A washing machine spin-drying method with adaptive adjustment of control parameters and a washing machine

Abstract

This invention provides a washing machine spin-drying method with adaptive adjustment of control parameters, comprising the following steps: S0: Start; S1: Determine if it is the first time the machine is turned on; if yes, initialize the vibration threshold and proceed to S2; otherwise, proceed directly to S2; S2: Initialize the distribution count t = 0; S3: Perform eccentric distribution; after the eccentric distribution, perform eccentricity and weighing detection, and determine if the machine has entered the rotation speed v(k-2); if yes, the washing machine speeds up to v(k-2) and detects the vibration value a(k-2) at this time, then proceed to S4; otherwise, proceed to S2; S4: Determine if a(k-2) < a(k-2) - threshold is satisfied; if yes, the washing machine speeds up to v(k-1) and detects the vibration value a(k-1) at this time, then proceed to S5; otherwise, proceed to S2. This invention does not rely on a single threshold for spin-drying; it not only makes full use of vibration data but also allows for corresponding parameter adjustments based on the actual machine conditions, improving the washing machine's vibration performance and user experience.

Description

Technical Field

[0001] This invention relates to the field of washing machine technology, specifically to a washing machine spin-drying method and a washing machine with adaptive adjustment of control parameters. Background Technology

[0002] Currently, washing machine spin-drying control schemes often rely on pre-set parameters, such as vibration values ​​and rotation speed. The measured parameters are compared with set thresholds to determine the washing machine's performance status. For example, patent application number 201110131911.4, publication number CN102251369A, entitled "Washing Machine," discloses a patent that uses a first and second detection mechanism to detect abnormal longitudinal shaking vibrations, and a third detection mechanism to detect abnormal lateral shaking vibrations during high-speed rotation. The first detection mechanism determines whether there is an imbalance in the washing and spin-drying tub by comparing the difference in rotation speed measured at specified intervals when the motor speed is increased to the low-speed target speed with a specified threshold. The second detection mechanism determines whether there is an imbalance in the washing and spin-drying tub by comparing the difference between the reduction in the load ratio used to maintain the low-speed target speed and the reduction in the reference load ratio with a threshold. The third detection mechanism observes the change in the load ratio during high-speed rotation and switches the threshold based on the reference load ratio to stop the motor. The aforementioned patent only makes a single threshold judgment on the vibration value. However, due to various reasons, the vibration performance of a product cannot be controlled by a single-dimensional parameter. For example, different temperatures cause different working damping forces of the vibration damping, and the vibration damping components may be damaged or worn. All of these situations can lead to a deterioration in the product's vibration performance. Detecting and judging by a single-dimensional parameter and threshold will reduce product performance and user experience.

[0003] Therefore, there is an urgent need to provide a washing machine spin-drying method and a washing machine with adaptive adjustment of control parameters to solve the above-mentioned technical problems. Summary of the Invention

[0004] This invention provides a washing machine spin-drying method and a washing machine with adaptive adjustment of control parameters. The method predicts vibration values ​​using a pre-established vibration mathematical model and detects actual vibration values ​​using vibration sensors. The parameters are then adjusted based on the measured and predicted values.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A washing machine spin-drying method with adaptive adjustment of control parameters includes the following steps:

[0007] S0: Start;

[0008] S1: Determine if this is the first time the device is powered on. If yes, initialize the vibration threshold and proceed to S2; otherwise, proceed directly to S2.

[0009] S2: Initialize the distribution number t=0;

[0010] S3: Perform eccentric distribution. After the eccentric distribution is completed, perform eccentricity and weighing detection to determine whether the speed v(k-2) has been reached. If yes, the washing machine speeds up to v(k-2) and the vibration value a(k-2) is detected at this time. Proceed to S4; otherwise, proceed to S2.

[0011] S4: Determine whether a(k-2) < a(k-2)_threshold is satisfied. If yes, the washing machine speeds up to v(k-1) and detects the vibration value a(k-1) at this time, then proceed to S5; otherwise, proceed to S2.

[0012] S5: Determine whether a(k-1) < a(k-1)_threshold is satisfied. If yes, the washing machine speeds up to v(k) and detects the vibration value a(k) at this time, then proceed to S6; otherwise, proceed to S7.

[0013] S6: Predict the vibration value at the current rotational speed v(k) based on the values ​​of a(k-2) and a(k-1), obtain the predicted value of a(k), and proceed to S8;

[0014] S7: The washing machine spins water at a stable speed v(k-1), and after the spin-drying is completed, it enters S10;

[0015] S8: Obtain the difference e by subtracting the actual detected vibration value a(k) from the predicted value a(k), and then proceed to S9;

[0016] S9: If e satisfies [-m1, n1], the washing machine will stably spin-dry at the target speed v(k); otherwise, the washing machine will enter the parameter adjustment / alarm module and proceed to S10.

[0017] S10: End;

[0018] Where k≥3.

[0019] Preferably, the washing machine dehydration method further includes a step of obtaining a prototype neural network mathematical model before step S0, comprising the following steps:

[0020] S00: Vibration data of the prototype in the laboratory is collected through vibration sensors;

[0021] S01: Train the neural network model;

[0022] S02: Obtain the neural network mathematical model of the prototype;

[0023] The predicted value of a(k) is obtained by a neural network mathematical model.

[0024] Preferably, the eccentric distribution in step S3 is a process of using centrifugal force to make the clothes stick to the inner drum of the washing machine.

[0025] Preferably, the eccentricity and weighing detection in step S3 includes the following steps: S310: After the eccentricity distribution is completed, the eccentricity and weighing value of the inner barrel are detected;

[0026] S320: Determine whether the following conditions are met: eccentricity < eccentricity threshold && weighing value < weighing threshold. If yes, the washing machine proceeds to the next program; otherwise, proceed to S4.

[0027] Preferably, step S9 further includes a parameter adjustment process, comprising the following steps:

[0028] S910: Determine whether the following conditions are met: n2≥e>n1‖-m2≤e<-m1. If yes, proceed to S920; otherwise, proceed to S950.

[0029] S920: and enter S930;

[0030] S930: a(n)_threshold = a(n)_threshold_new, and proceed to S940;

[0031] S940: The washing machine spins water at a stable speed v(n) and then enters S910 after the spin-drying is completed;

[0032] S950: Further determine whether e < -m2 is satisfied. If yes, proceed to S960; otherwise, proceed to S970.

[0033] S960: Sensor failure alarm, and enters S910;

[0034] S970: Alarm triggered by aging, damage, or impact to the housing of vibration damping components, and proceeds to S910;

[0035] Where 0 < β < 1.

[0036] Preferably, the vibration sensor is a 3D vibration sensor.

[0037] Preferably, the vibration value a(n) includes vibration values ​​in three orthogonal directions, i.e., a(n) = [a(n)_x, a(n)_y, a(n)_z].

[0038] Preferably, the value of e = a(n) - a(n)_predicted value = 1 / 3[(a(n)_x - a(n)_predicted value_x) + (a(n)_y - a(n)_predicted value_y) + (a(n)_z - a(n)_predicted value_z)], where n ≥ 3.

[0039] The present invention also provides a washing machine, wherein the washing machine performs a spin-drying operation using the aforementioned control parameter adaptive adjustment method.

[0040] As can be seen from the above technical solutions, the present invention has the following beneficial effects: In the present invention, modeling can be performed based on the data from research and development experiments for vibration data prediction. Vibration data from real users can be combined with the model for prediction. By comparing the actual vibration data and the predicted data, the error value is obtained. If the error value is within the control range, the dehydration control is performed normally. If the error value is not within the control range but within the adjustable parameter range, the parameter is adjusted. If the error value is neither within the control range nor within the adjustable parameter range, an alarm is triggered. The present invention does not perform dehydration processing based on a single threshold judgment. It can not only make full use of vibration data, but also make corresponding parameter adjustments according to the actual overall machine condition, thereby improving the vibration performance of the washing machine and the user experience. Attached Figure Description

[0041] Figure 1 A flowchart of one embodiment of the washing machine spin-drying method provided by the present invention;

[0042] Figure 2 Flowchart of the parameter adjustment algorithm;

[0043] Figure 3 Flowchart for training a neural network model;

[0044] Figure 4 A flowchart of another embodiment of the washing machine spin-drying method provided by the present invention. Detailed Implementation

[0045] A preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings.

[0046] Reference Figure 1 , Figure 4 A washing machine spin-drying method with adaptive adjustment of control parameters includes the following steps:

[0047] S0: Begin.

[0048] Specifically, the washing machine starts up according to the preset program and begins to work.

[0049] S1: Determine if this is the first time the device is powered on. If yes, initialize the vibration threshold and proceed to S2; otherwise, proceed directly to S2.

[0050] Specifically, it is determined whether the washing machine is being turned on for the first time. If it is, the vibration threshold A(n) is initialized to a(n)_threshold_original. It should be noted that a(n)_threshold_original is the initial value of the logic control valve, which is set by the design. After the threshold A(n) is initialized, it enters S2. If the washing machine is not being turned on for the first time, it directly enters S2.

[0051] S2: Initialize the distribution number t=0.

[0052] Specifically, the distribution frequency t is initialized by setting t to 0.

[0053] S3: Perform eccentric distribution. After the eccentric distribution is completed, perform eccentricity and weighing detection to determine whether to enter the rotation speed v(k-2). If yes, the washing machine speeds up to v(k-2) and the vibration value a(k-2) is detected at this time, then proceed to S4; otherwise, proceed to S2.

[0054] Specifically, eccentric distribution is performed. In this invention, eccentric distribution refers to a rotation process of the washing machine. By setting a rotation speed, the centrifugal force is continuously increased, causing the clothes to adhere to the inner drum of the washing machine. After the eccentric distribution stage is completed, eccentricity and weighing detection are performed. After the eccentricity and weighing detection are completed, based on the results of the eccentricity and weighing detection, it is determined whether the washing machine has increased its speed to v(k-2). If so, the washing machine increases its speed to v(k-2) and detects the vibration value a(k-2) at that speed, and then proceeds to S4. If the washing machine does not meet the condition of increasing its speed to v(k-2), the washing machine proceeds to S2, that is, the number of distributions t is re-initialized. It should be noted that in this invention, k≥3.

[0055] Furthermore, the eccentricity and weight detection are performed after the eccentricity distribution is completed (clothes are attached to the inner drum of the washing machine). The eccentricity and weight value at this time are detected when the inner drum rotates. During the eccentricity and weight detection process, the detection eccentricity amount < eccentricity threshold && weight value < weight threshold can be set. If the above setting logic is met, the washing machine can proceed to the next step.

[0056] In addition, the eccentricity and weighing detection process is not limited to detecting the eccentricity and weighing value. It can also be replaced by 3D acceleration detection, that is, by detecting whether the real-time acceleration 'a' of the inner tub is less than 'a' threshold. If 'a' < 'a' threshold, the washing machine will proceed to the next step.

[0057] It should be noted that, based on the initial distribution number t=0, each time an eccentric distribution is performed, the distribution number t needs to be incremented by 1. When the washing machine does not meet the condition of increasing speed to v(k-2), it is also necessary to judge the distribution number t at this time. That is, a distribution number threshold T is preset to judge whether t at this time satisfies t<T. If it satisfies, then proceed to step S2; if it does not satisfy, then proceed to S10 and end the entire dehydration operation.

[0058] S4: Determine whether a(k-2) < a(k-2)_threshold is satisfied. If yes, the washing machine speeds up to v(k-1) and detects the vibration value a(k-1) at this time, then proceed to S5; otherwise, proceed to S2.

[0059] Specifically, the vibration value a(k-2) detected in S3 is compared with the threshold a(k-2)_threshold set by the system. If a(k-2) < a(k-2)_threshold is satisfied, the washing machine speeds up to v(k-1) and the vibration value a(k-1) at that speed is detected. Then, the process proceeds to S5. If a(k-2) < a(k-2)_threshold is not satisfied, the process proceeds to S2, which is to reinitialize the number of distributions t.

[0060] S5: Determine whether a(k-1) < a(k-1)_threshold is satisfied. If yes, the washing machine speeds up to v(k) and detects the vibration value a(k) at this time, then proceed to S6; otherwise, proceed to S7.

[0061] Specifically, the a(k-1) detected in S4 is compared with the a(k-1) threshold set by the system. If a(k-1) < a(k-1) threshold is satisfied, the washing machine speeds up to v(k) and the vibration value a(k) at that speed is detected, and then proceeds to S6; if a(k-1) < a(k-1) threshold is not satisfied, then proceeds to S7.

[0062] S6: Predict the vibration value at the current rotational speed v(k) based on the values ​​of a(k-2) and a(k-1), obtain the predicted value of a(k), and proceed to S8.

[0063] Specifically, based on the two vibration values ​​a(k-2) and a(k-1) detected in S3 and S4, the vibration value at rotational speed v(k) is predicted, and the predicted value corresponding to rotational speed v(k) is obtained, i.e., a(k)_predicted value. Then, proceed to S8. It should be noted that the present invention will collect the vibration data of the prototype in the laboratory in advance through vibration sensors, and use neural network modeling or a mathematical model of whole machine vibration to predict the vibration value of the prototype at rotational speed v(k) through a(k-2) and a(k-1).

[0064] S7: The washing machine spins water at a stable speed v(k-1), and after the spin-drying is completed, it enters S10.

[0065] Specifically, if the detected a(k-1) in the aforementioned S5 does not satisfy a(k-1) < a(k-1)_threshold, the washing machine will stably spin-dry at a speed v(k-1), and the entire spin-drying process will end as the spin-drying process ends.

[0066] S8: Obtain the difference e by subtracting the actual detected vibration value a(k) from the predicted value a(k), and then proceed to S9.

[0067] Specifically, based on the predicted value of a(k) obtained in S6 above, the actual detected vibration value a(k) is subtracted from the predicted value of a(k) to obtain the difference e, that is, e=a(k)-a(k)-predicted value, and then proceed to S9.

[0068] S9: If e satisfies [-m1, n1], the washing machine will stably spin-dry at the target speed v(k); otherwise, the washing machine will enter the parameter adjustment / alarm module and proceed to S10.

[0069] Specifically, based on the difference e obtained in S8 above, it is further determined whether e is within the interval [-m1, n1], that is, whether -m1≤e≤n1 is satisfied. If satisfied, the washing machine will stably spin water at a rotation speed v(k). If not satisfied, the washing machine will enter the parameter adjustment / alarm module and then end the entire spin water process.

[0070] S10: End.

[0071] Specifically, after the washing machine performs the above-mentioned dehydration process, the work ends. It should be noted that since k≥3 in this invention, when predicting the vibration value of the washing machine at speed v(3) in this invention, it is necessary to predict the vibration value at speed v(3) based on the vibration values ​​at v(1) and v(2) actually measured by the sensor. Based on the first two vibration values, the vibration value at speed v(3) can be predicted by the neural network model.

[0072] Reference Figure 3 As a preferred embodiment of the present invention, the washing machine spin-drying method with adaptive adjustment of control parameters further includes a step of obtaining a prototype neural network mathematical model before S0, comprising the following steps:

[0073] S00: Vibration data of the prototype in the laboratory is collected through vibration sensors.

[0074] Specifically, vibration sensors are used to collect vibration data from the laboratory prototype, so that a vibration model of the prototype can be obtained by modeling based on the collected vibration data. In addition, the collected actual vibration data of the prototype can also be used to control the initial parameters of the washing machine.

[0075] S01: Train the neural network model.

[0076] Specifically, based on the prototype vibration data obtained from the aforementioned S00, a neural network model is trained.

[0077] S02: Obtain the neural network mathematical model of the prototype.

[0078] Specifically, based on the neural network model training performed in the aforementioned S01, a neural network mathematical model of the prototype is obtained, which facilitates the subsequent prediction of the vibration value at a certain speed based on the mathematical model. It should be noted that the aforementioned a(k)_ prediction value is obtained through the neural network mathematical model, and the step of obtaining the prototype neural network mathematical model is to conduct experiments and model it in the laboratory before the washing machine spins water.

[0079] As a preferred technical solution of the present invention, refer to Figure 2 Step S9 also includes a parameter adjustment process, which includes the following steps:

[0080] S910: Determine whether the following conditions are met: n2≥e>n1‖-m2≤e<-m1. If yes, proceed to S920; otherwise, proceed to S950.

[0081] Specifically, when e satisfies n1<e≤n2 or -m2≤e<-m1, the washing machine enters S920. That is, when e is in either of the intervals (n1, n2) and [-m2, -m1), the washing machine enters S920. If e is outside the above two intervals, the washing machine enters S950. It should be noted that n1<n2 and -m2<-m1.

[0082] S920: And enter S930.

[0083] Specifically, when e is in either of the intervals (n1, n2] and [-m2, -m1), the threshold corresponding to the rotational speed v(n) is adjusted to... ,Right now .

[0084] S930: a(n)_threshold = a(n)_threshold_new, and enter S940.

[0085] Specifically, the threshold under rotational speed v(n) is adjusted to a new threshold, i.e., a(n)_threshold = a(n)_threshold_new, and then proceed to S940.

[0086] S940: The washing machine spins water at a stable speed v(n) and then enters S910 after the spin-drying is completed.

[0087] Specifically, the washing machine spins water at a stable rotation speed v(n) and ends the entire spin-drying process after the spin-drying is completed.

[0088] S950: Further determine whether e < -m2 is satisfied. If yes, proceed to S960; otherwise, proceed to S970.

[0089] Specifically, if e is not within the intervals (n1, n2] and [-m2, -m1), then it is further determined whether e < -m2 is satisfied. If yes, then proceed to S960; otherwise, proceed to S970.

[0090] S960: Sensor failure alarm, and enters S910.

[0091] Specifically, if e is not within the intervals (n1, n2) and [-m2, -m1), but satisfies e < -m2, it indicates that the sensor has failed. The washing machine enters the sensor failure alarm program and ends the entire washing machine spin cycle after the alarm ends.

[0092] S970: Alarm triggered by aging, damage, or impact to the housing of vibration damping components, and proceeds to S910.

[0093] Specifically, if e is neither within the intervals (n1, n2) and [-m2, -m1) nor satisfies e < -m2, it indicates that the vibration damping components of the washing machine are aging or damaged, or that the vibration damping components collide with the cabinet. The washing machine will then issue an alarm for aging, damage, or collision with the cabinet of the vibration damping components, and end the entire spin-drying process of the washing machine after the alarm ends.

[0094] This invention revises the initially set threshold by the error value e. That is, if the threshold e is within the range of n2≥e>n1‖-m2≤e<-m1, the parameter is corrected. The principle is that because the state of the damper of the whole machine changes (such as wear), the previous logic control threshold can no longer meet the current state, and the control threshold needs to be adjusted by e.

[0095] As a preferred technical solution of the present invention, the vibration value of the washing machine at a specific rotation speed is detected by a 3D vibration sensor. The value detected by the 3D vibration sensor can be a vibration displacement value or a vibration acceleration value, which can be selected according to the actual working conditions. In the present invention, it is a vibration displacement value. The vibration value detected by the 3D vibration sensor includes values ​​in three orthogonal directions, namely x, y and z. As for the vibration value a(n), a(n) = [a(n)_x, a(n)_y, a(n)_z].

[0096] As a preferred technical solution of the present invention, the value of e = a(n) - a(n)_predicted value = 1 / 3 [(a(n)_x - a(n)_predicted value_x) + (a(n)_y - a(n)_predicted value_y) + (a(n)_z - a(n)_predicted value_z)] is given. Since the vibration value detected by the 3D vibration sensor is in three directions, the corresponding value of e is also in three directions, as shown in the formula above.

[0097] This invention also discloses a washing machine that uses the aforementioned adaptive adjustment method for control parameters during spin-drying. This allows for the initial modeling based on research and development data for vibration data prediction. Vibration data from real users can then be combined with the model for further prediction. By comparing the actual vibration data with the predicted data, an error value is obtained. If the error value is within the control range, normal spin-drying control is performed. If the error value is outside the control range but within the adjustable parameter range, parameter adjustments are made. If the error value is neither within the control range nor the adjustable parameter range, an alarm is triggered. This invention does not rely on a single threshold for spin-drying; it not only fully utilizes vibration data but also allows for corresponding parameter adjustments based on the actual condition of the entire machine, improving the washing machine's vibration performance and user experience.

[0098] The following example illustrates the dehydration method provided by this invention:

[0099] 1. First, data testing was conducted in the laboratory using a 3D vibration sensor to obtain 3D vibration values ​​under different eccentricities and load conditions (these 3D vibration values ​​can be vibration displacement values ​​or vibration acceleration values, which can be selected according to the actual working conditions; in this case, vibration displacement values ​​are used); as shown in Table 1 below, which shows the vibration values ​​under a load of 0kg, different eccentricities, and eccentricity at the beginning.

[0100]

[0101] Table 1 - Vibration values ​​of the prototype with a load of 0kg, different eccentricities, and eccentricity at the beginning.

[0102] 2. Then, by centering and post-centering the eccentricity, the corresponding vibration values ​​are obtained, and the model input X and output Y are obtained. 31 samples are shown in Table 2 below.

[0103]

[0104] Table 2-31 Vibration values ​​of samples

[0105] 3. Train a neural network model in Matlab (one sample, 6 input parameters, 3 output parameters).

[0106] 4. For a well-trained neural network model Y=net(X), with a load of 0kg, an eccentricity of 200g, and a preload, the vibration values ​​at 400rpm, 600rpm, and 750rpm are [7, 16, 10], [6, 14, 16], and [6, 14, 17], respectively, as shown in Table 1. Using these six parameters, the vibration value at 750rpm is predicted as Y=net([7, 16, 10, 6, 14, 16]). Inputting this into Matlab yields the following result: Y=[6.1686, 14.1252, 16.8160]. Comparing this with the actual test value, the error value e is obtained, e=a(n)-a(n)_prediction, and the result is e=sum([6, 14, 17]-[6.1686, 14.1252, 16.8160]) / 3=-0.0366.

[0107] 5. If the error value 'e' between the actual test value and the predicted value is outside the normal range during actual washing machine operation, appropriate handling is required. The specific solution is as follows: Figure 2 As shown.

[0108] 6. The parameter correction scheme involves revising the initially set threshold using the error value e. If the threshold e falls within the range of n2≥e>n1‖-m2≤e<-m1, parameter correction is performed. The principle is that changes in the state of the overall system damper (such as wear) cause the previous logic control threshold to be unable to meet the current state, requiring adjustment of the control threshold through e.

[0109] The above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A washing machine spin-drying method with adaptive adjustment of control parameters, characterized in that, Includes the following steps: S0: Start; S1: Determine if this is the first time the device is powered on. If yes, initialize the vibration threshold and proceed to S2; otherwise, proceed directly to S2. S2: Initialize the distribution number t=0; S3: Perform eccentric distribution. After the eccentric distribution is completed, perform eccentricity and weighing detection to determine whether the speed v(k-2) has been reached. If yes, the washing machine speeds up to v(k-2) and the vibration value a(k-2) is detected at this time. Proceed to S4; otherwise, proceed to S2. S4: Determine whether a(k-2) < a(k-2)_threshold is satisfied. If yes, the washing machine speeds up to v(k-1) and detects the vibration value a(k-1) at this time, then proceed to S5; otherwise, proceed to S2. S5: Determine whether a(k-1) < a(k-1)_threshold is satisfied. If yes, the washing machine speeds up to v(k) and detects the vibration value a(k) at this time, then proceed to S6; otherwise, proceed to S7. S6: Predict the vibration value at the current rotational speed v(k) based on the values ​​of a(k-2) and a(k-1), obtain the predicted value of a(k), and proceed to S8; S7: The washing machine spins water at a stable speed v(k-1), and after the spin-drying is completed, it enters S10; S8: Obtain the difference e by subtracting the actual detected vibration value a(k) from the predicted value a(k), and then proceed to S9; S9: If e satisfies [-m1, n1], the washing machine will stably spin-dry at the target speed v(k); otherwise, the washing machine will enter the parameter adjustment / alarm module and proceed to S10. S10: End; Where k≥3; Step S9, parameter adjustment, includes the following steps: S910: Determine whether the following conditions are met: n2≥e>n1‖-m2≤e<-m1. If yes, proceed to S920; otherwise, proceed to S950. S920: and enter S930; S930: a(n)_threshold = a(n)_threshold_new, and proceed to S940; S940: The washing machine spins water at a stable speed v(n) and then enters S910 after the spin-drying is completed; S950: Further determine whether e < -m2 is satisfied. If yes, proceed to S960; otherwise, proceed to S970. S960: Sensor failure alarm, and enters S910; S970: Alarm triggered by aging, damage, or impact to the housing of vibration damping components, and proceeds to S910; Where 0 < β < 1, a(n)_threshold is the vibration logic control threshold corresponding to the vibration value a(n) of the washing machine at a rotation speed v(n).

2. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 1, characterized in that, The washing machine spin-drying method further includes a step of obtaining a prototype neural network mathematical model before S0, including the following steps: S00: Vibration data of the prototype in the laboratory is collected through vibration sensors; S01: Train the neural network model; S02: Obtain the neural network mathematical model of the prototype; The predicted value of a(k) is obtained by a neural network mathematical model.

3. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 1, characterized in that, The eccentric distribution in step S3 is the process of using centrifugal force to make the clothes stick to the inner drum of the washing machine.

4. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 1, characterized in that, The eccentricity and weighing detection in step S3 includes the following steps: S310: After the eccentric distribution is completed, detect the eccentricity and weighing value of the inner barrel; S320: Determine whether the following conditions are met: eccentricity < eccentricity threshold && weighing value < weighing threshold. If yes, the washing machine proceeds to the next program; otherwise, proceed to S4.

5. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 2, characterized in that, The vibration sensor is a 3D vibration sensor.

6. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 5, characterized in that, The vibration value a(n) includes vibration values ​​in three orthogonal directions, i.e., a(n) = [a(n)_x, a(n)_y, a(n)_z].

7. The washing machine spin-drying method with adaptive adjustment of control parameters according to claim 6, characterized in that, The value e = a(n) - a(n)_predicted value = 1 / 3[(a(n)_x - a(n)_predicted value_x) + (a(n)_y - a(n)_predicted value_y) + (a(n)_z - a(n)_predicted value_z)], where n ≥ 3.

8. A washing machine, characterized in that, The washing machine performs a spin-drying operation using a washing machine spin-drying method with adaptive adjustment of control parameters as described in any one of claims 1-7.

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