Motor adjusting system and method based on artificial intelligence

Abstract

The invention discloses a motor adjusting system and method based on artificial intelligence, and relates to the technical field of motor adjustment.The motor adjusting system comprises a motor monitoring module, a process monitoring module, a water tank monitoring module, a database and an adjusting module; real-time equipment data and pipeline data at the rear end of a motor are collected through the flow monitoring module, real-time water level height and water quality data of a water tank at the rear end of the motor are collected through the water tank monitoring module, and current motor use data and motor rear end equipment use data are stored through the database. The adjusting module integrates data, analyzes the requirements of the water treatment system and adjusts the state of the motor in real time, the state of the motor and the running state of the system are comprehensively considered, the RO water pump in the water treatment system is subjected to refined management, the starting and stopping frequency of the motor is effectively reduced, the linkage of the whole system is enhanced, and the service life of the system is prolonged. And the safety and the accuracy of adjusting the state of the motor are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of motor regulation, and in particular to a motor regulation system and method based on artificial intelligence. Background Art

[0002] Through artificial intelligence, a variety of equipment can be controlled on a large scale, and the data calls are basically synchronized. At the same time, with the rise of the water treatment industry in my country, the types of equipment in the water treatment system are more complex and the number is increasing. The system often uses artificial intelligence to ensure the safe and stable operation of the system through established procedures. For example, in the reverse osmosis membrane filtration part of the water treatment system, the system usually sets the start and stop of the RO water pump through the water level of the water tanks before and after the RO water pump.

[0003] Since the user's water consumption changes at any time, it is difficult to determine the water consumption rate of the RO membrane, which may cause the frequent start and stop of the motor in the RO water pump, which will cause great losses during the control period and the motor, and increase unnecessary safety risks. On the one hand, when the water treatment system sets a set program, it is difficult to take into account the condition of the water pump motor itself, and the adjustment and protection of the motor are not refined enough. On the other hand, the system often reaches the set frequency when starting the water pump motor to supply water, which may cause problems such as excessive pressure in subsequent pipelines and RO membranes. When the motor is started at a high frequency, it may also cause excessive water production in the RO part, and the water quality will be reduced due to the long-term non-circulation of filtered water in the water tank.

[0004] Therefore, people need a motor regulation system and method based on artificial intelligence to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a motor adjustment system and method based on artificial intelligence to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a motor adjustment system based on artificial intelligence, the system comprising: a motor monitoring module, a process monitoring module, a water tank monitoring module, a database and an adjustment module;

[0007] Collecting real-time motor operating status data through the motor monitoring module;

[0008] The process monitoring module collects real-time equipment data and pipeline data of the motor backend;

[0009] The water tank monitoring module collects real-time water level and water quality data of the water tank at the rear end of the motor;

[0010] The database stores current motor usage data and motor back-end device usage data;

[0011] The regulating module integrates data, analyzes water treatment system requirements, and regulates motor status in real time.

[0012] Furthermore, the motor monitoring module collects the real-time frequency of the motor, collects the real-time amplitude data of the motor through a vibration sensor, and collects the real-time temperature data of the motor through a temperature sensor. The motor is an RO motor in a RO water pump at the front end of an RO membrane in a water treatment system. The motor monitoring module is connected to the sensor through a shielded control cable.

[0013] Furthermore, the process monitoring module collects real-time equipment data and pipeline data at the rear end of the motor through a pressure sensor, wherein the equipment data is the pressure difference between the front and rear ends of the RO membrane, and the pipeline data is the pipeline pressure of the pipeline at the rear end of the motor.

[0014] Furthermore, the water tank monitoring module collects water tank water level data through a water level sensor and collects water tank water quality data through a resistivity sensor.

[0015] Furthermore, the motor usage data includes the maximum life and usage time of the motor, the equipment usage data includes the optimal pressure difference of the RO membrane affecting water quality, the maximum life and water flow time of the RO membrane, and the adjusting of the motor state includes adjusting the motor frequency and shutting down the motor.

[0016] A motor adjustment method based on artificial intelligence comprises the following steps:

[0017] S1: Collect real-time motor operation status data, real-time equipment data and pipeline data at the rear end of the motor, and real-time water level and water quality data at the rear end of the motor water tank;

[0018] S2: Monitor the water quality of the water tank, alarm when the water quality is poor, analyze the water level of the water tank, and calculate the speed of change of the water level;

[0019] S3: When the water level rises, the need to reduce the motor frequency is determined based on the speed of the water level increase. When the motor frequency after the reduction is lower than the minimum motor frequency, the system turns off the motor; when the motor frequency after the reduction is higher than the minimum motor frequency, the motor frequency is adjusted;

[0020] S4: When the water level drops, the need to increase the motor frequency is determined based on the speed of the water level drop, and the motor data, RO membrane data and pipeline data are comprehensively analyzed to calculate the motor frequency increase value; when the motor is not turned on, the motor is turned on and increased to the minimum motor frequency; when the motor is turned on, the motor frequency is increased according to the motor frequency increase value.

[0021] Further, in step S1, the motor operation status data is collected: the real-time frequency of the motor is X1, the real-time amplitude data of the motor is Y1, and the real-time temperature data of the motor is Z1; the real-time equipment data of the rear end of the motor is collected: the pressure difference between the front and rear ends of the RO membrane is P1; the real-time pipeline data is collected: the pipeline pressure of the pipeline at the rear end of the motor is F1; the water quality data in the water tank is collected: the water quality resistivity is R1; the real-time water level height of the water tank is collected as H1; artificial intelligence technology is used to collect system information, and a database is provided for adjusting the motor status in real time and accurately;

[0022] Further, in step S2: the water level before the time t when the real-time water level H1 is collected is called, which is recorded as H2, and the water level change speed is V1:

[0023] V1=(H1-H2) / t;

[0024] Where t is the set time interval for collecting water level height. When the water resistivity R1 in the water tank is less than R, the system determines that the water quality in the water tank is poor, and R is the minimum water quality requirement required by the user. The reason for using resistivity value to judge water quality: resistivity is the most important requirement for judging water quality in pure water preparation and wastewater recovery, and is used as judgment data for the quality of RO membrane in RO reverse osmosis filtration process.

[0025] Further, when V1 is greater than 0, the system determines that the water level is rising, and the system enters step S3, and scores the motor frequency reduction demand B according to the water level change speed V1. When V1≥m1, the motor frequency reduction demand score B=B1; when m1>V1≥m2, the motor frequency reduction demand score B=B2; when V1<m2, the motor frequency reduction demand B=B3, B1>B2>B3, and the motor frequency X1_1 after the frequency reduction is calculated:

[0026]

[0027] Where a is the minimum motor frequency set by the system, m1 is the first threshold for the motor to reduce the frequency, and m2 is the second threshold for the motor to reduce the frequency. When the motor frequency X1_1 = 0, the system turns off the motor, adjusts the motor state, and returns to step S2 to calculate the change in the water level of the water tank with the current water level as the initial water level. Here, considering that starting the motor when the motor frequency is too low may cause a waste of resources, the motor is turned off when it is predicted that the motor frequency will be too low after it is reduced. When the water consumption rate is slightly lower than the production rate, the water level in the water tank rises slowly, and the system will reduce the motor frequency to ensure stable operation of the system and avoid frequent starting and stopping of the motor.

[0028] Further, when V1 is less than 0, the system determines that the water level has dropped, and the system enters step S4. The motor frequency reduction demand Q is scored according to the water level change speed V1. When |V1|≥M1, the motor frequency increase demand score Q=Q1; when M1>|V1|≥M2, the motor frequency increase demand score Q=Q2; when |V1|<M2, the motor frequency increase demand Q=Q3, where M1 is the first threshold value of the system frequency increase, M2 is the second threshold value of the system frequency increase, Q1>Q2>Q3, and the water tank water quality supports the motor frequency increase k1:

[0029] k1=(R1-R)*u1;

[0030] Where u1 is the weight of the effect of the water quality in the water tank on the motor frequency increase, and the support degree k2 of the motor frequency increase by the real-time amplitude data Y1 of the motor is calculated:

[0031] k2=Y2-u2*Y1;

[0032] Among them, u2 is the influence weight of the set motor real-time amplitude on the motor frequency increase, Y2 is the maximum value of the motor real-time amplitude data Y1 supporting the motor frequency increase, and the maximum life of the RO membrane n and the RO membrane water flow time N supporting the motor frequency increase k3 are calculated:

[0033]

[0034] Among them, u3 is the weight of the influence of the set maximum life of the RO membrane and the water flow time of the RO membrane on the motor frequency increase, and the degree of suppression of the motor frequency increase by the real-time temperature data Z1 of the motor is calculated as K1:

[0035] K1=U1*Z1;

[0036] Among them, U1 is the weight of the real-time temperature of the set motor on the motor frequency increase, and the degree of suppression of the motor frequency increase by the pressure difference P1 between the front and rear ends of the RO membrane is calculated as K2:

[0037] K2=U2*(P1-P);

[0038] Among them, U2 is the weight of the influence of the pressure difference between the front and rear ends of the set RO membrane on the motor frequency increase, P is the standard pressure difference when any type of RO membrane has the best filtering effect, and the pipeline pressure F1 of the pipeline at the rear end of the motor is calculated to suppress the motor frequency increase K3:

[0039] K3=U3*F1;

[0040] Among them, U3 is the influence weight of the pipeline pressure of the motor rear pipeline on the motor increase frequency. Based on the above data, the influence coefficient G1 on the motor increase frequency is calculated:

[0041] G1=1+k1+k2+k3-K1-K2-K3;

[0042] Calculate the motor frequency X1_2 after the frequency is increased:

[0043]

[0044] Where A is the maximum frequency of the motor set by the system. After adjusting the motor state, return to step S2 and calculate the change of the water level in the water tank with the current water level as the initial water level. In the process of adjusting the motor state, the damage to the RO membrane caused by excessively increasing the motor frequency is avoided. The water quality of the produced water is guaranteed by analyzing the pressure difference between the front and rear ends of the RO membrane, so as to reasonably adjust the motor state.

[0045] Compared with the prior art, the beneficial effect achieved by the present invention is that the information of the motor, RO membrane and equipment in the system can be obtained in real time through artificial intelligence technology. On the one hand, the present invention takes into account the change of water production, and performs refined management on the motor frequency adjustment, which reduces the number of motor starts and stops when the user's water consumption changes at any time and the RO membrane water production consumption rate is difficult to determine. The motor state is accurately adjusted to protect the motor safety. On the one hand, the present invention takes into account the state of the motor itself, the motor temperature and amplitude, and limits the frequency adjustment of the motor to protect the motor safety; on the other hand, the present invention takes into account the water quality data of the water tank, the optimal pressure difference of the RO membrane affecting the water quality, the maximum life of the RO membrane and the water flow time of the RO membrane, and calculates the motor frequency increase value based on the comprehensive motor frequency increase demand, which enhances the linkage of the entire system, provides more accurate data guarantee for adjusting the motor state, and ensures the safety and accuracy of adjusting the motor state. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 It is a structural diagram of a motor regulation system based on artificial intelligence of the present invention;

[0048] Figure 2 It is a flow chart of a motor adjustment method based on artificial intelligence of the present invention. DETAILED DESCRIPTION

[0049] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0050] See also Figure 1 and Figure 2,The present invention provides a technical solution: an artificial intelligence based motor regulation system, the system includes: a motor monitoring module, a process monitoring module, a water tank monitoring module, a database and a regulation module;

[0051] Collecting real-time motor operating status data through the motor monitoring module;

[0052] The process monitoring module collects real-time equipment data and pipeline data of the motor backend;

[0053] The water tank monitoring module collects real-time water level and water quality data of the water tank at the rear end of the motor;

[0054] The database stores current motor usage data and motor back-end device usage data;

[0055] The regulating module integrates data, analyzes water treatment system requirements, and regulates motor status in real time.

[0056] The motor monitoring module collects the real-time frequency of the motor, collects the real-time amplitude data of the motor through the vibration sensor, and collects the real-time temperature data of the motor through the temperature sensor. The motor is an RO motor in the RO water pump at the front end of the RO membrane in the water treatment system. The motor monitoring module is connected to the sensor through a shielded control cable.

[0057] The process monitoring module collects real-time equipment data and pipeline data at the rear end of the motor through a pressure sensor. The equipment data is the pressure difference between the front and rear ends of the RO membrane, and the pipeline data is the pipeline pressure of the pipeline at the rear end of the motor.

[0058] The water tank monitoring module collects the water level of the water tank through the water level sensor and collects the water quality data of the water tank through the resistivity sensor.

[0059] The motor usage data includes the maximum life and usage time of the motor. The equipment usage data includes the optimal pressure difference of the RO membrane affecting water quality, the maximum life and water flow time of the RO membrane. The adjusting the motor state includes adjusting the motor frequency and shutting down the motor.

[0060] A motor adjustment method based on artificial intelligence comprises the following steps:

[0061] S1: Collect real-time motor operation status data, real-time equipment data and pipeline data at the rear end of the motor, and real-time water level and water quality data at the rear end of the motor water tank;

[0062] S2: Monitor the water quality of the water tank, alarm when the water quality is poor, analyze the water level of the water tank, and calculate the speed of change of the water level;

[0063] S3: When the water level rises, the need to reduce the motor frequency is determined based on the speed of the water level increase. When the motor frequency after the reduction is lower than the minimum motor frequency, the system turns off the motor; when the motor frequency after the reduction is higher than the minimum motor frequency, the motor frequency is adjusted;

[0064] S4: When the water level drops, the need to increase the motor frequency is determined based on the speed of the water level drop, and the motor data, RO membrane data and pipeline data are comprehensively analyzed to calculate the motor frequency increase value; when the motor is not turned on, the motor is turned on and increased to the minimum motor frequency; when the motor is turned on, the motor frequency is increased according to the motor frequency increase value.

[0065] In step S1, the motor operation status data is collected: the real-time frequency of the motor is X1, the real-time amplitude data of the motor is Y1, and the real-time temperature data of the motor is Z1; the real-time equipment data of the rear end of the motor is collected: the pressure difference between the front and rear ends of the RO membrane is P1; the real-time pipeline data is collected: the pipeline pressure of the pipeline at the rear end of the motor is F1; the water quality data in the water tank is collected: the water quality resistivity is R1; the real-time water level height of the water tank is collected as H1;

[0066] In step S2: the water level before the real-time water level H1 is collected is called, which is recorded as H2, and the water level change speed is V1:

[0067] V1=(H1-H2) / t;

[0068] Where t is the set time interval for collecting water level height. When the water resistivity R1 in the water tank is less than R, the system determines that the water quality in the water tank is poor. R is the minimum water quality requirement required by the user.

[0069] When V1 is greater than 0, the system determines that the water level is rising, and the system enters step S3. The motor frequency reduction demand B is scored according to the water level change speed V1. When V1≥m1, the motor frequency reduction demand score B=B1; when m1>V1≥m2, the motor frequency reduction demand score B=B2; when V1<m2, the motor frequency reduction demand B=B3, B1>B2>B3, and the motor frequency X1_1 after the frequency reduction is calculated:

[0070]

[0071] Where a is the minimum motor frequency set by the system, m1 is the first threshold for the motor to reduce the frequency, and m2 is the second threshold for the motor to reduce the frequency. When the motor frequency X1_1=0, the system turns off the motor, adjusts the motor state, and returns to step S2 to calculate the water level change in the water tank with the current water level as the initial water level.

[0072] When V1 is less than 0, the system determines that the water level has dropped, and the system enters step S4. The motor frequency reduction demand Q is scored according to the water level change speed V1. When |V1|≥M1, the motor frequency increase demand score Q=Q1; when M1>|V1|≥M2, the motor frequency increase demand score Q=Q2; when |V1|<M2, the motor frequency increase demand Q=Q3, where M1 is the first threshold value of the system frequency increase, M2 is the second threshold value of the system frequency increase, Q1>Q2>Q3, and the water tank water quality supports the motor frequency increase k1:

[0073] k1=(R1-R)*u1;

[0074] Where u1 is the weight of the effect of the water quality in the water tank on the motor frequency increase, and the support degree k2 of the motor frequency increase by the real-time amplitude data Y1 of the motor is calculated:

[0075] k2=Y2-u2*Y1;

[0076] Among them, u2 is the influence weight of the set motor real-time amplitude on the motor frequency increase, Y2 is the maximum value of the motor real-time amplitude data Y1 supporting the motor frequency increase, and the maximum life of the RO membrane n and the RO membrane water flow time N supporting the motor frequency increase k3 are calculated:

[0077]

[0078] Among them, u3 is the weight of the influence of the set maximum life of the RO membrane and the water flow time of the RO membrane on the motor frequency increase, and the degree of suppression of the motor frequency increase by the real-time temperature data Z1 of the motor is calculated as K1:

[0079] K1=U1*Z1;

[0080] Among them, U1 is the weight of the real-time temperature of the set motor on the motor frequency increase, and the degree of suppression of the motor frequency increase by the pressure difference P1 between the front and rear ends of the RO membrane is calculated as K2:

[0081] K2=U2*(P1-P);

[0082] Among them, U2 is the weight of the influence of the pressure difference between the front and rear ends of the set RO membrane on the motor frequency increase, P is the standard pressure difference when any type of RO membrane has the best filtering effect, and the pipeline pressure F1 of the pipeline at the rear end of the motor is calculated to suppress the motor frequency increase K3:

[0083] K3=U3*F1;

[0084] Among them, U3 is the influence weight of the pipeline pressure of the motor rear pipeline on the motor increase frequency. Based on the above data, the influence coefficient G1 on the motor increase frequency is calculated:

[0085] G1=1+k1+k2+k3-K1-K2-K3;

[0086] Calculate the motor frequency X after the frequency is increased 1_2 :

[0087]

[0088] Where A is the maximum frequency of the motor set by the system. After adjusting the motor state, return to step S2 and calculate the water level change of the water tank with the current water level as the initial water level.

[0089] Embodiment 1: When the system detects V1=-5, when V1 is less than 0, the system determines that the water level has dropped, and the system enters step S4. The motor frequency reduction demand Q is scored according to the water level change speed V1. When |V1|≥M1, the motor frequency increase demand score Q=Q1; when M1>|V1|≥M2, the motor frequency increase demand score Q=Q2; when |V1|<M2, the motor frequency increase demand Q=Q3, where M1 is the first threshold value of the system frequency increase, and M2 is the second threshold value of the system frequency increase, where M1=15, M2=10, and M1=5. In summary, the motor frequency reduction demand Q=10, and the calculation of the water tank water quality support degree k1 for the motor frequency increase:

[0090] k=(R1-R))*1=(10-8)*0.1=0.2;

[0091] Among them, u1=0.1 is the weight of the influence of water quality in the water tank on the motor frequency increase, and the support degree k2 of the motor real-time amplitude data Y1 on the motor frequency increase is calculated:

[0092] k2=Y2-u2*Y1=0.3-0.1*1=0.2;

[0093] Among them, u2=0.1 is the weight of the influence of the real-time amplitude of the motor on the motor frequency increase, Y2 is the maximum value of the support degree of the real-time amplitude data Y1 of the motor for the motor frequency increase, and the support degree k3 of the maximum life of the RO membrane n and the water flow time N of the RO membrane for the motor frequency increase is calculated:

[0094]

[0095] Among them, u3=0.1 is the weight of the maximum life of the RO membrane and the length of time the RO membrane is flowing through the water on the motor frequency increase, and the degree of suppression of the motor frequency increase by the real-time temperature data Z1 of the motor is calculated as K1:

[0096] K1=U1*Z1=0.005*50=0.25;

[0097] Among them, U1=0.005 is the weight of the real-time temperature of the motor on the motor frequency increase, and the suppression degree K2 of the motor frequency increase by the pressure difference P1 at the front and rear ends of the RO membrane is calculated:

[0098] K2=U2*(P1-P)=0.5*(0.6-0.3)=0.15;

[0099] Among them, U2=0.5 is the weight of the pressure difference between the front and rear ends of the RO membrane on the motor frequency increase, P is the standard pressure difference when any type of RO membrane has the best filtering effect, and the degree of suppression of the motor frequency increase by the pipeline pressure F1 of the pipeline at the rear end of the motor is calculated as K3:

[0100] K3=U3*F1=0.5*0.8=0.4;

[0101] Among them, U1=0.3 is the weight of the pipeline pressure at the rear end of the motor on the motor boost frequency, and the motor boost frequency G1 is calculated as follows:

[0102] G1=1+k1+k2+k3-K1-K2-K3=0.8;

[0103] Substitute the calculated motor frequency X1_2 after the frequency is increased:

[0104]

[0105] Find X 1_2 =X1+8, after adjusting the motor state, return to step S2 and calculate the water level change of the water tank with the current water level as the initial water level.

[0106] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A motor adjustment system based on artificial intelligence, characterized in that: The system includes: a motor monitoring module, a process monitoring module, a water tank monitoring module, a database and a regulating module; Collecting real-time motor operating status data through the motor monitoring module; The process monitoring module collects real-time equipment data and pipeline data of the motor backend; The water tank monitoring module collects real-time water level and water quality data of the water tank at the rear end of the motor; The database stores current motor usage data and motor back-end device usage data; The regulating module integrates data, analyzes water treatment system requirements, and regulates motor status in real time.

2. The motor adjustment system based on artificial intelligence according to claim 1, characterized in that: The motor monitoring module collects the real-time frequency of the motor, collects the real-time amplitude data of the motor through a vibration sensor, and collects the real-time temperature data of the motor through a temperature sensor. The motor is an RO motor in an RO water pump at the front end of an RO membrane in a water treatment system. The motor monitoring module is connected to the sensor through a shielded control cable.

3. The motor adjustment system based on artificial intelligence according to claim 1, characterized in that: The process monitoring module collects real-time equipment data and pipeline data at the rear end of the motor through a pressure sensor, wherein the equipment data is the pressure difference between the front and rear ends of the RO membrane, and the pipeline data is the pipeline pressure of the pipeline at the rear end of the motor.

4. The motor adjustment system based on artificial intelligence according to claim 1, characterized in that: The water tank monitoring module collects the water level of the water tank through a water level sensor and collects water quality data of the water tank through a resistivity sensor.

5. The motor adjustment system based on artificial intelligence according to claim 1, characterized in that: The motor usage data includes the maximum life and usage time of the motor, the equipment usage data includes the optimal pressure difference of the RO membrane affecting water quality, the maximum life and water flow time of the RO membrane, and the adjustment of the motor state includes adjusting the motor frequency and shutting down the motor.

6. A motor adjustment method based on artificial intelligence, characterized in that: The following steps are involved: S1: Collect real-time motor operation status data, real-time equipment data and pipeline data at the rear end of the motor, and real-time water level and water quality data at the rear end of the motor water tank; S2: Monitor the water quality of the water tank, alarm when the water quality is poor, analyze the water level of the water tank, and calculate the speed of change of the water level; S3: When the water level rises, the need to reduce the motor frequency is determined based on the speed of the water level increase. When the motor frequency after the reduction is lower than the minimum motor frequency, the system turns off the motor; when the motor frequency after the reduction is higher than the minimum motor frequency, the motor frequency is adjusted; S4: When the water level drops, the need to increase the motor frequency is determined based on the speed of the water level drop, and the motor data, RO membrane data and pipeline data are comprehensively analyzed to calculate the motor frequency increase value; when the motor is not turned on, the motor is turned on and increased to the minimum motor frequency; when the motor is turned on, the motor frequency is increased according to the motor frequency increase value.

7. The motor adjustment method based on artificial intelligence according to claim 6, characterized in that: In step S1, the motor operation status data is collected: the real-time frequency of the motor is X1, the real-time amplitude data of the motor is Y1, and the real-time temperature data of the motor is Z1; the real-time equipment data at the rear end of the motor is collected: the front and rear end pressure difference of the RO membrane is P1; the real-time pipeline data is collected: the pipeline pressure of the pipeline at the rear end of the motor is F1; the water quality data in the water tank is collected: the water quality resistivity is R1; the real-time water level height of the water tank is collected as H1.

8. The motor adjustment method based on artificial intelligence according to claim 7, characterized in that: In step S2: the water level before the real-time water level H1 is collected is called, which is recorded as H2, and the water level change speed is V1: V1=(H1-H2) / t; Where t is the set time interval for collecting water level height. When the water resistivity R1 in the water tank is less than R, the system determines that the water quality in the water tank is poor, and R is the minimum water quality requirement required by the user.

9. The motor adjustment method based on artificial intelligence according to claim 8, characterized in that: When V1 is greater than 0, the system determines that the water level is rising, and the system enters step S3. According to the water level change speed V1, the motor frequency reduction demand B is scored. When V1 ≥ m1, the motor frequency reduction demand score B = B1; when m1>V1≥m2, the motor frequency reduction demand score B = B2; when V1<m2, the motor frequency reduction demand B = B3, B1>B2>B3, and the motor frequency after the frequency reduction is calculated. 1_1 : Where a is the minimum motor frequency set by the system, m1 is the first threshold for motor frequency reduction, and m2 is the second threshold for motor frequency reduction. 1_1 =0, the system turns off the motor, adjusts the motor state, and returns to step S2 to calculate the water level change in the water tank using the current water level as the initial water level.

10. The motor adjustment method based on artificial intelligence according to claim 9, characterized in that: When V1 is less than 0, the system determines that the water level has dropped, and the system enters step S4. The motor frequency reduction demand Q is scored according to the water level change speed V1. When |V1|≥M1, the motor frequency increase demand score Q=Q1; when M1>|V1|≥M2, the motor frequency increase demand score Q=Q2; when |V1|<M2, the motor frequency increase demand Q=Q3, where M1 is the first threshold value of the system frequency increase, M2 is the second threshold value of the system frequency increase, Q1>Q2>Q3, and the water tank water quality supports the motor frequency increase k1: k1=(R1-R)*u1; Where u1 is the weight of the effect of the water quality in the water tank on the motor frequency increase, and the support degree k2 of the motor frequency increase by the real-time amplitude data Y1 of the motor is calculated: k2=Y2-u2*Y1; Among them, u2 is the influence weight of the set motor real-time amplitude on the motor frequency increase, Y2 is the maximum value of the motor real-time amplitude data Y1 supporting the motor frequency increase, and the maximum life of the RO membrane n and the RO membrane water flow time N supporting the motor frequency increase k3 are calculated: Among them, u3 is the weight of the influence of the set maximum life of the RO membrane and the water flow time of the RO membrane on the motor frequency increase, and the degree of suppression of the motor frequency increase by the real-time temperature data Z1 of the motor is calculated as K1: K1=U1*Z1; Among them, U1 is the weight of the real-time temperature of the set motor on the motor frequency increase, and the degree of suppression of the motor frequency increase by the pressure difference P1 between the front and rear ends of the RO membrane is calculated as K2: K2=U2*(P1-P); Among them, U2 is the weight of the influence of the pressure difference between the front and rear ends of the set RO membrane on the motor frequency increase, P is the standard pressure difference when any type of RO membrane has the best filtering effect, and the pipeline pressure F1 of the pipeline at the rear end of the motor is calculated to suppress the motor frequency increase K3: K3=U3*F1; Among them, U3 is the weight of the influence of the pipeline pressure of the motor rear pipeline on the motor increase frequency. Based on the above data, the influence coefficient G1 on the motor increase frequency is calculated: G1=1+k1+k2+k3-K1-K2-K3; Calculate the motor frequency X after the frequency is increased 1_2 : Where A is the maximum frequency of the motor set by the system. After adjusting the motor state, return to step S2 and calculate the water level change of the water tank with the current water level as the initial water level.

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