A method for detecting eccentricity of a pulsator washing machine

Abstract

The application discloses a pulsator washing machine eccentricity detection method, force sensors are installed to collect force data of four hangers, and the detection process comprises the following steps: A, the washing machine is operated in a dehydration mode, the motor speed r is recorded, and an eccentricity index threshold value is set; B, force data of each hanger during operation of the washing machine is collected; C, the force data is filtered and denoised, and then the average force value Avg_Force of each hanger, the maximum force value Max_Force of each hanger and the standard deviation Std_Dev of each hanger are calculated; D, the maximum eccentricity index of the four hangers is calculated according to the data, and compared with the eccentricity index threshold value set in A, and if the maximum eccentricity index is greater than the eccentricity index threshold value, it is judged that the washing machine is eccentric. The maximum eccentricity index of the four hangers is obtained through the force data of the four hangers, and whether the washing machine is eccentric is judged according to comparison between the maximum eccentricity index and the eccentricity index threshold value. Only four force sensors need to be added, the hardware cost is low, and the calculation is simple.

Description

Technical Field

[0001] This invention belongs to the field of pulsator washing machines, and in particular to a method for detecting eccentricity in pulsator washing machines. Background Technology

[0002] With the continuous development of the national economy, people's requirements for quality of life are also increasing, and the comfort of using household appliances is becoming a criterion for their purchase. Currently, washing machines on the market generate a lot of vibration during the spin-drying process, causing serious noise pollution. Furthermore, the wear and tear between washing machine parts caused by vibration greatly reduces the lifespan of the washing machine.

[0003] The vibration during the spin cycle of a washing machine mainly stems from the imbalance of the clothes inside, meaning the clothes are eccentrically positioned. This eccentricity in traditional top-loading washing machines can lead to decreased washing performance, increased noise, and a shortened lifespan. Current technologies for detecting imbalance in front-loading washing machines primarily involve detecting steady-state motor speed fluctuations and torque fluctuations. However, these methods generate significant vibrations when estimating eccentricity, causing severe noise pollution. Furthermore, because the motor torque during rotation is difficult to measure, estimating eccentricity using speed and torque results in longer data acquisition times and less accurate eccentricity values. Therefore, developing a reliable eccentricity detection method for top-loading washing machines is crucial for improving their performance and stability. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for detecting eccentricity in a pulsator washing machine by obtaining the maximum eccentricity index of the four suspension rods through the force data of the four suspension rods, and determining whether there is eccentricity by comparing the maximum eccentricity index with the eccentricity index threshold. This method only requires the addition of four force sensors, is low in cost, and is simple to calculate.

[0005] The objective of this invention is achieved through the following technical solution: a method for detecting eccentricity in a pulsator washing machine, comprising installing force sensors to collect force data on four suspension rods, and the detection process including the following steps:

[0006] A. The washing machine is running in spin-dry mode. The motor speed r is recorded, and the eccentricity index threshold at speed r is set.

[0007] B. Data collection during washing machine operation. Force data for each internal boom;

[0008] C. Filter and denoise the force data, and then calculate the average force value Avg_Force, the maximum force value Max_Force, and the standard deviation Std_Dev of each boom.

[0009] D. Calculate the maximum eccentricity index of the four booms based on the data, and compare the maximum eccentricity index with the eccentricity index threshold set in A. If it is greater than the eccentricity index threshold, it is judged as eccentric.

[0010] The specific calculation method in step D is as follows:

[0011]

[0012] In the above equation, subscripts 1 to 4 represent four booms, and E1 to E4 are the eccentricity indices of each boom. max This is the maximum eccentricity index.

[0013] The beneficial effects of this invention are: This invention obtains the maximum eccentricity index of the four booms using force data, and determines whether eccentricity exists by comparing the maximum eccentricity index with an eccentricity index threshold. This invention only requires adding four force sensors to complete the detection, resulting in relatively low hardware costs; furthermore, the calculation method is simple, and the software implementation is quite easy, leading to very low overall development costs and ease of implementation. Attached Figure Description

[0014] Figure 1 This is a flowchart of the washing machine eccentricity detection method of the present invention. Detailed Implementation

[0015] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0016] This invention discloses a method for detecting eccentricity in a pulsator washing machine. This method involves installing force sensors to collect force data from the four suspension rods, and then calculating the maximum eccentricity index to determine if eccentricity exists. The specific process is as follows: Figure 1 As shown, the detection process includes the following steps:

[0017] A. The washing machine is running in spin-dry mode. The motor speed r is recorded, and the eccentricity index threshold at speed r is set.

[0018] B. Data collection during washing machine operation. Force data for each internal boom;

[0019] C. Filter and denoise the force data, and then calculate the average force value Avg_Force, the maximum force value Max_Force, and the standard deviation Std_Dev of each boom.

[0020] D. Calculate the maximum eccentricity index of the four booms based on the data, and compare the maximum eccentricity index with the eccentricity index threshold set in A. If it is greater than the eccentricity index threshold, it is judged as eccentric. The specific calculation method is as follows:

[0021]

[0022] In the above equation, subscripts 1 to 4 represent four booms, and E1 to E4 are the eccentricity indices of each boom. max This is the maximum eccentricity index.

[0023] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for detecting eccentricity in a pulsator washing machine, characterized in that, The force sensors are installed to collect force data on the four booms. The detection process includes the following steps: A. The washing machine is running in spin-dry mode. The motor speed r is recorded, and the eccentricity index threshold at speed r is set. B. Data collection during washing machine operation. Force data for each internal boom; C. Filter and denoise the force data, and then calculate the average force value Avg_Force, the maximum force value Max_Force, and the standard deviation Std_Dev of each boom. D. Calculate the maximum eccentricity index of the four booms based on the data, and compare the maximum eccentricity index with the eccentricity index threshold set in A. If it is greater than the eccentricity index threshold, it is judged as eccentric. The specific calculation method is as follows: ； In the above calculation method, subscripts 1 to 4 represent 4 lifting rods. Here is the eccentricity index of each boom. This is the maximum eccentricity index.

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