Method and system for detecting weight of clothes in washing machine, electronic equipment and medium

Abstract

The invention relates to the technical field of washing machines, and provides a method and system for detecting the weight of clothes in a washing machine, electronic equipment and a medium. Generating a weight parameter based on the actual acceleration signal, wherein the weight parameter comprises a first characteristic value representing an acceleration average value in unit time, a second characteristic value representing an acceleration optimal baseline value in unit time, and a third characteristic value representing a minimum value of the sum of acceleration absolute distances in unit time; determining at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generating prompt information for judging the weight of the clothes in the washing machine. According to the method for detecting the weight of the clothes in the washing machine, the weight of the clothes in the washing machine is quickly judged by obtaining the actual acceleration signal when the washing machine works.

Description

Technical Field

[0001] The present invention relates to the technical field of washing machines, and in particular to a method, system, electronic equipment and medium for detecting the weight of clothes in a washing machine. Background Art

[0002] When washing clothes, it is often necessary to determine the weight of the clothes in the washing machine and make corresponding adjustments.

[0003] The existing processing method is mainly to determine by direct weight detection, but this method requires additional weighing sensors, which increases the cost of the washing machine, and the detection efficiency of the weighing sensor set up solely for weighing is low during the operation of the washing machine. Summary of the invention

[0004] The embodiments of the present invention provide a method, system, electronic device and medium for detecting the weight of clothes in a washing machine, which solves the problem that weighing clothes in an existing washing machine requires an additional weighing sensor, which increases the cost of the washing machine and has low detection efficiency.

[0005] An embodiment of the present invention provides a method for detecting the weight of clothes in a washing machine, comprising:

[0006] Obtain the actual acceleration signal of the washing machine;

[0007] Generate a weight parameter based on the actual acceleration signal, the weight parameter including a first characteristic value representing an average value of acceleration within a unit time, a second characteristic value representing an optimal baseline value of acceleration within a unit time, and a third characteristic value representing a minimum value of a sum of absolute distances of acceleration within a unit time;

[0008] At least one of the first characteristic value, the second characteristic value and the third characteristic value is determined to generate prompt information for determining the weight of the clothes in the washing machine.

[0009] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, before the step of obtaining an actual acceleration signal of the washing machine, the method further includes:

[0010] Acquire a test acceleration set of the washing machine under different eccentricity conditions and clothing weights; the test acceleration set includes a plurality of groups of weight parameters corresponding to different eccentricity conditions and clothing weights;

[0011] A working model of the washing machine corresponding to different eccentricity conditions and clothing weights and each group of characteristic values ​​is established, wherein the working model includes a first fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value for different clothing weights in the case of no collision with the rod, and a second fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value for different clothing weights in the case of collision with the rod.

[0012] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, the step of determining at least one of the first characteristic value, the second characteristic value, and the third characteristic value and generating prompt information for determining the weight of clothes in the washing machine includes:

[0013] determining the eccentricity of the washing machine according to the first characteristic value, the second characteristic value, and the third characteristic value;

[0014] In the case where there is no collision with the rod, generating prompt information for determining the weight of the clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the first fluctuation range;

[0015] In the case of a collision with the rod, prompt information for determining the weight of the clothes in the washing machine is generated according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the second fluctuation range.

[0016] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, the first fluctuation range includes: a plurality of first fluctuation intervals, a plurality of second fluctuation intervals and a plurality of third fluctuation intervals;

[0017] Each of the first fluctuation intervals corresponds to the first characteristic value of different clothing weight intervals when no collision occurs; each of the second fluctuation intervals corresponds to the second characteristic value of different clothing weight intervals when no collision occurs; each of the third fluctuation intervals corresponds to the third characteristic value of different clothing weight intervals when no collision occurs;

[0018] The second fluctuation range includes: a plurality of fourth fluctuation intervals, a plurality of fifth fluctuation intervals and a plurality of sixth fluctuation intervals;

[0019] The first characteristic value of different clothing weight intervals when each of the fourth fluctuation intervals corresponds to the collision rod; the second characteristic value of different clothing weight intervals when each of the fifth fluctuation intervals corresponds to the collision rod; the third characteristic value of different clothing weight intervals when each of the sixth fluctuation intervals corresponds to the collision rod.

[0020] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, the step of generating prompt information for determining the weight of clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the first fluctuation range includes:

[0021] When the first characteristic value is within the first fluctuation range, and / or the second characteristic value is within the second fluctuation range, and / or the third characteristic value is within the third fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

[0022] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, the step of generating prompt information for determining the weight of clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the second fluctuation range comprises:

[0023] When the first characteristic value is within the fourth fluctuation range, and / or the second characteristic value is within the fifth fluctuation range, and / or the third characteristic value is within the sixth fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

[0024] According to a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention, after the step of determining at least one of the first characteristic value, the second characteristic value and the third characteristic value and generating prompt information for determining the weight of clothes in the washing machine, the method further includes:

[0025] In response to the prompt information, the speed of the drum in the washing machine is adjusted based on the weight of the clothes in the washing machine.

[0026] The present invention also provides a washing machine eccentricity detection system, comprising:

[0027] An acquisition module, used for acquiring an actual acceleration signal of the washing machine;

[0028] A first generating module is used to generate a weight parameter based on the actual acceleration signal, wherein the weight parameter includes a first characteristic value representing an average value of acceleration per unit time, a second characteristic value representing an optimal baseline value of acceleration per unit time, and a third characteristic value representing a minimum value of a sum of absolute distances of acceleration per unit time.

[0029] The second generating module is used to determine at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generate prompt information for judging the weight of the clothes in the washing machine.

[0030] An embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the method for detecting the weight of clothes in the washing machine is implemented when the processor executes the program.

[0031] An embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for detecting the weight of clothes in the washing machine is implemented.

[0032] An embodiment of the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the method for detecting the weight of clothes in the washing machine.

[0033] The method for detecting the weight of clothes in a washing machine provided by the present invention is to set an acceleration sensor in the washing machine, obtain the actual acceleration signal when the washing machine is working, and generate weight parameters based on the actual acceleration signal. The weight parameters include a first eigenvalue representing the average value of acceleration per unit time, a second eigenvalue representing the optimal baseline value of acceleration per unit time, and a third eigenvalue representing the minimum value of the sum of absolute distances of acceleration per unit time. The prompt information of the weight of clothes in the washing machine is judged based on this, so as to quickly determine the weight of clothes in the washing machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 This is one of the flow charts of a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention;

[0036] Figure 2 This is a second flow chart of a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention;

[0037] Figure 3 is a test acceleration set of a method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention;

[0038] Figure 4 is one of the schematic diagrams of a test acceleration set after data processing provided by an embodiment of the present invention;

[0039] Figure 5 This is a second schematic diagram of a test acceleration set after data processing provided by an embodiment of the present invention;

[0040] Figure 6 is a structural schematic diagram of a washing machine eccentricity detection system provided by an embodiment of the present invention;

[0041] Figure 7 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention;

[0042] Reference numerals:

[0043] 610, acquisition module; 620, first generation module; 620, second generation module; 710, processor; 720, communication interface; 730, memory; 740, communication bus. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] An embodiment of the present invention provides a method for detecting the weight of clothes in a washing machine. Different from the existing detection method, this embodiment sets an acceleration sensor in the washing machine and determines the weight of the clothes in the washing machine by changing the acceleration in the washing machine.

[0046] like Figure 1 As shown, the method for detecting the weight of clothes in the washing machine includes the following steps:

[0047] Step S110: obtaining an actual acceleration signal of the washing machine.

[0048] When the washing machine is in operation, the acceleration sensor obtains the actual acceleration signal of the washing machine in real time.

[0049] It should be pointed out that the actual acceleration signal detected by the acceleration sensor is a parameter of acceleration per unit time.

[0050] Step S120: Generate a weight parameter based on the actual acceleration signal.

[0051] After determining the actual acceleration signal of the washing machine, a weight parameter is generated based on the actual acceleration signal. The weight parameter includes a first characteristic value representing the average value of acceleration per unit time, a second characteristic value representing the optimal baseline value of acceleration per unit time, and a third characteristic value representing the minimum value of the sum of absolute distances of acceleration per unit time.

[0052] The first characteristic value is the average value of acceleration within a unit time (for example, 25 milliseconds).

[0053] The second characteristic value is the optimal baseline value SP per unit duration (e.g. 25 milliseconds). For example, under the data of unit duration, an initial baseline value is selected. This value can be selected by the average value of the current duration data (assuming baselineInput = 130), and at the same time, calculating the possible baseline values ​​SP_array within a certain range (the range is selected to include the maximum and minimum values ​​of the data of unit duration, for example SP_array = baselineInput-50:0.1:baselineInput+50). The optimal baseline value SP per unit duration is obtained from SP_array. The judgment basis is when R(i,1) obtains the minimum value. R(i,1) = sum(abs(ss1-sp_array(i))); where i represents each value in SP_array, i = 1:length(sp). For example, if i = 5, sp_array(i) represents the 5th value in sp_array. R represents the sum of the absolute values ​​of the differences between the acceleration value array and each possible SP_array value within a unit time length. When R takes the minimum value, the corresponding SP_array(i) under the i value (for example, when i=541, R(541)=40 is the minimum value of all R values), the optimal baseline value SP at this time is equal to SP_array(541), for example, equal to 134.

[0054] The third characteristic value is the minimum value of the sum of absolute distances per unit time length (eg, 25 milliseconds), that is, the value when R takes the minimum value.

[0055] Step S130: Determine at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generate prompt information for determining the weight of the clothes in the washing machine.

[0056] After determining at least one of the first characteristic value, the second characteristic value and the third characteristic value, the weight of the clothes in the washing machine can be judged according to the sizes of the three characteristic values, and prompt information for judging the weight of the clothes in the washing machine can be generated according to the situation.

[0057] The method for detecting the weight of clothes in a washing machine provided by an embodiment of the present invention sets an acceleration sensor in the washing machine, obtains the actual acceleration signal when the washing machine is working, and generates a weight parameter based on the actual acceleration signal. The weight parameter includes a first eigenvalue representing the average value of acceleration per unit time, a second eigenvalue representing the optimal baseline value of acceleration per unit time, and a third eigenvalue representing the minimum sum of absolute distances of acceleration per unit time. The prompt information of the weight of clothes in the washing machine is judged based on this, so as to quickly determine the weight of clothes in the washing machine.

[0058] In one embodiment, if Figure 2 As shown, before step S110: obtaining the actual acceleration signal of the washing machine, the method further includes:

[0059] Step S90: Obtain a set of test accelerations of the washing machine under different eccentricity conditions and clothing weights.

[0060] Before determining the weight of the clothes in the washing machine, it is necessary to determine the relationship between the characteristic value and the eccentricity of the washing machine, as well as the relationship between the weight of the clothes in the washing machine and the characteristic value. Therefore, an acceleration sensor is used to obtain the acceleration of the working process of the washing machine, so as to obtain a set of test accelerations under different eccentricity conditions and clothes weights. The test acceleration set includes multiple sets of weight parameters corresponding to different eccentricity conditions and clothes weights.

[0061] In a specific embodiment, to ensure the repeatability of the data, symmetrical weights are attached to the same position inside the washing machine drum according to different kilograms. For example, in the 1.4 kg test, two 0.7 kg weights are attached to the symmetrical ends of the straight line where the inner diameter of the drum is located. Each set of weights is repeated 4 times. In the later stage, the number of tests can be increased to optimize the model accuracy. The test results are shown in the figure. Figure 3 As shown, Figure 3 There are four groups representing 1.8 kg, and the raw acceleration data ACC and the pole / bar collision events are plotted for each group.

[0062] The curves in the figure above are the original acceleration signal, the data of the original acceleration signal after data cleaning, the display of the pole collision (pole collision event, pole collision occurs) in the time dimension (when it is equal to 200 units, it means that a pole collision event has occurred) and the mark position of the filtered acceleration abnormal data; the horizontal axis is the length of the original data, where the sampling frequency is Fs=1000hz.

[0063] After obtaining complete data, in order to judge the eccentricity state of the washing machine, Figure 4 and Figure 5As shown in the figure, three characteristic variables are extracted from the acceleration signal after data cleaning: the average value of the unit time length (for example, 25 milliseconds), the optimal baseline value of the unit time length, and the minimum value of the sum of the absolute distances of the unit time length; the washing machine state calculated by the acceleration data under the unit time length (when it is equal to 140, it is the washing machine initialization data. When the number of running cycles exceeds 5 times, the historical 25 milliseconds is multiplied by 5, triggering the algorithm monitoring and assigning a value of 155, indicating that the washing machine has not had a state event. When the value is assigned to 170, it means that a collision event has occurred. The black circle represents the position where the state occurs, which is consistent with the moment of the collision curve in the above figure, but is attributed to the collision event per unit time length). The horizontal axis is the time unit second, which is equivalent to generating the above set of data per unit time length. For example, the total length of the data is 15932, the sampling frequency is Fs, 25 milliseconds is equivalent to 25 data lengths, 15932 / 25 is rounded down to 637, that is, a total of 637 groups of five values, and the length of the time dimension is 15.925 seconds. That is, 0.025, 0.05, 0.075, 0.1 to 15.925, totaling 637 groups.

[0064] The principle of data extraction is shown in the following table. When the first pole collision event is not triggered, the values ​​of the three characteristic variables before the triggering (columns 4-6) and the values ​​of the three characteristic variables (columns 1-3) for each pole collision event are saved; the data of the untriggered pole collision event after the first pole collision event is triggered are ignored.

[0065] Specifically, the first four rows (columns 4-6) store the values ​​of the three characteristic variables before the first pole-hitting event is triggered; rows 5 to 9 (1-3) store the values ​​of the three characteristic variables during the first pole-hitting event; rows 13 to 16 (1-3) store the values ​​of the three characteristic variables during the second pole-hitting event; and the subsequent ones are similar. This is to express that the data of the untriggered pole-hitting event after the first pole-hitting event is triggered is no longer saved. Thus, by processing the data, a set of test accelerations corresponding to different eccentricity conditions and clothing weights can be obtained.

[0066] Table 1

[0067]

[0068] Step S100: Establishing a working model of the washing machine corresponding to different eccentricity conditions and clothing weights and each group of characteristic values.

[0069] After obtaining the test acceleration set of the washing machine under different eccentricity conditions and clothing weights, the difference between these three eigenvalues ​​in triggering the impact rod event and not triggering the impact rod event can be used to establish a method for identifying the weight of clothing through an accelerometer, and to establish a working model of the washing machine corresponding to each group of eigenvalues ​​under different eccentricity conditions and clothing weights.

[0070] The working model includes a first fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value of different clothing weights when there is no collision with the rod, and a second fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value of different clothing weights when there is a collision with the rod.

[0071] Based on the above embodiment, in one embodiment, step S130: determining at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generating prompt information for determining the weight of the clothes in the washing machine, includes:

[0072] Step S1310: Determine the eccentricity of the washing machine according to the first characteristic value, the second characteristic value, and the third characteristic value.

[0073] In order to reduce the measurement error, before determining the weight of the clothes, the eccentricity of the washing machine is determined according to the magnitudes of the first eigenvalue, the second eigenvalue and the third eigenvalue.

[0074] Step S1320: In the absence of a collision with the rod, a prompt message for determining the weight of the clothes in the washing machine is generated according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the first fluctuation range.

[0075] Step S1330: In the case of a collision with the rod, a prompt message for determining the weight of the clothes in the washing machine is generated according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the second fluctuation range.

[0076] Specifically, the first fluctuation range includes: multiple first fluctuation intervals, multiple second fluctuation intervals and multiple third fluctuation intervals; each first fluctuation interval corresponds to the first characteristic value of different clothing weight intervals when there is no collision with the rod; each second fluctuation interval corresponds to the second characteristic value of different clothing weight intervals when there is no collision with the rod; each third fluctuation interval corresponds to the third characteristic value of different clothing weight intervals when there is no collision with the rod.

[0077] The second fluctuation range includes: multiple fourth fluctuation intervals, multiple fifth fluctuation intervals and multiple sixth fluctuation intervals; the first characteristic value of different clothing weight intervals when each fourth fluctuation interval corresponds to the collision rod; the second characteristic value of different clothing weight intervals when each fifth fluctuation interval corresponds to the collision rod; the third characteristic value of different clothing weight intervals when each sixth fluctuation interval corresponds to the collision rod.

[0078] When it is determined that there is no collision with the rod, when the first characteristic value is within the first fluctuation range, and / or the second characteristic value is within the second fluctuation range, and / or the third characteristic value is within the third fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

[0079] For example, the third eigenvalue shows a regular pattern of showing a higher value in the low weight area. For example, from 1 to 1.4 kg, the third eigenvalue is above 140; and from 1.5 to 2.0 kg, the third eigenvalue is below 138. Therefore, the approximate range of the weight of the clothes in the washing machine can be determined according to the size of the third eigenvalue.

[0080] When a collision is detected, when the first characteristic value is within the fourth fluctuation range, and / or the second characteristic value is within the fifth fluctuation range, and / or the third characteristic value is within the sixth fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

[0081] In a specific embodiment, when the kilograms in the barrel are less than 1.4 kilograms, 95% of the values ​​of the second characteristic value are statistically lower than the second threshold value of 150. When actually applied, the method for real-time detection of the kilograms of the clothes in the barrel is that when the value of the second characteristic value has not exceeded the set second threshold value, and at the same time satisfies the judgment rules of similar examples composed of other first characteristic values, second characteristic values ​​and third characteristic values, it can be judged that the kilograms in the barrel are less than 1.4 kilograms.

[0082] In other embodiments, the duration can also be accumulated, and the non-operating time is defined as the T0 time, the time after t1 time after the self-operating state is turned on is the starting time T1, the time of the accumulated time ts after T1 is analyzed is the end time T2, and the average value curve of the first characteristic value, the second characteristic value and the third characteristic value in the ts time. Among them, for the judgment and selection of characteristic values, different starting times (T1), timing lengths ts, and end times T2 can be combined into multiple groups of judgment rules.

[0083] When the results of several judgment feature values ​​show different results, the priority principle is to make the results that meet multiple conditions at the same time. For example, if the weight is less than or equal to 1.7 kg and less than or equal to 1.4 kg, the result is less than or equal to 1.4 kg; if the weight is less than or equal to 1.7 kg and greater than 1.4 kg, the result is between 1.4 and 1.7 kg.

[0084] In actual measurement, it is necessary to comprehensively consider the values ​​of the first eigenvalue, the second eigenvalue, and the third eigenvalue within the fluctuation range. For example, the first eigenvalue determines the weight interval of one piece of clothing, the second eigenvalue determines the weight interval of another piece of clothing, and the third eigenvalue determines another weight interval of clothing. The weight of the clothing in the washing machine can be accurately determined by the overlapping positions of the three intervals.

[0085] Based on the above embodiment, after determining at least one of the first characteristic value, the second characteristic value and the third characteristic value in step S130 and generating a prompt message for judging the weight of the clothes in the washing machine, it also includes: responding to the prompt message and adjusting the rotation speed of the drum in the washing machine based on the weight of the clothes in the washing machine.

[0086] Here, the washing machine determines the weight of the clothes based on the prompt information, and can control the barrel in the washing machine to adjust the speed or stop according to the weight to protect the operation of the washing machine.

[0087] The following is a description of a washing machine eccentricity detection system provided by an embodiment of the present invention. The washing machine eccentricity detection system described below and the detection method described above can be referred to each other.

[0088] like Figure 6 As shown, the washing machine eccentricity detection system includes: an acquisition module 610 , a first generation module 620 and a second generation module 630 .

[0089] Among them, the acquisition module 610 is used to obtain the actual acceleration signal of the washing machine; the first generation module 620 is used to generate weight parameters based on the actual acceleration signal, and the weight parameters include a first eigenvalue representing the average value of acceleration per unit time, a second eigenvalue representing the optimal baseline value of acceleration per unit time, and a third eigenvalue representing the minimum sum of absolute distances of acceleration per unit time. The second generation module 630 is used to determine at least one of the first eigenvalue, the second eigenvalue and the third eigenvalue, and generate prompt information for judging the weight of clothes in the washing machine.

[0090] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730 and a communication bus 740, wherein the processor 710, the communication interface 720 and the memory 730 communicate with each other through the communication bus 740. The processor 710 may call the logic instructions in the memory 730 to execute the detection method including: obtaining the actual acceleration signal of the washing machine; generating a weight parameter based on the actual acceleration signal, the weight parameter including a first characteristic value representing the average value of acceleration per unit time, a second characteristic value representing the optimal baseline value of acceleration per unit time and a third characteristic value representing the minimum value of the sum of the absolute distance of acceleration per unit time; determining at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generating prompt information for judging the weight of the clothes in the washing machine.

[0091] It should be noted that the electronic device in this embodiment can be a server, a PC, or other devices in specific implementation, as long as its structure includes the following: Figure 7The processor 710, communication interface 720, memory 730 and communication bus 740 shown in the figure, wherein the processor 710, communication interface 720, memory 730 communicate with each other through the communication bus 740, and the processor 710 can call the logic instructions in the memory 730 to execute the above method. This embodiment does not limit the specific implementation form of the electronic device.

[0092] In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0093] Furthermore, an embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the detection methods provided by the above-mentioned method embodiments, and the detection method includes: obtaining an actual acceleration signal of a washing machine; generating a weight parameter based on the actual acceleration signal, the weight parameter including a first eigenvalue representing an average value of acceleration per unit time, a second eigenvalue representing an optimal baseline value of acceleration per unit time, and a third eigenvalue representing a minimum sum of absolute distances of acceleration per unit time; determining at least one of the first eigenvalue, the second eigenvalue and the third eigenvalue, and generating prompt information for judging the weight of clothes in the washing machine.

[0094] On the other hand, an embodiment of the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the detection method provided by the above-mentioned embodiments, and the detection method includes: obtaining an actual acceleration signal of a washing machine; generating a weight parameter based on the actual acceleration signal, the weight parameter including a first eigenvalue representing an average value of acceleration per unit time, a second eigenvalue representing an optimal baseline value of acceleration per unit time, and a third eigenvalue representing the minimum sum of absolute distances of acceleration per unit time; determining at least one of the first eigenvalue, the second eigenvalue and the third eigenvalue, and generating prompt information for judging the weight of clothes in the washing machine.

[0095] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0096] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the weight of clothes in a washing machine, characterized in that: include: Obtain the actual acceleration signal of the washing machine; Generate a weight parameter based on the actual acceleration signal, the weight parameter including a first characteristic value representing an average value of acceleration within a unit time, a second characteristic value representing an optimal baseline value of acceleration within a unit time, and a third characteristic value representing a minimum value of a sum of absolute distances of acceleration within a unit time; At least one of the first characteristic value, the second characteristic value and the third characteristic value is determined to generate prompt information for determining the weight of the clothes in the washing machine.

2. The method for detecting the weight of clothes in a washing machine according to claim 1, characterized in that: Before the step of obtaining the actual acceleration signal of the washing machine, the method further includes: Acquire a test acceleration set of the washing machine under different eccentricity conditions and clothing weights; the test acceleration set includes a plurality of groups of weight parameters corresponding to different eccentricity conditions and clothing weights; A working model of the washing machine corresponding to different eccentricity conditions and clothing weights and each group of characteristic values ​​is established, wherein the working model includes a first fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value for different clothing weights in the case of no collision with the rod, and a second fluctuation range corresponding to the first characteristic value, the second characteristic value and the third characteristic value for different clothing weights in the case of collision with the rod.

3. The method for detecting the weight of clothes in a washing machine according to claim 2, characterized in that: The step of determining at least one of the first characteristic value, the second characteristic value, and the third characteristic value to generate prompt information for determining the weight of the clothes in the washing machine includes: determining the eccentricity of the washing machine according to the first characteristic value, the second characteristic value, and the third characteristic value; In the case where there is no collision with the rod, generating prompt information for determining the weight of the clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the first fluctuation range; In the case of a collision with the rod, prompt information for determining the weight of the clothes in the washing machine is generated according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the second fluctuation range.

4. The method for detecting the weight of clothes in a washing machine according to claim 3, characterized in that: The first fluctuation range includes: a plurality of first fluctuation intervals, a plurality of second fluctuation intervals and a plurality of third fluctuation intervals; Each of the first fluctuation intervals corresponds to the first characteristic value of different clothing weight intervals when no collision occurs; each of the second fluctuation intervals corresponds to the second characteristic value of different clothing weight intervals when no collision occurs; each of the third fluctuation intervals corresponds to the third characteristic value of different clothing weight intervals when no collision occurs; The second fluctuation range includes: a plurality of fourth fluctuation intervals, a plurality of fifth fluctuation intervals and a plurality of sixth fluctuation intervals; The first characteristic value of different clothing weight intervals when each of the fourth fluctuation intervals corresponds to the collision rod; the second characteristic value of different clothing weight intervals when each of the fifth fluctuation intervals corresponds to the collision rod; the third characteristic value of different clothing weight intervals when each of the sixth fluctuation intervals corresponds to the collision rod.

5. The method for detecting the weight of clothes in a washing machine according to claim 4, characterized in that: The step of generating prompt information for determining the weight of clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the first fluctuation range comprises: When the first characteristic value is within the first fluctuation range, and / or the second characteristic value is within the second fluctuation range, and / or the third characteristic value is within the third fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

6. The method for detecting the weight of clothes in a washing machine according to claim 5, characterized in that: The step of generating prompt information for determining the weight of clothes in the washing machine according to the relationship between the first characteristic value, the second characteristic value, the third characteristic value and the second fluctuation range comprises: When the first characteristic value is within the fourth fluctuation range, and / or the second characteristic value is within the fifth fluctuation range, and / or the third characteristic value is within the sixth fluctuation range, a prompt message for determining the weight of the clothes in the washing machine is generated.

7. The method for detecting the weight of clothes in a washing machine according to any one of claims 1 to 6, characterized in that: After the step of determining at least one of the first characteristic value, the second characteristic value and the third characteristic value and generating prompt information for determining the weight of the clothes in the washing machine, the method further includes: In response to the prompt information, the speed of the drum in the washing machine is adjusted based on the weight of the clothes in the washing machine.

8. A washing machine eccentricity detection system, characterized in that: include: An acquisition module, used for acquiring an actual acceleration signal of the washing machine; A first generating module is used to generate a weight parameter based on the actual acceleration signal, wherein the weight parameter includes a first characteristic value representing an average value of acceleration per unit time, a second characteristic value representing an optimal baseline value of acceleration per unit time, and a third characteristic value representing a minimum value of a sum of absolute distances of acceleration per unit time. The second generating module is used to determine at least one of the first characteristic value, the second characteristic value and the third characteristic value, and generate prompt information for judging the weight of the clothes in the washing machine.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for detecting the weight of clothes in the washing machine as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for detecting the weight of clothes in a washing machine as described in any one of claims 1 to 7 is implemented.

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