CN-121997221-A - Method and system for detecting running state of fan, intelligent electrical appliance and storage medium

CN121997221ACN 121997221 ACN121997221 ACN 121997221ACN-121997221-A

Abstract

The disclosure provides a method, a system, an intelligent electrical appliance and a storage medium for detecting the running state of a fan. The detection method comprises the steps of collecting noise time domain signals and vibration time domain signals of the fan under the running state that the fan is in a maximum gear, extracting acoustic characteristic values representing abnormal sound prominence from the noise time domain signals, generating noise state scores through a first preset dynamic scoring rule based on the acoustic characteristic values, extracting vibration characteristic values representing single-frequency vibration intensity from the vibration time domain signals, generating vibration state scores through a second preset dynamic scoring rule based on the vibration characteristic values, calculating age correction factors through a piecewise increasing function according to the service life of the fan, and weighting and fusing the noise state scores, the vibration state scores and the age correction factors to generate comprehensive state scores. The method and the device generate comprehensive scores by fusing three elements of noise, vibration and age, so that the maintenance cost is reduced, the service life of the fan is prolonged, and the environmental noise reaches the standard.

Inventors

WU LIRONG
ZHAO SHIYANG
ZHANG LIQIANG

Assignees

宁波方太厨具有限公司

Dates

Publication Date: 20260508
Application Date: 20260109

Claims (10)

1. A method for detecting an operational state of a fan, the method comprising: Collecting noise time domain signals and vibration time domain signals of the fan under the running state that the fan is in the maximum gear; extracting an acoustic characteristic value representing the abnormal sound prominence degree from the noise time domain signal, and generating a noise state score through a first preset dynamic scoring rule based on the acoustic characteristic value; extracting a vibration characteristic value representing single-frequency vibration intensity from the vibration time domain signal, and generating a vibration state score through a second preset dynamic scoring rule based on the vibration characteristic value; Calculating a year correction factor through a piecewise increasing function according to the service life of the fan; and carrying out weighted fusion on the noise state score, the vibration state score and the age correction factor to generate a comprehensive state score, wherein the comprehensive state score is used for judging the running state of the fan.
2. The method of detecting according to claim 1, wherein the extracting an acoustic feature value characterizing a degree of abnormal sound protrusion from the noise time domain signal comprises: performing frequency domain conversion on the noise time domain signal to obtain a sound pressure frequency spectrum; extracting a maximum sound pressure level peak value of the sound pressure spectrum; calculating an effective sound pressure level for a full time period based on the noise time domain signal; and taking the difference value between the effective sound pressure level and the maximum sound pressure level peak value as the acoustic characteristic value.
3. The method according to claim 2, wherein the extracting the maximum sound pressure level peak of the sound pressure spectrum includes identifying an abnormal frequency band in the sound pressure spectrum in which a gradient change rate is greater than or equal to a change rate threshold value, and extracting the maximum sound pressure level peak from the abnormal frequency band; and/or the number of the groups of groups, The calculating the effective sound pressure level of the whole time period based on the noise time domain signal comprises the steps of calculating a sound pressure root mean square value for all sampling points of the noise time domain signal, and converting the sound pressure root mean square value into a decibel value to serve as the effective sound pressure level.
4. The method of claim 1, wherein said extracting a vibration eigenvalue characterizing a single frequency vibration intensity from said vibration time domain signal comprises: performing frequency domain conversion on the vibration time domain signal to obtain a vibration frequency spectrum; Extracting the maximum vibration peak value of the vibration spectrum; Calculating an effective vibration value of the full time period based on the vibration time domain signal; And taking the ratio of the maximum vibration peak value to the effective vibration value as the vibration characteristic value.
5. The method according to claim 4, wherein extracting the maximum vibration peak value of the vibration spectrum includes extracting a maximum amplitude point as a characteristic frequency peak value within a preset frequency range of the blower; and/or the number of the groups of groups, The calculating of the effective vibration value of the whole time period based on the vibration time domain signal comprises the step of calculating an acceleration root mean square value of all sampling points of the vibration time domain signal, wherein the acceleration root mean square value is used as the effective vibration value.
6. The method of claim 1, wherein the weighted fusion satisfies at least one of: the first contribution weight of the noise state score is greater than the second contribution weight of the vibration state score; the age correction factor monotonically increases with the age; The weighted fusion has an output value that is the product of the age correction factor and a weighted score, wherein the weighted score includes the product of the noise state score and the first contribution weight and the product of the vibration state score and the second contribution weight.
7. A system for detecting an operational condition of a fan, the system comprising: The acquisition module is used for acquiring noise time domain signals and vibration time domain signals of the fan in the running state that the fan is in the maximum gear; the first scoring module is used for extracting an acoustic characteristic value representing the abnormal sound prominence degree from the noise time domain signal and generating a noise state score through a first preset dynamic scoring rule based on the acoustic characteristic value; The second scoring module is used for extracting a vibration characteristic value representing single-frequency vibration intensity from the vibration time domain signal and generating a vibration state score through a second preset dynamic scoring rule based on the vibration characteristic value; The service life correction module is used for calculating a service life correction factor through a piecewise incremental function according to the service life of the fan; And the third scoring module is used for weighting and fusing the noise state score, the vibration state score and the age correction factor to generate a comprehensive state score, and the comprehensive state score is used for judging the running state of the fan.
8. A smart appliance comprising a memory, a processor and a computer program stored on the memory for running on the processor, wherein the processor implements the method of detecting the operational status of the blower of any one of claims 1 to 6 when the computer program is executed by the processor.
9. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the method for detecting the operating state of a fan according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements a method of detecting the operational state of a fan as claimed in any one of claims 1 to 6.

Description

Method and system for detecting running state of fan, intelligent electrical appliance and storage medium Technical Field The disclosure relates to the field of intelligent electrical appliances, in particular to a method and a system for detecting the running state of a fan, an intelligent electrical appliance and a storage medium. Background With the improvement of life quality of people, popularization and popularization of technologies such as Internet, big data, artificial intelligence, voice interaction and the like, more and more traditional life modes are gradually changed, and use of household appliances is gradually approaching to an intelligent direction. The functions of various household appliances tend to be diversified while bringing more convenience to users. At present, the state evaluation of the outdoor fan of the commercial range hood mainly depends on subjective feeling of a user or maintenance plan of a fixed period, and lacks objective quantification basis. In the prior art, although a single parameter (such as the total sound pressure level of noise or the total vibration value) can be detected, a correlation model of age and performance attenuation is not established, so that new and old equipment adopts the same judgment standard. This results in users being unable to accurately judge the actual state of the fan, which is prone to cause problems such as untimely maintenance (shortened service life), premature replacement (resource waste) or continuous exceeding operation (harm of disturbing people). Disclosure of Invention The technical problem to be solved by the present disclosure is to overcome the defect that a set of dynamic quantitative evaluation system integrating noise abnormal sound characteristics, vibration frequency doubling energy and equipment aging factors is not established in the prior art to realize accurate hierarchical decision of fan states, and provide a detection method, a system, an intelligent electrical appliance and a storage medium for fan running states. The technical problems are solved by the following technical scheme: The present disclosure provides a method for detecting a fan operation state, the method comprising: Collecting noise time domain signals and vibration time domain signals of the fan under the running state that the fan is in the maximum gear; extracting an acoustic characteristic value representing the abnormal sound prominence degree from the noise time domain signal, and generating a noise state score through a first preset dynamic scoring rule based on the acoustic characteristic value; extracting a vibration characteristic value representing single-frequency vibration intensity from the vibration time domain signal, and generating a vibration state score through a second preset dynamic scoring rule based on the vibration characteristic value; Calculating a year correction factor through a piecewise increasing function according to the service life of the fan; and carrying out weighted fusion on the noise state score, the vibration state score and the age correction factor to generate a comprehensive state score, wherein the comprehensive state score is used for judging the running state of the fan. Optionally, the extracting an acoustic feature value characterizing a degree of alien protrusion from the noise time domain signal includes: performing frequency domain conversion on the noise time domain signal to obtain a sound pressure frequency spectrum; extracting a maximum sound pressure level peak value of the sound pressure spectrum; calculating an effective sound pressure level for a full time period based on the noise time domain signal; and taking the difference value between the effective sound pressure level and the maximum sound pressure level peak value as the acoustic characteristic value. Optionally, the extracting the maximum sound pressure level peak value of the sound pressure spectrum comprises identifying an abnormal frequency band with a gradient change rate greater than or equal to a change rate threshold value in the sound pressure spectrum, and extracting the maximum sound pressure level peak value from the abnormal frequency band; and/or the number of the groups of groups, The calculating the effective sound pressure level of the whole time period based on the noise time domain signal comprises the steps of calculating a sound pressure root mean square value for all sampling points of the noise time domain signal, and converting the sound pressure root mean square value into a decibel value to serve as the effective sound pressure level. Optionally, the extracting a vibration characteristic value characterizing the single-frequency vibration intensity from the vibration time domain signal includes: performing frequency domain conversion on the vibration time domain signal to obtain a vibration frequency spectrum; Extracting the maximum vibration peak value of the vibration spectrum; Calculating an effective v