1;

[0050] Step 2: Set a cleaning efficiency value for each washing machine respectively, extract the washing machine number, and compare it with all the set washing machine numbers respectively to match the corresponding cleaning efficiency value, denoted as Ra; obtain the number of cleaning tasks of the washing machine in real-time and denote it as H2; normalize the risk index VB, interval distance H1, cleaning efficiency value Ra, and number of cleaning tasks H2 and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain a sorting value RH. The specific calculation formula is:

[0051]

[0052] where γ1, γ2, γ3, and γ4 are respectively set weight constants; thus, the sorting values between the user and each washing machine in the park can be obtained. When the user logs in and submits a cleaning task, the washing machines are sorted in descending order according to their corresponding sorting values and displayed for the user to select. At the same time, the user can view the number of cleaning tasks of each washing machine in real-time; when the user selects one of the washing machines, the number of cleaning tasks of that washing machine increases by one, and that washing machine is marked as the target washing machine of the user terminal;

[0053] Step 3: Whenever a washing machine completes a cleaning task, the number of cleaning tasks in the corresponding washing machine's task list decreases by one, and a cleaning record is formed. The specific cleaning record includes the cleaning start time, cleaning end time, and cleaning weight; every time a cleaning task is completed, cleaning cumulative analysis is performed to obtain the cleaning efficiency value, and the number of cleaning tasks and cleaning efficiency value of each washing machine are updated in real-time and sent to Step 2;

[0054] Step 4: Retrieve the distance between each user terminal and the target washing machine, multiply it by the set serial number coefficient to obtain a reminder serial number, extract the serial number of the user terminal's cleaning task in the task list, and if it is less than the reminder serial number value, then integrate the task list of the target washing machine into a cleaning reminder and send it to the user terminal;

[0055] Step Five: Repeat the above steps until all the cleaning tasks in the washing machine's task list are completed.

[0056] Advantages of the present invention:

[0057] 1. By analyzing the usage status of the washing machine to obtain the usage intensity index of each washing machine, and based on this, determining whether intelligent sharing regulation of the washing machine is required to avoid the washing machine being in an idle or overloaded state;

[0058] 2. By real-time monitoring the operating parameters of the washing machine, and based on this, monitoring and analyzing the operating state of the washing machine, which helps to comprehensively understand the health state of the washing machine and provides data support for realizing the precise regulation of the washing machine;

[0059] 3. By comprehensively analyzing the number of cleaning tasks, risk index, interval distance, and cleaning efficiency value to obtain a sorting value, and sorting and displaying each washing machine in descending order according to its corresponding sorting value for the user to select; providing personalized washing machine selection suggestions for each user, which helps to improve the user's satisfaction and usage experience, improve the cleaning efficiency of the washing machine, and reduce the user's waiting time;

[0060] 4. By real-time updating the number of cleaning tasks and cleaning efficiency value, the sorting of each washing machine can be dynamically adjusted, which is convenient for the user to select the most suitable washing machine for themselves, so that the washing machine can maximize the cleaning efficiency without causing overloading. After each cleaning is completed, the reduction of the task number and the recalculation of the cleaning efficiency enable the system to respond to load changes in a timely manner. Brief Description of the Drawings

[0061] Figure 1 is a schematic diagram of the system module connection of the present invention;

[0062] Figure 2 is a line graph of the change of usage value of the present invention;

[0063] Figure 3 is a schematic diagram of the method flow of the present invention. Detailed Embodiments

[0064] In order to make the purpose and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principle of the present invention and do not limit the protection scope of the present invention.

[0066] It should be noted that in the description of the present invention, the terms indicating directions or positional relationships such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0067] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and defined, the terms "installed", "connected", "connected to" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0068] Please refer to Figure 1 As shown, the present invention is an intelligent control system for a shared washing machine, including: a user terminal and a washing machine sharing platform, and the user terminal and the washing machine sharing platform are communicatively connected; wherein the washing machine sharing platform includes a server, a demand analysis module, a monitoring and analysis module, and an intelligent control module;

[0069] It should be noted that the usage scenario of the present invention is a large public living place, such as a comprehensive university campus. Since there are many dormitory areas and a large number of students on campus, and the space of each dormitory room is limited, the shared washing machines are widely placed in each building of each dormitory area so that users can use the shared washing machines to wash clothes;

[0070] The server is communicatively connected to the shared washing machine and various types of sensors carried on the shared washing machine to collect the operating parameters of the washing machine in real time and save them;

[0071] The demand analysis module judges whether intelligent sharing control of the washing machine is required based on the usage status of each washing machine. If so, a regulation instruction is generated and sent to the monitoring and analysis module; specifically:

[0072] Retrieve the load of the washing machine and the number of washing tasks in the task list at each collection moment, and record them as Fj and Nj respectively; where j = 1, 2, 3... J, J belongs to positive integers, J represents the total number of collection moments, and j represents the number of any one collection moment; normalize the load Fj and the number of washing tasks Nj in the task list and take their values, and perform formula-based calculation and analysis on the values to obtain the usage value FNj at each collection moment; the specific calculation formula is:

[0073] FNj = c1×Fj + c2×Nj

[0074] Where c1 and c2 are respectively set weight coefficients. Sometimes the washing machine is in the cleaning state, sometimes it is in the barrel self-cleaning state after the cleaning is completed (usually, a shared washing machine will perform a barrel self-cleaning after each cleaning to disinfect and sterilize to prevent cross-infection), and sometimes the washing machine is in the standby state (idle state). Therefore, the load of the washing machine at different acquisition times will be different. It should be noted that a high load will increase the cleaning time and the usage intensity of the device. Therefore, the greater the load of the washing machine, the greater the usage value of the washing machine. The greater the number of cleaning tasks in the task list, the busier the laundry, and the greater the usage value of the washing machine.

[0075] As Figure 2 shown, a two-dimensional rectangular coordinate system is constructed with time as the abscissa and the usage value as the ordinate. The usage value is input into the coordinate axis according to the corresponding acquisition time, and the position of the usage value in the coordinate axis is marked as the usage point. The usage value change line graph is obtained by connecting each usage point with a line segment in turn; the line segment formed by two adjacent usage points is denoted as The slope of the line segment is calculated by data fitting. Perpendiculars are drawn from the two endpoints of each line segment to the horizontal axis and intersect with the horizontal axis. Thus, the enclosed area formed by the line segment, the perpendiculars of the two endpoints, and the horizontal axis is denoted as It should be noted that the greater the enclosed area, the greater the usage value of the washing machine. The sum of the slopes greater than zero is calculated to obtain the usage increase degree denoted as Y1, and the sum of the slopes less than zero is calculated and the absolute value is taken to obtain the usage decrease degree denoted as Y2.

[0076] The usage increase degree Y1, the usage decrease degree Y2, and the enclosed area are normalized and their numerical values are taken. The numerical values are calculated and analyzed formulaically to obtain the usage intensity index SY of the washing machine. The specific calculation formula is:

[0077]

[0078] Among them, c3 and c4 are respectively set weight constants, and the specific values are set by those skilled in the art according to the specific details of the washing machine; for example, the value of c3 is 1.629 and the value of c4 is 1.538; thus, the usage intensity values of each washing machine can be obtained, and they are compared and analyzed with the set intensity range. If the usage intensity value is greater than the upper limit of the set intensity range, the washing machine corresponding to this usage intensity value is recorded as a high-intensity washing machine; if the usage intensity value is within the set intensity range, the washing machine corresponding to this usage intensity value is recorded as a medium-intensity washing machine; if the usage intensity value is less than the lower limit of the set intensity range, the washing machine corresponding to this usage intensity value is recorded as a low-intensity washing machine; the numbers of high-intensity washing machines, medium-intensity washing machines, and low-intensity washing machines are respectively counted and recorded as M1, M2, and M3; if M3≥M1+M2, it means that the busy degree of most washing machines is not high and no intelligent regulation is required; otherwise, it means that the busy degree of some washing machines is relatively large and intelligent regulation is required to enable the washing machine to meet the current cleaning task and improve the cleaning efficiency, and then an intelligent regulation instruction is generated to the monitoring and analysis module;

[0079] By analyzing the usage status of the washing machine to obtain the usage intensity index of each washing machine, and based on this, it is judged whether intelligent sharing regulation of the washing machine is required to avoid the washing machine being in an idle or overloaded state.

[0080] The monitoring and analysis module monitors and analyzes the operating status of the washing machine based on the received regulation instruction to judge the operating status of the washing machine, and based on this, obtains a risk index; specifically:

[0081] Retrieve the operating parameters of the washing machine at each acquisition moment. The specific operating parameters include the vibration amplitude, noise value, voltage, and load of the washing machine, and they are respectively recorded as Dj, Zj, Vj, and Fj; normalize the vibration amplitude Dj, noise value Zj, and load Fj and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain the operating value DFj of the washing machine at each acquisition moment; the specific calculation formula is:

[0082]

[0083] Among them, β1, β2, and β3 are respectively set weight constants. It should be noted that when the vibration amplitude of the washing machine is larger, it means that the possibility of the washing machine having a fault or component wear is greater. For example, drum imbalance, bearing problems, or uneven loading, etc. More frequent abnormal vibrations will directly affect the life of the equipment; normally, the larger the noise value of the washing machine, it may be because of component damage, looseness, or the presence of accumulated water or dirt inside the equipment, which may increase the risk of equipment failure; if the voltage fluctuates too much, it may be that the motor or other key components have failed or the load is uneven, affecting the equipment performance, indicating an increase in the fault risk of the washing machine;

[0084] Taking time as the abscissa and the running value as the ordinate, a two-dimensional rectangular coordinate system is constructed. The running value is input into the coordinate axis according to its corresponding acquisition time, and the position of the running value in the coordinate axis is recorded as the running point. A smooth curve is used to connect each running point in turn to obtain the running value change curve graph; at each running point, a curve tangent is made, and the tangent expression is calculated by data fitting. The derivative of the tangent expression is calculated to obtain the running derivative denoted as Bj. It should be noted that when the running derivative is greater than zero, it indicates that the running value shows an increasing trend; when the running derivative is less than zero, it indicates that the running value shows a decreasing trend; the sum of the running derivatives greater than zero is calculated to obtain the running increase degree denoted as Y3, and the sum of the running derivatives less than zero is taken and the absolute value is calculated to obtain the running decrease degree denoted as Y4;

[0085] The voltage Vj, running value DFj, running derivative Bj, running increase degree Y3, and running decrease degree Y4 at each acquisition time are normalized and their numerical values are taken. The numerical values are calculated by a formula to obtain the risk index VB; the specific calculation formula is:

[0086] where α1, α2, α3, and α4 are respectively set weight constants, is the average voltage at each acquisition time, is the average value of each running derivative; it should be noted that the greater the voltage fluctuation, the lower the health status of the washing machine, and the greater the risk index; the greater the increasing trend of the running value and the smaller the decreasing trend, the greater the risk index; the more unstable the running derivative, the more unstable the state of the washing machine, and the greater the risk index; the greater the running value, the greater the risk index; thus, the risk index of each washing machine can be obtained and sent to the intelligent control module;

[0087] By real-time monitoring the operating parameters of the washing machine and analyzing the operating state of the washing machine accordingly, it helps to comprehensively understand the health status of the washing machine and provides data support for realizing the precise control of the washing machine.

[0088] The intelligent control module intelligently regulates the cleaning tasks of each washing machine based on the received risk coefficient to maximize the cleaning efficiency of the washing machine and improve the user experience while ensuring the safe operation of the washing machine; the specific steps are as follows:

[0089] Step 1: Mark the numbers and positions of each washing machine on the park map, send a position acquisition instruction to the user terminal to obtain the real-time position of the user, and calculate the interval distance between the user and each washing machine in the park denoted as H1;

[0090] Step 2: Set a cleaning efficiency value for each washing machine, extract the washing machine number, and compare it with all the set washing machine numbers to match the corresponding cleaning efficiency value, recorded as Ra; obtain the number of cleaning tasks of the washing machine in real time, and record it as H2; normalize the risk index VB, the interval distance H1, the cleaning efficiency value Ra and the number of cleaning tasks H2 and take their values, and perform formula calculation and analysis on the values to obtain the ranking value RH. The specific calculation formula is:

[0091]

[0092] Among them, γ1, γ2, γ3, and γ4 are the set weight constants respectively; thus, the ranking values between the user and the washing machines in the park can be obtained. When the user logs in and submits a cleaning task, the washing machines are sorted and displayed in descending order according to their corresponding ranking values for the user to choose. At the same time, the user can view the number of cleaning tasks for each washing machine in real time; when the user selects one of the washing machines, the number of cleaning tasks for the washing machine increases by one, and the washing machine is marked as the target washing machine on the user side; the cleaning tasks in the task list of the washing machine are sorted according to the submission time of each user. The earlier the specific submission time, the higher the corresponding ranking. First; extract the serial number of the cleaning task submitted by the user through the user terminal in the cleaning task, and use it as the cleaning number of the user terminal; thus, the cleaning number of the cleaning task submitted by each user terminal can be obtained, and it is sent to the corresponding user terminal; the specific washing machine cleaning number update is accumulated on a daily basis, and the cleaning number is reset on the second day; for example, on September 2, 2024, the washing machine has completed 10 cleaning tasks, and there are still 4 cleaning tasks to be cleaned in the washing machine task list. The cleaning number of the first cleaning task to be cleaned in the washing machine task list is 11, and the others are analogous; on September 3, 2024, it will be reset and the accumulation will start again;

[0093] Step 3: Whenever the washing machine completes a cleaning task, the number of cleaning tasks in the task list of the corresponding washing machine is reduced by one, and a cleaning record is formed. The specific cleaning record includes the cleaning start time, cleaning end time and cleaning weight; each time a cleaning task is completed, a cleaning cumulative analysis is performed to obtain a cleaning efficiency value, which is specifically:

[0094] Retrieve the historical cleaning records of the washing machine, as well as the corresponding cleaning start time, cleaning end time, and cleaning weight for each record. Calculate the time difference between the cleaning start time and the cleaning end time to obtain the cleaning duration. Thus, the cleaning duration and cleaning weight corresponding to each cleaning record can be obtained, and they are respectively denoted as Q1 and Q2. Normalize the cleaning duration Q1 and the cleaning weight Q2 and take their numerical values, and perform a formula-based calculation on the numerical values to obtain the cleaning value Qb corresponding to each cleaning record. The specific calculation formula is:

[0095]

[0096] where b1 and b2 are respectively set weight constants. It can be seen from the formula that when the cleaning weight is heavier and the cleaning time is shorter, it means that the efficiency of this cleaning is higher, and the corresponding cleaning value is larger. Compare and analyze the cleaning value with the set cleaning range. When the cleaning value is greater than the upper limit of the set cleaning range, count one high-efficiency cleaning. When the cleaning value is within the set cleaning range, count one medium-efficiency cleaning. When the cleaning value is less than the lower limit of the set cleaning range, count one low-efficiency cleaning. Respectively count the cumulative times of high-efficiency cleaning, medium-efficiency cleaning, and low-efficiency cleaning, and denote them as R1, R2, and R3 respectively;

[0097] Calculate the mean value of the cleaning values corresponding to each cleaning record to obtain the cleaning mean value denoted as and perform a numerical calculation and analysis on it with the cumulative number R1 of high-efficiency cleaning, the cumulative number R2 of medium-efficiency cleaning, and the cumulative number R3 of low-efficiency cleaning to obtain the cleaning efficiency value Ra. The specific calculation formula is:

[0098]

[0099] where a1, a2, and a3 are respectively set weight constants, and a1 > a2 > a3 > 1. Real-time update the cleaning task quantity and cleaning efficiency value of each washing machine, and send them to step two;

[0100] Step four: Retrieve the distance between each client and the target washing machine, and multiply it by the set serial number coefficient (the specific value of the serial number coefficient is set by the personnel in this field according to actual needs) to obtain the reminder serial number. Extract the serial number of the cleaning task of the client in the task list. If it is less than the reminder serial number value, then integrate the task list of the target washing machine into a cleaning reminder and send it to the client to facilitate timely reminding the user to wash clothes and prevent the user from missing the queue. For example, the distance between the client and the target washing machine is 100m, and the serial number coefficient is 0.02, then the reminder serial number value is 5. Therefore, when the serial number of the user's cleaning task (i.e., the sorting number of the user's cleaning task in the task list of the target washing machine) is less than 5, then integrate the task list of the target washing machine into a cleaning reminder and send it to the client;

[0101] Step 5: Repeat the above steps until all the cleaning tasks in the washing machine's task list are completed;

[0102] By comprehensively analyzing the number of cleaning tasks, risk index, interval distance, and cleaning efficiency value, a sorting value is obtained. The washing machines are sorted in descending order according to their corresponding sorting values and displayed for the user to select; providing personalized washing machine selection suggestions for each user helps improve user satisfaction and usage experience, increases the cleaning efficiency of the washing machine, and reduces the user's waiting time; at the same time, by real-time updating the number of cleaning tasks and cleaning efficiency value, the sorting of each washing machine can be dynamically adjusted, facilitating the user to choose the most suitable washing machine for themselves, maximizing the cleaning efficiency of the washing machine without causing excessive load. After each cleaning is completed, the reduction of the task quantity and the recalculation of the cleaning efficiency enable the system to promptly respond to load changes.

[0103] Please refer to Figure 3 As shown in the figure, the present invention is an intelligent control method for a shared washing machine, including the following steps:

[0104] Step 1: Analyze based on the usage status of each washing machine to determine whether intelligent sharing control of the washing machine is required. If so, generate a regulation instruction and send it to Step 2;

[0105] Step 2: Monitor and analyze the operating status of the washing machine based on the received regulation instruction to determine the operating status of the washing machine, and obtain a risk index accordingly; send the risk index to Step 3;

[0106] Step 3: Intelligently regulate the cleaning tasks of each washing machine based on the received risk coefficient. The specific steps are as follows:

[0107] Step 1: Mark the numbers and locations of each washing machine on the park map, send a location acquisition instruction to the user terminal to obtain the user's real-time location, and calculate the interval distance between the user and each washing machine in the park and record it as H1;

[0108] Step 2: Set each washing machine to correspond to a cleaning efficiency value, extract the washing machine number, and compare it with all the set washing machine numbers respectively to match the corresponding cleaning efficiency value and record it as Ra; obtain the number of cleaning tasks of the washing machine in real-time and record it as H2; normalize the risk index VB, interval distance H1, cleaning efficiency value Ra, and number of cleaning tasks H2 and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain a sorting value RH. The specific calculation formula is:

[0109]

[0110] where γ1, γ2, γ3, and γ4 are respectively set weight constants; thus, the sorting values between the user and each washing machine in the park can be obtained. When the user logs in and submits a cleaning task, the washing machines are sorted and displayed in descending order according to their corresponding sorting values for the user to select. At the same time, the user can view the number of cleaning tasks of each washing machine in real time. When the user selects one of the washing machines, the number of cleaning tasks of that washing machine increases by one, and that washing machine is marked as the target washing machine of the user side;

[0111] Step 3: Whenever a washing machine completes a cleaning task, the number of cleaning tasks in the task list of the corresponding washing machine decreases by one, and a cleaning record is formed. The specific cleaning record includes the cleaning start time, cleaning end time, and cleaning weight. Each time a cleaning task is completed, a cleaning cumulative analysis is performed to obtain a cleaning efficiency value, the number of cleaning tasks and the cleaning efficiency value of each washing machine are updated in real time, and they are sent to Step 2;

[0112] Step 4: Retrieve the distance between each user side and the target washing machine, multiply it by the set serial number coefficient to obtain a reminder serial number, extract the serial number of the user side's cleaning task in the task list. If it is less than the reminder serial number value, then integrate the task list of the target washing machine into a cleaning reminder and send it to the user side;

[0113] Step 5: Repeat the above steps until the cleaning tasks in the task list of the washing machine are completed.

[0114] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar methods to replace them. As long as they do not deviate from the structure of the invention or exceed the scope defined by this claims, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent control system for a shared washing machine, comprising: Client and washing machine sharing platform; characterized in that the washing machine sharing platform includes: a demand analysis module, a monitoring and analysis module, and an intelligent control module; The demand analysis module analyzes based on the usage status of each washing machine to determine whether intelligent sharing control of the washing machine is required. If so, a regulation instruction is generated and sent to the monitoring and analysis module; The monitoring and analysis module monitors and analyzes the operating status of the washing machine based on the received regulation instruction to determine the operating status of the washing machine, and obtains a risk index accordingly; the risk index is sent to the intelligent control module; The intelligent control module intelligently regulates the cleaning tasks of each washing machine based on the received risk coefficient. Specifically: mark the numbers and locations of each washing machine on the park map, send a location acquisition instruction to the client to obtain the real-time location of the user, and calculate the interval distance between the user and each washing machine in the park; extract the washing machine numbers and compare them with all the set washing machine numbers respectively to match the corresponding cleaning efficiency values; obtain the number of cleaning tasks of the washing machine in real time, and analyze it with the risk index, interval distance, and cleaning efficiency value to obtain a sorting value, and then obtain the sorting value between the user and each washing machine in the park. When the user logs in and submits a cleaning task through the client, sort each washing machine in descending order according to its corresponding sorting value and display it. At the same time, the user can view the number of cleaning tasks of each washing machine in real time; when the user selects one of the washing machines, the number of cleaning tasks of the washing machine increases by one, and the washing machine is marked as the target washing machine of the client; whenever a washing machine completes a cleaning task, the number of cleaning tasks in the task list of the corresponding washing machine decreases by one, and a cleaning record is formed; every time a cleaning task is completed, a cleaning cumulative analysis is performed to obtain a cleaning efficiency value, and the number of cleaning tasks and cleaning efficiency value of each washing machine are updated in real time; retrieve the distance between each client and the target washing machine, multiply it by the set serial number coefficient to obtain a reminder serial number, extract the serial number of the cleaning task of the client in the task list, and if it is less than the reminder serial number value, integrate the task list of the target washing machine into a cleaning reminder and send it to the client; until the cleaning tasks in the task list of the washing machine are completed.

2. The intelligent control system of a shared washing machine according to claim 1, characterized in that, The specific cleaning cumulative analysis is: retrieve the historical cleaning records of the washing machine and the corresponding cleaning start time, cleaning end time, and cleaning weight of each record, and calculate the time difference between the cleaning start time and the cleaning end time to obtain the cleaning duration; Obtain the cleaning duration and cleaning weight corresponding to each cleaning record, and calculate the cleaning value corresponding to each cleaning record; Compare and analyze the cleaning value with the set cleaning interval. When the cleaning value is greater than the upper limit of the set cleaning interval, accumulate one high-efficiency cleaning; when the cleaning value is within the set cleaning interval, accumulate one medium-efficiency cleaning; When the cleaning value is less than the lower limit of the set cleaning interval, accumulate one low-efficiency cleaning; respectively count the cumulative times of high-efficiency cleaning, medium-efficiency cleaning, and low-efficiency cleaning; Calculate the average cleaning value for each cleaning record to obtain the cleaning average, and analyze it together with the cumulative number of high-efficiency cleaning, the cumulative number of medium-efficiency cleaning, and the cumulative number of low-efficiency cleaning to obtain the cleaning efficiency value.

3. The intelligent control system of a shared washing machine according to claim 1, characterized in that, The specific process of analyzing and judging based on the usage status of each washing machine is as follows: Retrieve the load of the washing machine and the number of cleaning tasks in the task list at each collection moment, normalize them and take their numerical values, and perform formula-based calculation and analysis on the numerical values to obtain the usage value at each collection moment; Construct a two-dimensional rectangular coordinate system with time as the abscissa and the usage value as the ordinate. Input the usage value into the coordinate axis according to the corresponding collection moment, mark the position of the usage value in the coordinate axis as the usage point, and connect each usage point in sequence with line segments to obtain the usage value change line graph; perform image analysis on the usage value change line graph to obtain the usage intensity index of the washing machine; Compare and analyze the intensity intervals set for the usage intensity index of each washing machine. If the usage intensity value is greater than the upper limit of the set intensity interval, then mark the washing machine corresponding to this usage intensity value as a high-intensity washing machine; If the usage intensity value is within the set intensity interval, then mark the washing machine corresponding to this usage intensity value as a medium-intensity washing machine; If the usage intensity value is less than the lower limit of the set intensity interval, then mark the washing machine corresponding to this usage intensity value as a low-intensity washing machine; Count the numbers of high-intensity washing machines, medium-intensity washing machines, and low-intensity washing machines respectively, and record them as M1, M2, and M3; if M3≥M1 + M2, there is no need for intelligent regulation; otherwise, generate an intelligent regulation instruction to the monitoring and analysis module.

4. The intelligent control system of a shared washing machine according to claim 3, characterized in that, The specific process of performing image analysis on the usage value change line graph is as follows: Retrieve the usage value change line graph, use data fitting to calculate the slope of the line segment formed by two adjacent usage points, draw perpendicular lines from the two endpoints of each line segment perpendicular to the horizontal axis and intersect with the horizontal axis. Thus, the enclosed area formed by the line segment, the perpendicular lines of the two endpoints, and the horizontal axis can be obtained; Sum up the slopes greater than zero to obtain the usage increase degree, and sum up the slopes less than zero and then take the absolute value to calculate the usage decrease degree; Analyze the usage increase degree, the usage decrease degree, and the enclosed area to obtain the usage intensity index of the washing machine, thereby obtaining the usage intensity value of each washing machine.

5. The intelligent control system of a shared washing machine according to claim 1, characterized in that, Monitor and analyze the operating status of the washing machine to judge the operating status of the washing machine. The specific monitoring and analysis process is as follows: Retrieve the operating parameters of the washing machine at each collection moment, including the vibration amplitude, noise value, voltage, and load of the washing machine, and analyze them to obtain the operating value of the washing machine at each collection moment; Construct a two-dimensional rectangular coordinate system with time as the abscissa and the operating value as the ordinate. Input the operating value into the coordinate axis according to its corresponding collection moment, mark the position of the operating value in the coordinate axis as the operating point, and connect each operating point in sequence with a smooth curve to obtain the operating value change curve graph; analyze the change trend of the operating value based on the operating value change curve graph to obtain the risk index; thereby obtaining the risk index of each washing machine and sending it to the intelligent control module.

6. The intelligent control system of a shared washing machine according to claim 5, characterized in that, The specific process of analyzing the change trend of the operating value according to the operating value change curve is as follows: At each operating point, make a tangent to the curve, use data fitting to calculate the tangent expression, and perform a derivative calculation on the tangent expression to obtain the operating derivative; sum the operating derivatives greater than zero to obtain the operating increase, and sum the operating derivatives less than zero and then take the absolute value to calculate the operating decrease; Analyze the voltage, operating value, operating derivative, operating increase, and operating decrease at each acquisition moment to obtain the risk index.

7. An intelligent control method for a shared washing machine, characterized in that Applied to an intelligent control system of a shared washing machine as described in any one of claims 1-6, the method includes the following steps: Step1: Analyze the usage status of each washing machine to determine whether intelligent sharing control of the washing machine is required. If so, generate a regulation instruction and send it to Step2; Step2: Monitor and analyze the operating status of the washing machine based on the received regulation instruction to determine the operating status of the washing machine, and obtain the risk index accordingly; send the risk index to Step3; Step3: Intelligently regulate the cleaning tasks of each washing machine based on the received risk coefficient.

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