Kitchen air conditioner and active noise reduction method and device thereof under different working conditions

Abstract

The embodiment of the invention discloses a kitchen air conditioner and an active noise reduction method and device thereof under different working conditions. A fan and a secondary loudspeaker are arranged in the kitchen air conditioner, and an acceleration sensor is arranged on a casing of the fan. The active noise reduction method comprises the steps that an acceleration sensor is used for detecting a machine shell vibration signal of a draught fan; predicting a real-time noise signal of the fan according to the vibration signal and a preset noise prediction model; according to the real-time noise signal of the fan, determining an anti-phase sound wave signal of the real-time noise of the fan through a preset secondary sound wave digital model; and the secondary loudspeaker is used for playing the reverse sound wave signal so as to carry out active noise reduction on the kitchen air conditioner. According to the embodiment, the problems that in the operation process of the kitchen air conditioner, noise is large, and communication and cooking experience of people in a kitchen are seriously disturbed are solved, the noise level generated during operation of the kitchen air conditioner is lowered, and active noise reduction on the noise of the kitchen air conditioner based on the fan vibration condition is achieved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of noise control, and in particular, to a kitchen air conditioner and an active noise reduction method and device thereof under different working conditions. Background Art

[0002] With the continuous improvement of people's living quality, the requirements for the comfort of the home environment are becoming increasingly strict. In the kitchen scenario, as a key device for adjusting the indoor temperature, the performance of the kitchen air conditioner directly affects the user's cooking experience.

[0003] Currently, common kitchen air conditioners mainly achieve air circulation and heating / cooling through the operation of traditional fans. To reduce noise, some products add sound-absorbing materials such as sound-absorbing cotton inside the air conditioner housing. At the same time, some air conditioners are equipped with basic noise monitoring functions. When the detected noise exceeds a certain threshold, the fan speed will be reduced.

[0004] However, based on the above technical solutions, there is still a problem of high noise during the operation of the kitchen air conditioner. Especially when in different working conditions, it is unable to adjust the noise reduction strategy according to the working conditions, and can only block some noise, and cannot solve the problem of noise generation at the source. This seriously interferes with the communication of people in the kitchen, makes it difficult to communicate during the cooking process, and also greatly destroys the cooking experience, making users suffer from noise problems when using the kitchen air conditioner. Summary of the Invention

[0005] The present invention provides a kitchen air conditioner and an active noise reduction method and device thereof under different working conditions to solve the problems of high noise during the operation of the kitchen air conditioner, which seriously interfere with the communication of people in the kitchen and the cooking experience.

[0006] In a first aspect, an embodiment of the present invention provides an active noise reduction method for a kitchen air conditioner fan. A fan and a secondary speaker are provided inside the kitchen air conditioner, and an acceleration sensor is provided on the housing of the fan.

[0007] The active noise reduction method includes:

[0008] Detecting the vibration signal of the fan housing by using the acceleration sensor;

[0009] Predicting the real-time noise signal of the fan according to the vibration signal and a preset noise prediction model;

[0010] Determining the anti-phase sound wave signal of the real-time noise of the fan through a preset secondary sound wave digital model according to the real-time noise signal of the fan;

[0011] Playing the anti-phase sound wave signal by using the secondary speaker to perform active noise reduction on the kitchen air conditioner.

[0012] Optionally, the noise prediction model is trained as follows:

[0013] Experimentally obtain a wind turbine vibration signal dataset, which includes multiple vibration signal samples and real-time wind turbine noise samples corresponding to the vibration signal samples;

[0014] Use the wind turbine vibration signal dataset to train a neural network model to obtain a noise prediction model.

[0015] Optionally, the kitchen air conditioner includes a refrigeration chamber and a heat dissipation chamber;

[0016] The secondary speakers include a first secondary speaker and a second secondary speaker; the first secondary speaker is disposed in the refrigeration chamber; the second secondary speakers are all disposed in the heat dissipation chamber;

[0017] A refrigeration fan is also disposed in the refrigeration chamber, and a heat dissipation fan is also disposed in the heat dissipation chamber;

[0018] The acceleration sensors include a first acceleration sensor and a second acceleration sensor. The first acceleration sensor is disposed on the casing of the refrigeration fan, and the second acceleration sensor is disposed on the casing of the heat dissipation fan;

[0019] Detecting the casing vibration signal of the fan by using the acceleration sensor includes:

[0020] Detecting a first vibration signal of the casing of the refrigeration fan by using the first acceleration sensor;

[0021] Detecting a second vibration signal of the casing of the heat dissipation fan by using the second acceleration sensor;

[0022] Predicting the real-time noise signal of the fan according to the vibration signal and a preset noise prediction model, including:

[0023] Predicting a first real-time noise signal of the refrigeration fan according to the first vibration signal and a preset noise prediction model of the refrigeration fan;

[0024] Predicting a second real-time noise signal of the heat dissipation fan according to the second vibration signal and a preset noise prediction model of the heat dissipation fan;

[0025] Determining the anti-sound wave signal of the real-time noise of the fan according to the real-time noise signal of the fan through a preset secondary sound wave digital model, including:

[0026] Selecting the one with the greater noise among the first real-time noise signal and the second real-time noise signal, and determining a first anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model;

[0027] Playing the anti-sound wave signal by using the secondary speaker to perform active noise reduction on the kitchen air conditioner, including:

[0028] Play a first anti - sound wave signal through a first secondary speaker in the refrigeration chamber where the refrigeration fan with relatively high noise is located, or play a first anti - sound wave signal through a second secondary speaker in the heat dissipation chamber where the heat dissipation fan with relatively high noise is located, so as to perform primary active noise reduction on the kitchen air conditioner.

[0029] Optionally, selecting the one with relatively higher noise among the first real - time noise signal and the second real - time noise signal includes:

[0030] Calculate the root - mean - square values of the first real - time noise signal and the second real - time noise signal respectively, and obtain a first root - mean - square value and a second root - mean - square value;

[0031] Compare the first root - mean - square value and the second root - mean - square value, and obtain the larger one.

[0032] Optionally, before calculating the root - mean - square values of the first real - time noise signal and the second real - time noise signal respectively to obtain a first root - mean - square value and a second root - mean - square value, it further includes:

[0033] Intercept the first real - time noise signal and the second real - time noise signal within the human ear hearing frequency band.

[0034] Optionally, an acoustic microphone sensor is arranged on the shell of the kitchen air conditioner;

[0035] After performing primary active noise reduction on the kitchen air conditioner by playing a first anti - sound wave signal through a first secondary speaker in the refrigeration chamber where the refrigeration fan with relatively high noise is located, or playing a first anti - sound wave signal through a second secondary speaker in the heat dissipation chamber where the heat dissipation fan with relatively high noise is located, it further includes:

[0036] Collect the noise signal of the space where the kitchen air conditioner is located by using the acoustic microphone sensor;

[0037] When the noise signal is greater than a preset noise threshold, select the smaller one of the first real - time noise signal and the second real - time noise signal, and determine a second anti - sound wave signal of the real - time noise of the corresponding fan through a preset secondary sound wave digital model;

[0038] Play the second anti - sound wave signal through a first secondary speaker in the refrigeration chamber where the refrigeration fan with relatively low noise is located, or play the second anti - sound wave signal through a second secondary speaker in the heat dissipation chamber where the heat dissipation fan with relatively low noise is located, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0039] Optionally, when the noise signal is greater than a preset noise threshold, selecting the smaller one of the first real - time noise signal and the second real - time noise signal, and determining a second anti - sound wave signal of the real - time noise of the corresponding fan through a preset secondary sound wave digital model includes:

[0040] Calculate the root mean square value of the noise signal to obtain the third root mean square value;

[0041] When the third root mean square value is greater than the preset root mean square value of the noise, calculate the root mean square values of the first real-time noise signal and the second real-time noise signal respectively to obtain the first root mean square value and the second root mean square value;

[0042] Select the smaller one of the first root mean square value and the second root mean square value, and determine the second anti-sound wave signal of the real-time noise of the corresponding fan through the preset secondary sound wave digital model.

[0043] Optionally, before calculating the root mean square value of the noise signal to obtain the third root mean square value, it further includes:

[0044] Intercept the noise signal within the human ear hearing frequency band.

[0045] Optionally, the secondary acoustic mathematical model is trained in the following manner:

[0046] Build a primary acoustic channel and a secondary acoustic channel; wherein, the primary acoustic channel sequentially includes a noise signal source, a microphone, and an error sensor at a preset position; the secondary acoustic channel sequentially includes a noise signal source, a microphone, a digital filter, a secondary speaker, and an error sensor;

[0047] Determine the first transfer function from the microphone to the error sensor in the primary acoustic channel;

[0048] Determine the second transfer function from the speaker to the error sensor in the secondary acoustic channel;

[0049] Use the digital filter to train the secondary acoustic model, and calculate the sum of the noise signals of the primary acoustic channel and the secondary acoustic channel received by the error sensor during the training process according to the first transfer function and the second transfer function until the sum of the noise signals is zero.

[0050] In a second aspect, an embodiment of the present invention further provides an active noise reduction device for a kitchen air conditioner for implementing the active noise reduction method for a kitchen air conditioner fan in the first aspect. A control module, a fan, and a secondary speaker are provided in the kitchen air conditioner, and an acceleration sensor is provided on the casing of the fan; both the acceleration sensor and the secondary speaker are electrically connected to the control module;

[0051] The acceleration sensor is used to detect the casing vibration signal of the fan;

[0052] The control module is used to predict the real-time noise signal of the fan according to the vibration signal and the preset noise prediction model; and determine the anti-sound wave signal of the real-time noise of the fan through the preset secondary sound wave digital model according to the real-time noise signal of the fan;

[0053] The secondary speaker is used to play an anti-phase sound wave signal for active noise reduction of the kitchen air conditioner.

[0054] Optionally, the kitchen air conditioner includes a refrigeration chamber and a heat dissipation chamber;

[0055] The secondary speaker includes a first secondary speaker and a second secondary speaker; the first secondary speaker is arranged in the refrigeration chamber; the second secondary speakers are all arranged in the heat dissipation chamber;

[0056] A refrigeration fan is also arranged in the refrigeration chamber, and a heat dissipation fan is also arranged in the heat dissipation chamber;

[0057] The acceleration sensor includes a first acceleration sensor and a second acceleration sensor. The first acceleration sensor is arranged on the housing of the refrigeration fan, and the second acceleration sensor is arranged on the housing of the heat dissipation fan;

[0058] The first acceleration sensor is used to detect the first vibration signal of the housing of the refrigeration fan;

[0059] The second acceleration sensor is used to detect the second vibration signal of the housing of the heat dissipation fan;

[0060] The control module is also used for:

[0061] According to the first vibration signal and a preset noise prediction model of the refrigeration fan, predict the first real-time noise signal of the refrigeration fan;

[0062] According to the second vibration signal and a preset noise prediction model of the heat dissipation fan, predict the second real-time noise signal of the heat dissipation fan;

[0063] Select the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determine the first anti-phase sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model;

[0064] The first secondary speaker in the refrigeration chamber where the refrigeration fan with the larger noise is located is used to play the first anti-phase sound wave signal, or the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with the larger noise is located plays the first anti-phase sound wave signal for primary active noise reduction of the kitchen air conditioner.

[0065] Optionally, an acoustic microphone sensor is arranged on the housing of the kitchen air conditioner;

[0066] The acoustic microphone sensor is used to collect the noise signal in the space where the kitchen air conditioner is located;

[0067] The control module is also used to select the one with the smaller noise among the first real-time noise signal and the second real-time noise signal when the noise signal is greater than a preset noise threshold, and determine the second anti-phase sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model;

[0068] The first secondary loudspeaker in the refrigeration cavity where the refrigeration fan with less noise is located is also used to play a second anti-phase sound wave signal, or the second secondary loudspeaker in the heat dissipation cavity where the heat dissipation fan with less noise is located is also used to play a second anti-phase sound wave signal, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0069] Optionally, the control module includes:

[0070] A central controller, configured to predict the real-time noise signal of the fan according to the vibration signal and a preset noise prediction model;

[0071] An active noise controller, electrically connected to the central controller, configured to determine the anti-phase sound wave signal of the real-time noise of the fan according to the real-time noise signal of the fan through a preset secondary sound wave digital model.

[0072] In a third aspect, an embodiment of the present invention further provides a kitchen air conditioner, including an active noise reduction device under different working conditions of the kitchen air conditioner in the second aspect.

[0073] An embodiment of the present invention provides a kitchen air conditioner and an active noise reduction method and device thereof under different working conditions, which are applied to a kitchen air conditioner provided with a fan and a secondary loudspeaker, and an acceleration sensor is arranged on the casing of the fan. The active noise reduction method includes: using the acceleration sensor to detect the casing vibration signal of the fan to obtain the casing vibration signal of the fan. According to the vibration signal and a preset noise prediction model, predict the real-time noise signal of the fan to grasp the law and characteristics of noise generation. According to the real-time noise signal of the fan, determine the anti-phase sound wave signal of the real-time noise of the fan through a preset secondary sound wave digital model, realizing targeted processing of the fan noise under different working conditions. Finally, use the secondary loudspeaker to play the anti-phase sound wave signal to perform active noise reduction on the kitchen air conditioner, so that it interferes with and cancels the original noise generated by the operation of the kitchen air conditioner, thereby effectively performing active noise reduction on the kitchen air conditioner. The embodiment of the present invention successfully solves the problem that the noise of the kitchen air conditioner is too loud during operation, seriously interfering with the communication and cooking experience of people in the kitchen, greatly reducing the noise level generated during the operation of the kitchen air conditioner, and significantly improving the comfort of the kitchen environment. Description of the Drawings

[0074] Figure 1 It is a schematic structural diagram of an active noise reduction device under different working conditions of a kitchen air conditioner provided by an embodiment of the present invention;

[0075] Figure 2 It is a schematic structural diagram of a casing of a kitchen air conditioner provided by an embodiment of the present invention;

[0076] Figure 3Schematic diagram of the circuit structure of an active noise reduction device for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention;

[0077] Figure 4 Flowchart of an active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention;

[0078] Figure 5 Flowchart of another active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention;

[0079] Figure 6 Flowchart of yet another active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention;

[0080] Figure 7 Flowchart of a training method for a noise prediction model provided by an embodiment of the present invention;

[0081] Figure 8 Flowchart of a training method for a secondary acoustic mathematical model provided by an embodiment of the present invention;

[0082] Figure 9 Schematic diagram of the primary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention;

[0083] Figure 10 Schematic diagram of the secondary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention;

[0084] Figure 11 Flow schematic diagram of the secondary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention;

[0085] In the figure:

[0086] 10, blower; 11, refrigeration blower; 12, heat dissipation blower; 20, secondary speaker; 21, first secondary speaker; 22, second secondary speaker; 30, refrigeration chamber; 32, evaporator; 40, heat dissipation chamber; 41, compressor; 43, condenser; 50, acceleration sensor; 51, first acceleration sensor; 52, second acceleration sensor; 53, acoustic microphone sensor; 61, air outlet; 62, display panel; 63, button. Detailed implementation manners

[0087] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. Additionally, it should be noted that for the sake of description, only parts related to the present invention are shown in the drawings, rather than all the structures.

[0088] The terms used in the embodiments of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. It should be noted that the orientation terms such as "upper", "lower", "left", and "right" described in the embodiments of the present invention are described from the angles shown in the drawings and should not be construed as limiting the embodiments of the present invention. In addition, in the context, it should also be understood that when it is mentioned that an element is formed "on" or "under" another element, it can not only be directly formed "on" or "under" another element, but also be indirectly formed "on" or "under" another element through an intermediate element. The terms "first", "second", etc. are only used for descriptive purposes and do not indicate any order, quantity, or importance, but are only used to distinguish different components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0089] The term "comprising" and its variants used in the present invention are open-ended, that is, "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment".

[0090] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish the corresponding contents and are not used to limit the order or interdependent relationship.

[0091] It should be noted that the modification of "one" and "multiple" mentioned in the present invention is illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly specified in the context, it should be understood as "one or more".

[0092] Figure 1 The figure is a schematic structural diagram of an active noise reduction device of a kitchen air conditioner under different working conditions provided for the embodiments of the present invention. Figure 2 The figure is a schematic structural diagram of a housing of a kitchen air conditioner provided for the embodiments of the present invention. Figure 3 The figure is a schematic circuit diagram of an active noise reduction device of a kitchen air conditioner under different working conditions provided for the embodiments of the present invention. As Figures 1-3 shown, the device includes a control module 70, a blower 10, and a secondary speaker 20. An acceleration sensor 50 is disposed on the housing of the blower 10; both the acceleration sensor 50 and the secondary speaker 20 are electrically connected to the control module 70; the acceleration sensor 50 is configured to detect the housing vibration signal of the blower 10; the control module 70 is configured to predict the real-time noise signal of the blower 10 according to the vibration signal and a preset noise prediction model; and determine the anti-phase sound wave signal of the real-time noise of the blower 10 through a preset secondary sound wave digital model according to the real-time noise signal of the blower 10; the secondary speaker 20 is configured to play the anti-phase sound wave signal to perform active noise reduction on the kitchen air conditioner.

[0093] Specifically, during the actual operation process, the control module 70 continuously monitors the kitchen air conditioner fan 10 through the acceleration sensor 50 installed outside the casing of the fan 10, captures the slight vibrations generated by the casing during the operation of the fan, and converts them into vibration signals. A noise prediction model is preset in the control module 70. After receiving the vibration signals, this model predicts the real-time noise signals of the fan 10, and calculates and determines the anti-sound wave signals of the real-time noise of the fan through a preset secondary sound wave digital model. These anti-sound wave signals are then transmitted to the corresponding secondary speakers 20. The secondary speakers 20 are distributed near each noise source in the kitchen air conditioner, such as the fan 10. After receiving the anti-sound wave signals transmitted from the control module, the secondary speakers 20 convert them into anti-sound waves and play them outwards. The anti-sound waves interfere with the original noise sound waves generated by the operation of the fan 10 in space. Utilizing the superposition characteristics of sound waves, the peaks and valleys of the waves are mutually cancelled, thereby reducing the noise generated during the operation of the kitchen air conditioner and creating a quiet and comfortable kitchen environment for users.

[0094] In the above technical solution, by setting the acceleration sensor 50 to capture the slight vibrations generated by the casing during the operation of the fan, predicting the real-time noise signals based on the vibrations generated by the casing, and cooperating with the secondary speakers 20 to achieve noise cancellation, active noise reduction is carried out for the kitchen air conditioner under different working conditions, effectively solving the problem of high operating noise of the kitchen air conditioner, improving the product's usage experience and market competitiveness, and having higher intelligence and accuracy compared with the traditional air conditioner noise reduction method.

[0095] In an optional embodiment, the kitchen air conditioner includes a refrigeration chamber 30 and a heat dissipation chamber 40. The secondary speakers include a first secondary speaker 21 and a second secondary speaker 22. The first secondary speaker 22 is arranged in the refrigeration chamber 30, and the second secondary speakers 22 are all arranged in the heat dissipation chamber 40. A refrigeration fan 11 is also arranged in the refrigeration chamber 30, and a heat dissipation fan 12, a compressor 41 and a condenser 43 are also arranged in the heat dissipation chamber 40. The acceleration sensor 50 includes a first acceleration sensor 51 and a second acceleration sensor 52. The first acceleration sensor 51 is arranged on the casing of the refrigeration fan 11, and the second acceleration sensor 52 is arranged on the casing of the heat dissipation fan 12; the first acceleration sensor 51 is used to detect the first vibration signal of the casing of the refrigeration fan 11; the second acceleration sensor 52 is used to detect the second vibration signal of the casing of the heat dissipation fan 12.

[0096] The control module 70 is further configured to: predict a first real-time noise signal of the refrigeration fan 10 according to the first vibration signal and a preset refrigeration fan noise prediction model; predict a second real-time noise signal of the cooling fan 10 according to the second vibration signal and a preset cooling fan noise prediction model; select the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determine a first anti-phase sound wave signal corresponding to the real-time noise of the corresponding fan 10 through a preset secondary sound wave digital model. The first secondary speaker 21 in the refrigeration chamber 30 where the refrigeration fan 11 with the larger noise is located is used to play the first anti-phase sound wave signal, or the second secondary speaker 22 in the cooling chamber 40 where the cooling fan 12 with the larger noise is located plays the first anti-phase sound wave signal to perform primary active noise reduction on the kitchen air conditioner.

[0097] Specifically, the first acceleration sensor 51 monitors the vibration generated by the refrigeration fan 11, converts this vibration into a first vibration signal, and transmits it to the control module 70. The second acceleration sensor 52 is disposed on the casing of the cooling fan 12, and in the same manner, transmits the second vibration signal generated by the operation of the cooling fan 12 to the control module 70.

[0098] After receiving the above two sets of vibration signals, the control module 70 analyzes and processes the first vibration signal and the second vibration signal respectively based on the preset refrigeration fan noise prediction model and the cooling fan noise prediction model inside, and predicts the first real-time noise signal corresponding to the refrigeration fan 11 and the second real-time noise signal corresponding to the cooling fan 12. Subsequently, the control module 70 compares these two real-time noise signals and selects the one with the larger noise value. If the first real-time noise signal is larger, indicating that the noise generated by the refrigeration fan 11 is more prominent, the control module 70 transmits the first anti-phase sound wave signal to the first secondary speaker 21, and the first secondary speaker 21 in the refrigeration chamber 30 converts it into a sound wave and plays it into the refrigeration chamber 30, interfering with the original noise sound wave generated by the refrigeration fan 11 to achieve noise reduction. On the contrary, if the second real-time noise signal is larger, the control module 70 will send the first anti-phase sound wave signal to the second secondary speaker 22, and the noise generated by the cooling fan 12 is cancelled through the second secondary speaker 22 in the cooling chamber 40, thereby completing the primary active noise reduction of the kitchen air conditioner, effectively reducing the overall noise level during the operation of the kitchen air conditioner, and improving the comfort of the user in the kitchen environment.

[0099] Continue to refer to Figure 1 and Figure 2 In an alternative embodiment, an acoustic microphone sensor 53 is provided on the outer shell of the kitchen air conditioner;

[0100] The acoustic microphone sensor 53 is configured to collect the noise signal in the space where the kitchen air conditioner is located;

[0101] The control module 70 is further configured to select the smaller one of the first real-time noise signal and the second real-time noise signal when the noise signal is greater than a preset noise threshold, and determine a second anti-sound wave signal corresponding to the real-time noise of the corresponding fan 10 through a preset secondary sound wave digital model;

[0102] The first secondary loudspeaker 21 in the refrigeration chamber 30 where the refrigeration fan 11 with smaller noise is located is further configured to play the second anti-sound wave signal, or the second secondary loudspeaker 22 in the heat dissipation chamber 40 where the heat dissipation fan 12 with smaller noise is located is further configured to play the second anti-sound wave signal, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0103] Wherein, the noise signal in the space where the kitchen air conditioner is located can be understood as the noise after primary active noise reduction of the noise of the kitchen air conditioner. Here, the noise of the kitchen air conditioner after primary active noise reduction is detected, and the purpose is to judge whether the noise after primary active noise reduction can meet the acceptable range of the user. Correspondingly, a noise threshold can be preset for comparison and judgment.

[0104] Specifically, the acoustic microphone sensor 53 installed on the outer shell of the kitchen air conditioner will capture the overall noise generated by the kitchen air conditioner after primary active noise reduction. If the noise is less than the preset noise threshold, it indicates that the kitchen air conditioner only turns on primary active noise reduction, that is, only reducing the noise of the louder one of the refrigeration fan 11 and the heat dissipation fan 12 can reduce the noise generated by the kitchen air conditioner to an acceptable range.

[0105] On the contrary, after the kitchen air conditioner completes primary active noise reduction, the acoustic microphone sensor 53 installed on the outer shell of the kitchen air conditioner continuously captures the noise and converts it into a noise signal and transmits it to the control module 70. The control module 70 continuously receives and analyzes the noise signal after primary active noise reduction. Once it is determined that the noise signal is greater than the preset noise threshold, it means that the noise in the current kitchen environment still does not reach the ideal quiet level after primary active noise reduction, and further noise reduction measures need to be taken.

[0106] At this time, the control module 70 controls the loudspeaker 20 corresponding to the fan 10 with larger noise to play the first anti-sound wave signal, and the loudspeaker 20 corresponding to the fan 10 with smaller noise to play the second anti-sound wave signal, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0107] Exemplarily, assuming that the noise of the refrigeration fan 11 is relatively small and the noise of the heating fan 12 has been neutralized in the primary active noise reduction, the control module 70 will generate a corresponding second anti-sound wave signal according to the real-time noise characteristics of the refrigeration fan 11 based on the preset secondary sound wave digital model, and transmit it to the first secondary speaker 21 in the refrigeration chamber 30. The first secondary speaker 21 immediately converts the received second anti-sound wave signal into sound waves and plays them in the refrigeration chamber 30. During this process, the second anti-sound wave interferes with the relatively small noise sound waves generated by the operation of the refrigeration fan 11, further reducing the impact of the noise generated by the refrigeration fan 11 on the kitchen environment.

[0108] Conversely, if it is assumed that the noise of the heating fan 12 is relatively small and the noise of the refrigeration fan 11 has been neutralized in the primary active noise reduction, the control module 70 will send the generated second anti-sound wave signal to the second secondary speaker 22 in the heat dissipation chamber 40. The sound waves played by the second secondary speaker 22 cancel out the relatively small noise sound waves generated by the heat dissipation fan 12, thereby achieving the secondary active noise reduction of the kitchen air conditioner. Through this combination of primary and secondary active noise reduction, the kitchen air conditioner can more accurately and comprehensively reduce the noise generated by its own operation, creating a quieter and more comfortable kitchen space for users.

[0109] Continue to refer to Figure 3 , in an optional embodiment, the control module 70 includes: a central controller 71, configured to predict the real-time noise signal of the fan 10 according to the vibration signal and the preset noise prediction model;

[0110] An active noise controller 72, electrically connected to the central controller 71, configured to determine the anti-sound wave signal of the real-time noise of the fan 10 according to the real-time noise signal of the fan 10 through the preset secondary sound wave digital model.

[0111] Specifically, during the operation of the kitchen air conditioner, the acceleration sensor 50 installed on the housing of the fan 10 monitors the vibration of the housing of the fan 10 in real time and transmits the collected vibration signal to the control module 70.

[0112] In the control module 70, the central controller 71 receives these vibration signals. A noise prediction model is pre-stored in the central controller 71. This model is a real-time noise signal prediction model trained based on a fan vibration signal data set. Based on this model, the central controller 71 analyzes and processes the input vibration signals, thereby predicting the real-time noise signal of the fan 10 in the current operating state.

[0113] After predicting the real-time noise signal, the central controller 71 transmits the signal to the active noise controller 72. The active noise controller 72 is built-in with a preset secondary sound wave digital model, which can perform an inverting process on the noise signal according to the received real-time noise signal of the fan, ensuring that when the generated anti-sound wave signal meets the original noise signal in space, they can interfere and cancel each other out.

[0114] After the active noise controller 72 determines the anti-sound wave signal based on the secondary sound wave digital model, the active noise controller 72 transmits it to the secondary speaker 20. The secondary speaker 20 converts the received electrical signal into a sound wave and plays it out, superimposing it with the original noise generated by the fan 10. Using the principle of sound wave interference, active noise reduction processing of the fan noise is achieved, effectively reducing the noise generated during the operation of the kitchen air conditioner and improving the operation quality of the kitchen air conditioner and the user experience.

[0115] In addition, as Figures 1-2 shown, the embodiment of the present invention also provides a kitchen air conditioner, including the active noise reduction device under different working conditions of the kitchen air conditioner in the above embodiment. Since this kitchen air conditioner includes the active noise reduction device in any of the above embodiments, it has the same or corresponding beneficial effects as those in the above embodiments, which will not be elaborated here.

[0116] Regarding the active noise reduction device and the kitchen air conditioner under different working conditions of the kitchen air conditioner provided in the above embodiments, the present invention also provides an active noise reduction method for the kitchen air conditioner under different working conditions based on this device. Figure 4 is a flowchart of an active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention. First, refer to Figure 1 , there is a fan 10 and a secondary speaker 20 installed in the kitchen air conditioner, and an acceleration sensor 50 is arranged on the casing of the fan 10. Based on this kitchen air conditioner, refer to Figure 4 , the active noise reduction method may include the following specific steps:

[0117] S110. Detect the casing vibration signal of the fan using the acceleration sensor.

[0118] Among them, the casing vibration signal can be understood as the physical signal generated by the mechanical vibration of the casing of the fan 10 during its operation. This signal includes information such as vibration frequency and amplitude, and the operating state of the fan 10 can be indirectly reflected through the above information.

[0119] Specifically, the acceleration sensor 50 is installed on the surface of the casing of the fan 10, used to capture the minute vibration generated by the casing during the operation of the fan 10 and transmit it to the control module 70 in real time for subsequent processing.

[0120] S120. Predict the real-time noise signal of the fan according to the vibration signal and a preset noise prediction model.

[0121] Among them, the noise prediction model can be understood as a mapping relationship between the vibration signal of the fan 10 housing and the actually generated noise constructed based on a large amount of experimental data and theoretical analysis. The real-time noise signal can be understood as the representation of the noise actually generated by the fan 10 at the current operating moment at the electrical signal level. Exemplarily, by analyzing the vibration and noise data of the fan 10 under a large number of different working conditions, methods such as machine learning can be used to construct the mapping relationship between the housing vibration signal and the actually generated noise.

[0122] Specifically, after the control module 70 receives the housing vibration signal from the acceleration sensor 50, it inputs the housing vibration signal into the preset noise prediction model, thereby predicting the real-time noise signal of the fan 10 at the current moment.

[0123] S130. According to the real-time noise signal of the fan, determine the anti-sound wave signal of the real-time noise of the fan through a preset infrasonic wave digital model.

[0124] Among them, the infrasonic wave digital model can be understood as a mathematical model based on acoustic principles and signal processing technologies for generating anti-sound waves that can cancel the original noise; the anti-sound wave signal can be understood as a sound wave signal that is the same as the real-time noise signal of the fan 10 in terms of frequency and amplitude but has the opposite phase.

[0125] Specifically, after the control module 70 obtains the real-time noise signal of the fan 10, it inputs it into the preset infrasonic wave digital model, calculates an anti-sound wave signal with a phase difference of 180 degrees from the original noise signal according to the model, and transmits the anti-sound wave signal to the secondary speaker 20.

[0126] S140. Use the secondary speaker to play the anti-sound wave signal to actively reduce the noise of the kitchen air conditioner.

[0127] Specifically, the anti-sound wave signal generated by the infrasonic wave digital model is transmitted to the secondary speaker 20. The secondary speaker 20 converts the received electrical signal into a sound wave form and plays it into the space around the kitchen air conditioner. When the anti-sound wave played by the secondary speaker 20 meets the original noise sound wave generated by the fan 10 in space, due to their opposite phases, their wave crests and wave troughs are superimposed on each other. According to the principle of sound wave interference, the superimposed sound waves cancel each other out, thereby effectively reducing the noise intensity generated by the operation of the kitchen air conditioner and achieving active noise reduction of the kitchen air conditioner, creating a quieter and more comfortable kitchen environment for users.

[0128] An embodiment of the present invention discloses a kitchen air conditioner and an active noise reduction method and device thereof under different working conditions. A blower and a secondary loudspeaker are arranged in the kitchen air conditioner, and an acceleration sensor is arranged on the housing of the blower. The active noise reduction method includes: detecting the housing vibration signal of the blower by using the acceleration sensor; predicting the real-time noise signal of the blower according to the vibration signal and a preset noise prediction model; determining the anti-phase sound wave signal of the real-time noise of the blower through a preset secondary sound wave digital model according to the real-time noise signal of the blower; and playing the anti-phase sound wave signal by using the secondary loudspeaker to perform active noise reduction on the kitchen air conditioner. The real-time working condition of the kitchen air conditioner is indirectly obtained by determining the housing vibration signal of the kitchen air conditioner, and the operating state of the air conditioner is determined, such as refrigeration, heating, and the intensity level of refrigeration and heating, etc. By determining the blower that is in the working state currently according to the real-time working condition of the kitchen air conditioner, the source blower generating noise is identified. The real-time noise signal is obtained through the noise prediction model, providing the original material for subsequent noise processing and ensuring the reliability of the noise reduction effect. The anti-phase sound wave signal of the real-time noise of the blower is determined through the preset secondary sound wave digital model, realizing targeted noise reduction starting from the characteristics of the noise source. The anti-phase processed noise signal is played by the secondary loudspeaker to perform active noise reduction on the kitchen air conditioner under the current working condition, interfering with and canceling the original noise. The embodiment of the present invention solves the problems that the kitchen air conditioner has a large noise during operation, seriously disturbing the communication among people in the kitchen and the cooking experience, reduces the noise level generated during the operation of the kitchen air conditioner, and realizes the active noise reduction of the noise of the kitchen air conditioner.

[0129] Figure 5 is a flowchart of another active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention. First, refer to Figure 1 and Figure 2 , in the embodiment of the present invention, the kitchen air conditioner includes a refrigeration chamber 30 and a heat dissipation chamber 40; the secondary loudspeaker 20 includes a first secondary loudspeaker 21 and a second secondary loudspeaker 22; the first secondary loudspeaker 21 is arranged in the refrigeration chamber; the second secondary loudspeakers 22 are all arranged in the heat dissipation chamber 40; a refrigeration blower 11 is further arranged in the refrigeration chamber 30, and a heat dissipation blower 12 is further arranged in the heat dissipation chamber 40; the acceleration sensor 50 includes a first acceleration sensor 51 and a second acceleration sensor 52, the first acceleration sensor 51 is arranged on the housing of the refrigeration blower 11, and the second acceleration sensor 52 is arranged on the housing of the heat dissipation blower 12.

[0130] Based on the above kitchen air conditioner, refer to Figure 5, The embodiments of the present invention are refinements or optimizations of the above embodiments. Specifically, for "S110. Detect the vibration signal of the fan casing using an acceleration sensor" in the above embodiments, it can be specifically refined as: Detect the first vibration signal of the refrigeration fan casing using a first acceleration sensor; Detect the second vibration signal of the cooling fan casing using a second acceleration sensor.

[0131] For "S120. Predict the real-time noise signal of the fan according to the vibration signal and a preset noise prediction model" in the above embodiments, it can be specifically refined as: Predict the first real-time noise signal of the refrigeration fan according to the first vibration signal and a preset refrigeration fan noise prediction model; Predict the second real-time noise signal of the cooling fan according to the second vibration signal and a preset cooling fan noise prediction model.

[0132] For "S130. Determine the anti-sound wave signal of the real-time noise of the fan through a preset secondary sound wave digital model according to the real-time noise signal of the fan" in the above embodiments, it can be specifically refined as: Select the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determine the first anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model. For "S140. Play the anti-sound wave signal using a secondary speaker to perform active noise reduction on the kitchen air conditioner." in the above embodiments, it can be specifically refined as: Play the first anti-sound wave signal using a first secondary speaker in the refrigeration chamber where the refrigeration fan with the larger noise is located, or play the first anti-sound wave signal using a second secondary speaker in the cooling chamber where the cooling fan with the larger noise is located to perform primary active noise reduction on the kitchen air conditioner.

[0133] For the content not detailed in this embodiment, please refer to the previous embodiment.

[0134] As Figure 5 shown, another active noise reduction method for the kitchen air conditioner under different working conditions may include the following specific steps:

[0135] S210. Detect the first vibration signal of the refrigeration fan casing using a first acceleration sensor.

[0136] Among them, the first vibration signal can be understood as a physical signal formed by the mechanical vibration of the casing of the refrigeration fan 11 during operation due to various factors such as motor drive, blade rotation, and air flow impact. It reflects the working condition of the refrigeration fan 11 from the side.

[0137] Specifically, the first acceleration sensor 51 is installed on the casing of the refrigeration fan 11. When the refrigeration fan 11 starts to operate, the detection element in the first acceleration sensor 51 undergoes corresponding displacement or deformation as the casing vibrates, and then generates the first vibration signal.

[0138] S211. Detect the second vibration signal of the housing of the cooling fan using the second acceleration sensor.

[0139] Among them, the second vibration signal can be understood as a physical signal formed by the mechanical vibration of the housing of the cooling fan 12 during operation due to various factors such as motor drive, blade rotation, and air flow impact. It reflects the working condition of the cooling fan 12 from the side.

[0140] Specifically, the second acceleration sensor 52 is installed on the housing of the cooling fan 12, and its detection element displaces or deforms as the housing vibrates, thereby outputting the second vibration signal.

[0141] S221. Predict the first real-time noise signal of the cooling fan according to the first vibration signal and the preset cooling fan noise prediction model.

[0142] Among them, the first real-time noise signal can be understood as the noise actually generated by the cooling fan 11 at the current moment, which is a specific representation presented in the form of an electrical signal.

[0143] Specifically, after receiving the first vibration signal transmitted by the first acceleration sensor 51, the control module 70 inputs this signal into the preset cooling fan noise prediction model, and predicts the first real-time noise signal generated by the cooling fan 11 in the current operating state according to this model.

[0144] S222. Predict the second real-time noise signal of the cooling fan according to the second vibration signal and the preset cooling fan noise prediction model.

[0145] Among them, the second real-time noise signal can be understood as the noise actually generated by the cooling fan 12 at the current moment, which is a specific representation presented in the form of an electrical signal.

[0146] Specifically, after receiving the second vibration signal transmitted by the second acceleration sensor 52, the control module 70 inputs this signal into the preset cooling fan noise prediction model, and predicts the second real-time noise signal generated by the cooling fan 12 in the current operating state according to this model.

[0147] S231. Select the one with the greater noise among the first real-time noise signal and the second real-time noise signal, and determine the first anti-sound wave signal of the real-time noise of the corresponding fan through the preset secondary sound wave digital model.

[0148] Among them, the first anti-sound wave signal can be understood as a sound wave signal that is exactly the same as the real-time noise signal generated by the fan 10 with the greater noise in terms of frequency and amplitude, but with the opposite phase.

[0149] Specifically, after the control module 70 obtains the first real-time noise signal (from the refrigeration fan 11) and the second real-time noise signal (from the heat dissipation fan 12), it will compare the noise intensities of these two signals, identify the one with the greater noise, input it into a preset secondary acoustic wave digital model, calculate a first anti-acoustic wave signal with a 180-degree phase difference from the original noise signal according to the model, and transmit the first anti-acoustic wave signal to the secondary speaker 20.

[0150] Exemplarily, assuming that the intensity of the first real-time noise signal is higher, that is, the noise generated by the refrigeration fan 11 is more prominent, the control module 70 will use the first real-time noise signal as the input, import it into the preset secondary acoustic wave digital model, and then obtain the first anti-acoustic wave signal.

[0151] S241. Play the first anti-acoustic wave signal through the first secondary speaker in the refrigeration chamber where the refrigeration fan with greater noise is located, or play the first anti-acoustic wave signal through the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with greater noise is located, so as to perform primary active noise reduction on the kitchen air conditioner.

[0152] Specifically, after the control module 70 determines the first anti-acoustic wave signal, it will send a playback instruction to the corresponding secondary speaker 20 according to the fan 10 with greater noise. If it is determined that the noise generated by the refrigeration fan 11 is greater, then the control module 70 will transmit the first anti-acoustic wave signal to the first secondary speaker 21 in the refrigeration chamber 30. After receiving the signal, the first secondary speaker 21 converts the electrical signal into an acoustic wave signal and plays it into the refrigeration chamber 30 and the surrounding space. These anti-acoustic waves meet the original noise acoustic waves generated by the refrigeration fan 11, and through the superposition of wave crests and wave troughs, noise cancellation is achieved, thereby reducing the overall noise level of the kitchen air conditioner.

[0153] Conversely, if it is found through comparison that the noise generated by the heat dissipation fan 12 is more prominent, the control module 70 will send the first anti-acoustic wave signal to the second secondary speaker 22 in the heat dissipation chamber 40. The second secondary speaker 22 converts the received electrical signal into an acoustic wave and plays it into the heat dissipation chamber 40 and its surrounding environment, interfering and canceling with the original noise generated by the heat dissipation fan 12 to complete primary active noise reduction.

[0154] In the embodiment of the present invention, by comparing the first real-time noise signal and the second real-time noise signal, the fan that generates more prominent noise is determined, and the noise generated by this fan is processed specifically. Thereby, the noise reduction cost is reduced and the cost-effectiveness is improved.

[0155] In an optional embodiment, an acoustic microphone sensor 53 is further provided on the housing of the kitchen air conditioner; after "S241. Play the first anti-phase sound wave signal through the first secondary speaker in the refrigeration chamber where the refrigeration fan with a relatively high noise is located, or play the first anti-phase sound wave signal through the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with a relatively high noise is located, so as to perform primary active noise reduction on the kitchen air conditioner." in the above embodiment, the following is further included:

[0156] S250. Use the acoustic microphone sensor to collect the noise signal in the space where the kitchen air conditioner is located.

[0157] Specifically, as Figure 2 shown, the microphone sensor 53 provided near the air outlet of the kitchen air conditioner is used to collect the noise signal in the space where the kitchen air conditioner is located after primary active noise reduction.

[0158] S260. When the noise signal is greater than the preset noise threshold, select the smaller one of the first real-time noise signal and the second real-time noise signal, and determine the second anti-phase sound wave signal of the real-time noise of the corresponding fan through the preset secondary sound wave digital model.

[0159] Specifically, after the kitchen air conditioner completes primary active noise reduction, the acoustic microphone sensor 53 installed on the housing of the kitchen air conditioner continuously captures the noise and converts it into a noise signal to be transmitted to the control module 70. The control module 70 continuously receives and analyzes the noise signal after primary active noise reduction. Once it determines that the noise signal is greater than the preset noise threshold, it means that the noise in the current kitchen environment still does not reach the ideal quiet level after primary active noise reduction, and further noise reduction measures need to be taken.

[0160] S270. Play the second anti-phase sound wave signal through the first secondary speaker in the refrigeration chamber where the refrigeration fan with a relatively low noise is located, or play the second anti-phase sound wave signal through the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with a relatively low noise is located, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0161] Specifically, when the noise signal is greater than the preset noise threshold, the control module 70 controls the speaker 20 corresponding to the fan 10 with a relatively high noise to play the first anti-phase sound wave signal, and the speaker 20 corresponding to the fan 10 with a relatively low noise to play the second anti-phase sound wave signal, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0162] Exemplarily, when the fan 10 with a relatively low noise is the refrigeration fan 11, use the first secondary speaker 21 in the refrigeration chamber 30 to play the second anti-phase sound wave signal; when the fan 10 with a relatively low noise is the heat dissipation fan 12, use the second secondary speaker 21 in the heat dissipation chamber 40 to play the second anti-phase sound wave signal, so as to perform secondary active noise reduction on the kitchen air conditioner.

[0163] In the embodiment of the present invention, through the combination of primary and secondary active noise reduction, the noise generated during the operation of the kitchen air conditioner is reduced more precisely and comprehensively, creating a quieter and more comfortable kitchen space for users.

[0164] Further, "S260. When the noise signal is greater than the preset noise threshold, select the smaller one of the first real-time noise signal and the second real-time noise signal, and determine the second anti-sound wave signal of the real-time noise of the corresponding fan through the preset secondary sound wave digital model" may specifically include the following steps:

[0165] S261. Calculate the root mean square value of the noise signal to obtain the third root mean square value.

[0166] Among them, the third root mean square value can be understood as a quantitative representation of the noise signal intensity in the space where the kitchen air conditioner is located collected by the acoustic microphone sensor.

[0167] Specifically, within a period of time, calculate the square values of the noise signals at different time points, and average these square values to obtain the third root mean square value.

[0168] Exemplarily, assume that the values of the noise signal at discrete time points t1, t2,..., t n are x(t1), x(t2),..., x(t n ). First, perform a square operation on the noise signal values at each time point to obtain x 2 (t1), x 2 (t2),..., x 2 (t n ). Then calculate the average value of these square values, that is to obtain the third root mean square value.

[0169] S262. When the third root mean square value is greater than the preset root mean square value of the noise, calculate the root mean square values of the first real-time noise signal and the second real-time noise signal respectively to obtain the first root mean square value and the second root mean square value.

[0170] Among them, the first root mean square value can be understood as the root mean square of the first real-time noise signal generated by the refrigeration fan; the second root mean square value can be understood as the root mean square of the intensity of the second real-time noise signal generated by the heat dissipation fan.

[0171] Specifically, when the control module 70 determines that the third root mean square value is greater than the preset root mean square value of the noise, it means that the noise intensity in the current space where the kitchen air conditioner is located exceeds the expected range, and it is necessary to further analyze the respective noise contributions of the refrigeration fan 11 and the heat dissipation fan 12. At this time, the control module 70 calculates the first root mean square value and the second root mean square value in sequence, providing data support for subsequent determination of the relatively smaller noise source and generation of targeted anti-sound wave signals.

[0172] S263. Select the smaller one of the first root mean square value and the second root mean square value, and determine the second anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model.

[0173] Specifically, after the control module 70 obtains the first root mean square value and the second root mean square value, it compares the two. If the first root mean square value is less than the second root mean square value, it indicates that the noise generated by the refrigeration fan 11 is relatively small but still has a certain impact on the overall environment. The control module 70 takes the first real-time noise signal corresponding to the first root mean square value as the input and imports it into the preset secondary sound wave digital model to generate the second anti-sound wave signal. On the contrary, if the second root mean square value is smaller, that is, the noise of the heat dissipation fan 12 is relatively small, the control module 70 inputs the second real-time noise signal into the secondary sound wave digital model to generate the second anti-sound wave signal for the relatively small noise of the heat dissipation fan 12.

[0174] Figure 6 is a flowchart of another active noise reduction method for a kitchen air conditioner under different working conditions provided by an embodiment of the present invention. Refer to Figure 6 , the embodiment of the present invention is a refinement or optimization of the above embodiment. Specifically, for "S231. Select the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determine the first anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model" in the above embodiment, it can be specifically refined as: calculate the root mean square values of the first real-time noise signal and the second real-time noise signal respectively to obtain the first root mean square value and the second root mean square value; compare the first root mean square value and the second root mean square value to obtain the larger one, and determine the first anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model.

[0175] For the content not detailed in this embodiment, please refer to the previous embodiment.

[0176] As Figure 6 shown, another active noise reduction method for a kitchen air conditioner under different working conditions may include the following specific steps:

[0177] S310. Use the first acceleration sensor to detect the first vibration signal of the refrigeration fan housing.

[0178] S311. Use the second acceleration sensor to detect the second vibration signal of the heat dissipation fan housing.

[0179] S321. Predict the first real-time noise signal of the refrigeration fan according to the first vibration signal and a preset refrigeration fan noise prediction model.

[0180] S322. Predict the second real-time noise signal of the heat dissipation fan according to the second vibration signal and a preset heat dissipation fan noise prediction model.

[0181] S331. Calculate the root mean square values of the first real-time noise signal and the second real-time noise signal respectively to obtain the first root mean square value and the second root mean square value.

[0182] Specifically, the control module 70 calculates the first root mean square value and the second root mean square value in sequence, providing data support for subsequent determination of the relatively smaller noise source and generation of targeted anti-sound wave signals.

[0183] S332. Compare the first root mean square value and the second root mean square value, obtain the larger one, and determine the first anti-sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model.

[0184] Specifically, after the control module 70 obtains the first root mean square value and the second root mean square value, it compares the two. If the first root mean square value is greater than the second root mean square value, it indicates that the noise generated by the refrigeration fan 11 is relatively larger and has a greater impact on the overall environment. The control module 70 takes the first real-time noise signal corresponding to the first root mean square value as the input and imports it into the preset secondary sound wave digital model to generate the first anti-sound wave signal. On the contrary, if the second root mean square value is larger, that is, the noise of the heat dissipation fan 12 is relatively larger, the control module 70 inputs the second real-time noise signal into the secondary sound wave digital model to generate the second anti-sound wave signal for the relatively larger noise of the heat dissipation fan 12.

[0185] S341. Play the first anti-sound wave signal through the first secondary speaker in the refrigeration cavity where the refrigeration fan with larger noise is located, or play the first anti-sound wave signal through the second secondary speaker in the heat dissipation cavity where the heat dissipation fan with larger noise is located to perform primary active noise reduction on the kitchen air conditioner.

[0186] Specifically, when the noise signal is greater than the preset noise threshold, the control module 70 controls the speaker 20 corresponding to the fan 10 with larger noise to play the first anti-sound wave signal to perform secondary active noise reduction on the kitchen air conditioner.

[0187] Exemplarily, when the noise of the refrigeration fan 11 is relatively large, the first secondary speaker 21 in the refrigeration cavity 30 plays the first anti-sound wave signal. On the contrary, when the noise of the heat dissipation fan 12 is relatively large, the second secondary speaker 22 in the heat dissipation cavity 40 plays the first anti-sound wave signal to perform primary active noise reduction on the kitchen air conditioner.

[0188] In the embodiment of the present invention, by calculating the root mean square value of the noise signal, short-term accidental noise interference is effectively avoided. Based on this, anti-sound wave signals are generated, which can accurately target the actual noise of the fan, greatly improving the stability and effectiveness of active noise reduction and enhancing the noise reduction effect of the kitchen air conditioner.

[0189] Optionally, before "S331. Calculate the root mean square values of the first real-time noise signal and the second real-time noise signal respectively to obtain a first root mean square value and a second root mean square value" in the above embodiments, the method further includes:

[0190] Intercept the first real-time noise signal and the second real-time noise signal within the human ear hearing frequency band range.

[0191] Specifically, the sound frequency range that the human ear can perceive is usually between 20 Hz and 20 kHz. In order to make the active noise reduction more targeted and conform to the auditory characteristics of the human ear, it is necessary to intercept the frequency bands of the first real-time noise signal (from the refrigeration fan 11) and the second real-time noise signal (from the heat dissipation fan 12).

[0192] Exemplarily, a band-pass filter is preset in the control module 70, and its passband range is set to 20 Hz - 20 kHz. When the first real-time noise signal and the second real-time noise signal pass through the band-pass filter, the signal components outside the human ear hearing frequency band range are filtered out, and only the signals within the 20 Hz - 20 kHz frequency band are retained, thereby completing the interception of the first real-time noise signal.

[0193] By intercepting the first real-time noise signal and the second real-time noise signal within the human ear hearing frequency band range in the embodiments of the present invention, it is possible to perform noise reduction processing on the noise that can be perceived by the human ear, improve the effect of the active noise reduction system. At the same time, unnecessary processing of signals that the human ear cannot hear is avoided, and the efficiency of the active noise reduction system is improved.

[0194] Figure 7 is a flowchart of a method for training a noise prediction model provided by an embodiment of the present invention. As Figure 7 shown, the noise prediction model is trained in the following manner:

[0195] S410. Experimentally obtain a fan vibration signal data set, where the fan vibration signal data set includes multiple vibration signal samples and the corresponding fan real-time noise samples of the vibration signal samples.

[0196] Specifically, referring to Figure 1 , an acceleration sensor 50 is provided on the casing of the fan 10. The acceleration sensor 50 synchronously records the fan vibration signal at regular time intervals, and each recorded vibration signal is a vibration signal sample. Similarly, by setting a microphone near the fan 10 to capture the noise generated during the operation of the fan in real time, the noise in the corresponding time period of each vibration signal sample constitutes the fan real-time noise sample.

[0197] S420. Use the fan vibration signal data set to train the neural network model to obtain a noise prediction model.

[0198] Specifically, the noise prediction model is trained as follows:

[0199] Obtain a dataset of fan vibration signals; the dataset of fan vibration signals includes multiple vibration signal samples and corresponding real-time fan noise samples; train a neural network model based on the vibration signal samples and the corresponding real-time fan noise samples to obtain a pre-trained model.

[0200] Use the pre-trained model to attempt to predict the real-time fan noise.

[0201] Calculate the error between the prediction result and the actual output, for example, use a loss function such as mean square error to measure. Then use the backpropagation algorithm to propagate the error from the output layer back to the input layer, and adjust the weight parameters of each layer in the neural network according to the error, so that the prediction result of the model gradually approaches the real-time fan noise.

[0202] When the performance of the model on the training set and the validation set reaches a certain level, the output neural network model is the noise prediction model.

[0203] The embodiment of the present invention further illustrates the training process of the noise prediction model, improves the technical system of the entire active noise reduction system for kitchen air conditioners, and makes it more reliable and effective in practical applications.

[0204] Figure 8 It is a flowchart of a training method for a secondary acoustic mathematical model provided by an embodiment of the present invention.

[0205] Figure 9 It is a schematic diagram of the primary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention.

[0206] Figure 10 It is a schematic diagram of the secondary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention. Figure 11 It is a schematic flow diagram of the secondary acoustic channel of a secondary acoustic mathematical model provided by an embodiment of the present invention.

[0207] Refer to Figure 8 , the secondary acoustic mathematical model is trained as follows:

[0208] S510. Build a primary acoustic channel and a secondary acoustic channel; wherein, the primary acoustic channel sequentially includes a noise signal source, a microphone, and an error sensor at a preset position; the secondary acoustic channel sequentially includes a noise signal source, a microphone, a digital filter, a secondary speaker, and an error sensor.

[0209] Specifically, refer to Figure 9 and Figure 11, in the primary acoustic channel, the noise signal source is the source that generates noise. The microphone is used to collect the noise emitted by the noise signal source, convert the acoustic signal into an electrical signal, and mark the output signal as X(t), and then transmit it to the ANC controller. After receiving the noise signal X(t) from the microphone, the digital filter in the ANC controller extracts the characteristics of the noise signal and analyzes and processes it to generate a control signal Y(t) for driving the speaker to emit corresponding sound waves. The speaker is used to receive the control signal Y(t) output by the ANC controller, convert the electrical signal into a sound wave signal and play it out, and this sound wave is used to cancel the noise in the environment. The error sensor is used to detect the remaining noise situation in the environment after the noise reduction process by the speaker, and feedback the detected signal to the ANC controller so that the ANC controller can adjust the output signal according to the actual noise reduction effect and optimize the noise reduction performance.

[0210] S520. Determine the first transfer function between the microphone and the error sensor in the primary acoustic channel.

[0211] Among them, refer to Figure 9 and Figure 11 , H r (Z) represents the transfer function of the channel between the noise signal and the microphone; the first transfer function H p (Z) is the transfer function between the microphone and the error sensor. This part is the primary path, that is, the path of the noise from the microphone to the error sensor, including the delay, attenuation and other characteristics of the acoustic path.

[0212] Specifically, when actually determining H r (Z), first, a suitable excitation signal needs to be set in this channel, which can usually be the signal emitted by a noise signal source with known characteristics. After the microphone collects this excitation signal, the error sensor will receive the signal propagated through this channel. By comparing the input signal collected by the microphone and the output signal received by the error sensor, using signal processing and system identification methods, such as using the Fourier transform to convert the time-domain signal into the frequency-domain signal, analyzing the gain and phase changes of different frequency components, so as to determine the specific expression of H r (Z).

[0213] S530. Determine the second transfer function between the speaker and the error sensor in the secondary acoustic channel.

[0214] Among them, refer to Figure 10 and Figure 11 , H r (Z) represents the transfer function of the channel between the noise signal and the microphone; the second transfer function H s(Z) represents the transfer function of the secondary channel between the speaker and the error sensor. This part refers to the secondary path, that is, the secondary acoustic digital model, and its determining factors are related to the environment.

[0215] Specifically, to determine H s (Z) is similar to the method of determining H r (Z). First, a test signal with known characteristics is emitted by the speaker, and the error sensor receives the signal propagated through this channel. By using methods such as frequency-domain analysis on the input and output signals, determine the gain and phase change of the signal by this channel at different frequencies, and then obtain the specific form of H s (Z).

[0216] S540. Use a digital filter to train the secondary acoustic model, and calculate the sum of the noise signals of the primary acoustic channel and the secondary acoustic channel received by the error sensor during the training process according to the first transfer function and the second transfer function until the sum of the noise signals is zero.

[0217] Specifically, at the beginning of the training, the digital filter W(Z) first adopts a set of initial tap coefficients. The noise signal P(t) is transmitted to the microphone through H r (Z) to generate a signal X(t). The signal X(t) is processed by the digital filter W(Z) to generate a signal Y(t). The signal Y(t) then passes through H s (Z) to reach the error sensor and generate a signal S(t). At the same time, X(t) will also pass through H p (Z) to generate a signal d(n). The signal e(n) received by the error sensor is the sum of the noise signals of the primary acoustic channel and the secondary acoustic channel, that is, e(n) = S(t) + d(n). During the training process, use the error signal e(n) to adjust the tap coefficients of the digital filter W(Z) through an adaptive algorithm (such as the least mean square algorithm). According to the magnitude and direction of the error signal, continuously modify the parameters of the filter to make the error signal e(n) gradually decrease. Continue this adjustment process, repeatedly calculate the sum of the noise signals of the two channels received by the error sensor, and adjust the parameters of the digital filter according to the calculation results until the error signal e(n) approaches zero. At this time, the parameters of the digital filter are optimized to a suitable state, and the secondary acoustic model is also completed in training, and can effectively generate an anti-sound wave to achieve the cancellation of the original noise.

[0218] In an ideal situation, when the cancellation signal reaches the error sensor after passing through the secondary path, it should cancel out with the original noise signal at the error point. That is to say, the sum of the signal of the original noise passing through the primary path to the error point and the signal of the cancellation signal generated by the filter passing through the secondary path to the error point is zero, that is, X(t)H P (Z) + X(t)W(Z)H s(Z) = 0. Performing operations on the above equation gives the condition H that the filter needs to satisfy. p (Z) = -W(Z)H s (Z).

[0219] Note that the above is only a preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described here, and various obvious changes, re-adjustments, combinations with each other, and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments only. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An active noise reduction method for a kitchen air conditioner fan, characterized in that, A blower and a secondary speaker are provided inside the kitchen air conditioner, and an acceleration sensor is provided on the housing of the blower; The active noise reduction method includes: Detecting the housing vibration signal of the blower by using the acceleration sensor; Predicting the real-time noise signal of the blower according to the vibration signal and a preset noise prediction model; Determining the anti-phase sound wave signal of the real-time noise of the blower through a preset secondary sound wave digital model according to the real-time noise signal of the blower; Playing the anti-phase sound wave signal by using the secondary speaker to perform active noise reduction on the kitchen air conditioner.

2. The active noise reduction method according to claim 1, wherein The noise prediction model is obtained through training in the following manner: Experimentally obtaining a blower vibration signal data set, where the blower vibration signal data set includes multiple vibration signal samples and the real-time noise samples of the blower corresponding to the vibration signal samples; Training a neural network model by using the blower vibration signal data set to obtain the noise prediction model.

3. The active noise reduction method according to claim 1, wherein, The kitchen air conditioner includes a refrigeration chamber and a heat dissipation chamber; The secondary speaker includes a first secondary speaker and a second secondary speaker; the first secondary speaker is arranged in the refrigeration chamber; the second secondary speakers are all arranged in the heat dissipation chamber; A refrigeration blower is further arranged in the refrigeration chamber, and a heat dissipation blower is further arranged in the heat dissipation chamber; The acceleration sensor includes a first acceleration sensor and a second acceleration sensor, the first acceleration sensor is arranged on the housing of the refrigeration blower, and the second acceleration sensor is arranged on the housing of the heat dissipation blower; Detecting the housing vibration signal of the blower by using the acceleration sensor includes: Detecting a first vibration signal of the housing of the refrigeration blower by using the first acceleration sensor; Detecting a second vibration signal of the housing of the heat dissipation blower by using the second acceleration sensor; Predicting the real-time noise signal of the blower according to the vibration signal and a preset noise prediction model includes: Predicting a first real-time noise signal of the refrigeration blower according to the first vibration signal and a preset refrigeration blower noise prediction model; Predicting a second real-time noise signal of the heat dissipation blower according to the second vibration signal and a preset heat dissipation blower noise prediction model; Determining the anti-phase sound wave signal of the real-time noise of the blower through a preset secondary sound wave digital model according to the real-time noise signal of the blower includes: Selecting the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determining a first anti-phase sound wave signal of the real-time noise of the corresponding blower through a preset secondary sound wave digital model; Playing the anti-phase sound wave signal by using the secondary speaker to perform active noise reduction on the kitchen air conditioner includes: Playing the first anti-phase sound wave signal by using the first secondary speaker in the refrigeration chamber where the refrigeration blower with the larger noise is located, or playing the first anti-phase sound wave signal by using the second secondary speaker in the heat dissipation chamber where the heat dissipation blower with the larger noise is located to perform primary active noise reduction on the kitchen air conditioner.

4. The active noise reduction method according to claim 3, wherein Selecting the one with the larger noise among the first real-time noise signal and the second real-time noise signal includes: Calculate the root mean square (RMS) values of the first real-time noise signal and the second real-time noise signal respectively to obtain a first RMS value and a second RMS value; Compare the first RMS value and the second RMS value to obtain the larger one.

5. The active noise reduction method according to claim 4, characterized in that Before calculating the root mean square (RMS) values of the first real-time noise signal and the second real-time noise signal respectively to obtain a first RMS value and a second RMS value, it further includes: Intercept the first real-time noise signal and the second real-time noise signal within the human ear hearing frequency band range.

6. The active noise reduction method according to claim 3, characterized in that, An acoustic microphone sensor is provided on the kitchen air conditioner housing; After playing the first anti-phase sound wave signal by the first secondary speaker in the refrigeration chamber where the refrigeration fan with larger noise is located, or playing the first anti-phase sound wave signal by the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with larger noise is located to perform primary active noise reduction on the kitchen air conditioner, it further includes: Collect the noise signal in the space where the kitchen air conditioner is located by using the acoustic microphone sensor; When the noise signal is greater than a preset noise threshold, select the smaller one of the first real-time noise signal and the second real-time noise signal, and determine the second anti-phase sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model; Play the second anti-phase sound wave signal by the first secondary speaker in the refrigeration chamber where the refrigeration fan with smaller noise is located, or play the second anti-phase sound wave signal by the second secondary speaker in the heat dissipation chamber where the heat dissipation fan with smaller noise is located to perform secondary active noise reduction on the kitchen air conditioner.

7. The active noise reduction method according to claim 6, wherein When the noise signal is greater than a preset noise threshold, select the smaller one of the first real-time noise signal and the second real-time noise signal, and determine the second anti-phase sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model, including: Calculate the root mean square (RMS) value of the noise signal to obtain a third RMS value; When the third RMS value is greater than a preset noise RMS value, calculate the root mean square (RMS) values of the first real-time noise signal and the second real-time noise signal respectively to obtain a first RMS value and a second RMS value; Select the smaller one of the first RMS value and the second RMS value, and determine the second anti-phase sound wave signal of the real-time noise of the corresponding fan through a preset secondary sound wave digital model.

8. The active noise reduction method according to claim 7, wherein Before calculating the root mean square (RMS) value of the noise signal to obtain a third RMS value, it further includes: Intercept the noise signal within the human ear hearing frequency band range.

9. The active noise reduction method according to claim 1, characterized in that, The secondary acoustic mathematical model is trained in the following manner: Build a primary acoustic channel and a secondary acoustic channel; wherein, the primary acoustic channel sequentially includes a noise signal source, a microphone, and an error sensor at a preset position; the secondary acoustic channel sequentially includes the noise signal source, the microphone, a digital filter, the secondary speaker, and the error sensor; Determine the first transfer function between the microphone and the error sensor in the primary acoustic channel; Determine the second transfer function between the speaker and the error sensor in the secondary acoustic channel; Train the secondary acoustic model using the digital filter, and calculate the sum of the noise signals of the primary acoustic channel and the secondary acoustic channel received by the error sensor during the training process according to the first transfer function and the second transfer function until the sum of the noise signals is zero.

10. An active noise reduction device for a kitchen air conditioner fan, characterized in that, A control module (70), a fan (10) and a secondary speaker (20) are arranged in the kitchen air conditioner, and an acceleration sensor (50) is arranged on the housing of the fan (10); the acceleration sensor (50) and the secondary speaker (20) are both electrically connected to the control module (70); The acceleration sensor (50) is used to detect the housing vibration signal of the fan (10); The control module (70) is used to predict the real-time noise signal of the fan (10) according to the vibration signal and a preset noise prediction model; and determine the anti-phase sound wave signal of the real-time noise of the fan (10) through a preset secondary sound wave digital model according to the real-time noise signal of the fan (10); The secondary speaker (20) is used to play the anti-phase sound wave signal to perform active noise reduction on the kitchen air conditioner.

11. The active noise reduction device according to claim 10, characterized in that, The kitchen air conditioner includes a refrigeration chamber (30) and a heat dissipation chamber (40); The secondary speaker includes a first secondary speaker (21) and a second secondary speaker (22); the first secondary speaker (22) is arranged in the refrigeration chamber (30); the second secondary speaker (22) is arranged in the heat dissipation chamber (40); A refrigeration fan (11) is further arranged in the refrigeration chamber (30), and a heat dissipation fan (12) is further arranged in the heat dissipation chamber (40); The acceleration sensor (50) includes a first acceleration sensor (51) and a second acceleration sensor (52), the first acceleration sensor (51) is arranged on the housing of the refrigeration fan (11), and the second acceleration sensor (52) is arranged on the housing of the heat dissipation fan (12); The first acceleration sensor (51) is used to detect the first vibration signal of the housing of the refrigeration fan (11); The second acceleration sensor (52) is used to detect the second vibration signal of the housing of the heat dissipation fan (12); The control module (70) is further used for: Predict the first real-time noise signal of the refrigeration fan according to the first vibration signal and a preset refrigeration fan noise prediction model; Predict the second real-time noise signal of the heat dissipation fan according to the second vibration signal and a preset heat dissipation fan noise prediction model; Select the one with the larger noise among the first real-time noise signal and the second real-time noise signal, and determine the first anti-phase sound wave signal of the real-time noise of the corresponding fan (10) through a preset secondary sound wave digital model; The first secondary loudspeaker (21) in the refrigeration chamber (30) where the refrigeration fan (11) with relatively high noise is located is used to play the first anti-sound wave signal, or the second secondary loudspeaker (22) in the heat dissipation chamber (40) where the heat dissipation fan (12) with relatively high noise is located plays the first anti-sound wave signal to perform primary active noise reduction on the kitchen air conditioner.

12. The active noise reduction device according to claim 11, wherein An acoustic microphone sensor (53) is provided on the housing of the kitchen air conditioner; The acoustic microphone sensor (53) is used to collect the noise signal in the space where the kitchen air conditioner is located; The control module (70) is further configured to select the smaller one of the first real-time noise signal and the second real-time noise signal when the noise signal is greater than a preset noise threshold, and determine the second anti-sound wave signal of the real-time noise of the corresponding fan (10) through a preset secondary sound wave digital model; The first secondary loudspeaker (21) in the refrigeration chamber (30) where the refrigeration fan (11) with relatively low noise is located is further used to play the second anti-sound wave signal, or the second secondary loudspeaker (22) in the heat dissipation chamber (40) where the heat dissipation fan (12) with relatively low noise is located is further used to play the second anti-sound wave signal to perform secondary active noise reduction on the kitchen air conditioner.

13. The active noise reduction device according to claim 10, characterized in that, The control module (70) includes: A central controller (71) for predicting the real-time noise signal of the fan (10) according to the vibration signal and a preset noise prediction model; An active noise controller (72) electrically connected to the central controller (71) for determining the anti-sound wave signal of the real-time noise of the fan (10) through a preset secondary sound wave digital model according to the real-time noise signal of the fan (10).

14. A kitchen air conditioner, characterized in that, It includes the kitchen air conditioner fan active noise reduction device according to any one of claims 10-13.

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