A fault recognition method, device and hob
By acquiring and analyzing signal characteristic parameters through an acoustic wave sensing device, the fault status of the stove can be identified, thus solving the stability problem of the stove's anti-overflow and anti-dry-burning technologies and ensuring safety.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-01-04
- Publication Date
- 2026-05-29
AI Technical Summary
Existing cooktop anti-overflow and anti-dry-burning technologies are difficult to reliably monitor overflow or dry-burning phenomena, leading to safety hazards.
Acquire acoustic wave detection signals through an acoustic wave sensing device, extract signal characteristic parameters, and identify fault states based on these parameters, including anomalies in signal strength, signal-to-noise ratio, and acoustic wave transmission path, thereby identifying the fault state of the acoustic wave sensing system.
It enables timely fault identification of the acoustic wave sensing system, avoiding safety hazards such as overflow prevention or dry burning monitoring failure caused by system abnormalities.
Smart Images
Figure CN122109305A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of smart appliances, and more particularly to a fault identification method, device, and cooktop. Background Technology
[0002] Existing cooktop anti-overflow and anti-dry-burning technologies are difficult to reliably predict overflow or dry-burning. Therefore, it is necessary to seek a stable and reliable sensing system to monitor overflow or dry-burning phenomena and ensure that the sensing system is in normal working condition. Summary of the Invention
[0003] To address the aforementioned technical problems, this disclosure proposes a fault identification method, device, and cookware, particularly a sound wave sensing device for identifying the state of cookware through sound wave detection. This device can accurately and promptly identify the working state of the sound wave sensing system corresponding to the sound wave sensing device and promptly obtain information about the fault state of the sound wave sensing system.
[0004] According to a first aspect of this disclosure, a fault identification method is provided, comprising: Acquire a sound wave detection signal, wherein the sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave, wherein the received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container, and the detection sound wave is provided by the sound source component; The acoustic wave detection signal is processed to obtain signal feature parameters; Fault identification processing is performed based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the acoustic wave sensing system is in one of a non-fault state or a fault state. The acoustic wave sensing system includes the sound source component, the acoustic wave detection component, and an acoustic wave transmission path including the cooking container.
[0005] Optionally, the signal characteristic parameters include signal strength and signal-to-noise ratio, the fault identification result includes first fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the signal strength is within a first strength range and the signal-to-noise ratio is less than or equal to a preset signal-to-noise ratio threshold, a first fault information is generated, which is used to indicate that the acoustic wave sensing system is in an external interference state.
[0006] Optionally, the signal characteristic parameters include signal strength, the fault identification result includes second fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the fluctuation range of the signal strength within a preset time period is greater than or equal to the preset fluctuation range, a second fault information is generated, which is used to indicate that the cooking container is in an unstable support state.
[0007] Optionally, the signal characteristic parameters include signal strength, the fault identification result includes third fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the signal strength is less than or equal to a preset strength threshold, a third fault information is generated, which indicates that at least one of the sound source component and the sound wave detection component is in a failure state.
[0008] Optionally, the acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include multiple sub-signal intensities corresponding to the multiple acoustic wave detection components respectively, and the fault identification result includes second fault information; The fault identification process based on the signal feature parameters to obtain the fault identification result includes: If the fluctuation amplitude of any one of the multiple sub-signal intensities is greater than or equal to the preset fluctuation amplitude within a preset duration, a second fault information is generated. The second fault information is used to indicate that the cooking container is in an unstable support state.
[0009] Optionally, the acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include signal strength, the signal strength includes multiple sub-signal strengths corresponding to the multiple acoustic wave detection components respectively, and the fault identification result includes fourth fault information; The fault identification process based on the signal feature parameters to obtain the fault identification result includes: If at least one of the plurality of sub-signal intensities is within the corresponding first intensity range, and another of the plurality of sub-signal intensities is less than the corresponding preset intensity threshold, a fourth fault information is generated, which is used to indicate that the acoustic wave detection component corresponding to the other sub-signal intensity is in a failure state.
[0010] Optionally, the acoustic wave sensing system includes a bracket with multiple legs, and the multiple acoustic wave detection components are respectively connected to different legs; The fault identification result includes fifth fault information. The fault identification processing based on the signal feature parameters to obtain the fault identification result includes: When at least one of the plurality of sub-signal strengths is within the corresponding second strength range, a fifth fault information is generated. The fifth fault information is used to indicate that the pin corresponding to the sub-signal strength within the second strength range is in a contaminated state. The upper limit of the second strength range corresponding to the sub-signal strength is less than the lower limit of the first strength range corresponding to the sub-signal strength.
[0011] Optionally, the acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include signal strength, the signal strength includes multiple sub-signal strengths corresponding to the multiple acoustic wave detection components respectively, and the fault identification result includes sixth fault information; The fault identification process based on the signal feature parameters to obtain the fault identification result includes: When the strength of each of the multiple sub-signals is less than the corresponding preset strength threshold, a sixth fault message is generated, which is used to indicate that the sound source component is in a failure state.
[0012] Optionally, the fault identification result includes a seventh fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the signal strength is within the second strength range, a seventh fault message is generated, which indicates that the foot is in a contaminated state.
[0013] According to a second aspect of this disclosure, a fault identification device is provided, comprising: The signal acquisition module is used to acquire a sound wave detection signal. The sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave. The received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container. The detection sound wave is provided by the sound source component. The extraction module is used to perform extraction processing on the acoustic wave detection signal to obtain the signal feature parameters; The identification module is used to perform fault identification processing based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the sound wave sensing system is in one of a non-fault state and a fault state. The sound wave sensing system includes the sound source component, the sound wave detection component, and a sound wave transmission path including the cooking container.
[0014] According to a third aspect of this disclosure, a smart cooktop is provided, the cooktop including the sound wave sensing device, the sound wave sensing device including a sound source component and a sound wave detection component, and the cooktop employing the fault identification method as described in the above technical solution.
[0015] According to a fourth aspect of this disclosure, an electronic device is provided, including at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the at least one processor implements the fault identification method as described above by executing the instructions stored in the memory.
[0016] According to a fifth aspect of this disclosure, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or at least one program being loaded and executed by a processor to implement the fault identification method as described above.
[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.
[0018] Implementing this disclosure will have the following beneficial effects: This disclosure provides a fault identification method, device, and stove, comprising: acquiring a sound wave detection signal, wherein the sound wave detection signal is obtained by a sound wave detection component detecting and processing a received sound wave, the received sound wave including a sound wave formed by the detection sound wave passing through a cooking container, the detection sound wave being provided by a sound source component; extracting and processing the sound wave detection signal to obtain signal feature parameters; and performing fault identification processing based on the signal feature parameters to obtain a fault identification result, the fault identification result being used to indicate that the sound wave sensing system is in one of a non-fault state or a fault state, the sound wave sensing system including a sound source component, a sound wave detection component, and a sound wave transmission path including a cooking container; thereby, the fault state of the sound wave sensing system can be promptly detected, avoiding safety hazards caused by the user's inability to promptly detect the fault state of the sound wave sensing system, for example, avoiding safety hazards caused by the inability to perform anti-overflow or dry-burning monitoring due to system malfunction when using the sound wave sensing system for monitoring.
[0019] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description
[0020] To more clearly illustrate the technical solutions and advantages in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0021] Figure 1 A flowchart illustrating a fault identification method according to an embodiment of the present disclosure is shown; Figure 2 A schematic diagram of the structure of a fault identification device according to an embodiment of the present disclosure is shown. Detailed Implementation
[0022] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.
[0024] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.
[0025] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.
[0026] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more of a plurality of objects. For example, including at least one or more of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.
[0027] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.
[0028] This disclosure provides a fault identification method. The fault identification method of this invention can be applied to a sound wave sensing device, a stove including a sound wave sensing device, a smart terminal, or a backend server. For example, it can be a control unit of a sound wave sensing device or a stove including a sound wave sensing device, or a smart terminal or backend server communicatively connected to the sound wave sensing device or stove. The smart terminal can be a smart appliance control device, a PC, a mobile phone, or a smart wearable device, etc. The smart appliance control device is used to control at least one type of home appliance; this invention does not limit the scope of the method. This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many steps and does not represent a unique execution order. In actual devices, systems, processors, or server products, the method can be executed sequentially according to the embodiments or accompanying drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment).
[0029] The sound wave sensing device injects sound waves, especially ultrasonic waves, into the cooking container and receives and detects the sound wave feedback signal formed by the injected sound waves transmitted through the cooking container. Based on the sound wave feedback signal, it analyzes the characteristics of the sound wave vibration transmitted by the cooking container and accurately judges the physical state of the liquid in the cooking container (such as calm, boiling, or signs of overflow) and whether the cooking container is dry-burning. Based on this, it can intelligently adjust the firepower of the stove to achieve intelligent cooking or timely prompt the user.
[0030] Optionally, the acoustic sensing device includes a sound source component, an acoustic detection component, and a fault identification unit. Specifically, the sound source component provides detection acoustic waves and includes a sound wave generator, preferably an ultrasonic wave, which can be a piezoelectric ceramic transducer. The sound source component is connected to a sound wave conducting member, which transmits the acoustic waves generated by the sound wave generator directly or indirectly to the cooking container. One end of the sound wave conducting member is connected to the sound wave generator, and the other end is connected to a leg of a support for supporting the cooking container. Thus, the acoustic waves generated by the sound wave generator can be transmitted to the cooking container at least via the sound wave conducting member and the leg.
[0031] For example, the cooktop includes a support for a cooking container, the support comprising a plurality of spaced-apart legs, preferably 3-16 legs, such as 4, 5, 6, 8, 10, or 12 legs. Other numbers of legs are also possible, without limitation. The cooking container is supported by contact with the legs, which are relatively fixedly arranged. For example, each leg is connected to a leg frame, which can be circular, square, or rectangular, and can also be constructed in other shapes, without limitation. The legs are spaced apart; for example, the leg frame has a plurality of spaced-apart leg connecting portions, at which legs are fixedly connected.
[0032] Optionally, the sound wave generator operates at a frequency greater than or equal to 20 kHz, preferably 25 kHz to 400 kHz, especially 30 kHz to 250 kHz, such as 40 kHz, 50 kHz, 70 kHz, 80 kHz, 100 kHz, 120 kHz, 150 kHz or 200 kHz.
[0033] The acoustic wave detection component is used to detect and process received acoustic waves to obtain an acoustic wave detection signal. The received acoustic waves include acoustic waves generated by the detection acoustic waves provided by the sound source component and transmitted through the cooking container. For example, the acoustic wave detection component includes a vibration sensor that generates a detection signal based on the received vibration signal. The vibration sensor can be an acoustic wave sensor, for example, a piezoelectric ceramic transducer. The vibration sensor is connected to an acoustic wave transmission member. Optionally, one end of the acoustic wave transmission member is connected to the vibration sensor, and the other end is connected to another leg of the support used to support the cooking container. Thus, the acoustic waves provided by the sound source component can be transmitted from one leg to the cooking container via its acoustic wave transmission member, and then to the acoustic wave detection component via the other leg. The acoustic wave transmission member of the acoustic wave detection component transmits the acoustic waves to the vibration sensor, and the vibration sensor generates an acoustic wave detection signal based on the received acoustic waves.
[0034] Optionally, the acoustic sensing device includes one or more acoustic detection components. The acoustic source component and the plurality of acoustic detection components are respectively connected to different feet.
[0035] In an optional example, the bracket includes a first leg and a second leg spaced apart, the first leg and the second leg being two of a plurality of legs of the bracket, and the acoustic sensing device includes an acoustic detection component, the acoustic source component being connected to the first leg and the acoustic detection component being connected to the second leg.
[0036] In an optional example, the support includes a first leg, a second leg, and a third leg spaced apart. The first leg, the second leg, and the third leg are three of the multiple legs of the support. The sound wave sensing device includes two sound wave detection components. The sound source component is connected to the first leg, one of the two sound wave detection components is connected to the second leg, and the other of the two sound wave detection components is connected to the third leg. The detection sound wave provided by the sound source component is transmitted to the two sound wave detection components through the cooking container. Since the transmission paths of the detection sound wave to the two sound wave detection components are different, especially the transmission paths in the cooking container, the sound waves transmitted to the second leg and the third leg are different. Therefore, there is a certain difference in the sound waves received by the two sound wave detection components.
[0037] In an alternative example, the acoustic sensing device includes three acoustic detection components, which, along with the sound source component, are connected to four different feet.
[0038] The cooking container can be a wok, frying pan, or saucepan, or other types of cooking containers.
[0039] Figure 1 This diagram illustrates a flowchart of a fault identification method according to an embodiment of the present disclosure, as shown below. Figure 1 As shown, the fault identification method includes: Step S101: Obtain a sound wave detection signal. The sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave. The received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container. The detection sound wave is provided by the sound source component.
[0040] Specifically, the detection sound wave generated by the sound source component is transmitted to the sound wave detection component via the cooking container, and then to the support foot connected to the sound wave conduction component of the sound wave detection component, forming the received sound wave received by the sound wave detection component. The sound wave detection component detects the received sound wave and generates a sound wave detection signal.
[0041] Step S102: Extract and process the acoustic wave detection signal to obtain signal feature parameters.
[0042] Specifically, the detection sound wave generated by the sound source component is transmitted to the sound wave detection component via the support leg connected to the sound source component, the cooking container, and the support leg connected to the sound wave detection component, forming a received sound wave. The detected sound wave is transmitted through the sound wave transmission path including the support leg connected to the sound source component, the cooking container, and the support leg connected to the sound wave detection component to form the received sound wave. The acoustic characteristics of the sound wave transmission path affect the formed received sound wave. Sound wave transmission paths with different acoustic characteristics result in the same detection sound wave being transmitted to form a received sound wave or the received sound wave having different acoustic characteristics. The sound wave detection signal generated based on the received sound wave has different signal characteristics. The signal characteristics refer to the signal sequence characteristics corresponding to the sound wave detection signal. The signal characteristic parameters are used to quantitatively describe the signal characteristics or sound wave detection signal characteristics.
[0043] Abnormal conditions of the sound source component and / or sound wave detection component can also cause changes in the sound wave characteristics and / or sound wave detection signal of the received sound wave, which in turn leads to changes in the signal characteristic parameters corresponding to the received sound wave.
[0044] Step S103: Perform fault identification processing based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the sound wave sensing system is in one of a non-fault state or a fault state. The sound wave sensing system includes the sound source component, the sound wave detection component, and a sound wave transmission path including the cooking container.
[0045] Specifically, fault identification processing is performed based on the signal characteristic parameters to obtain the fault identification result. The non-fault state characterizes the acoustic wave sensing system as capable of generating, transmitting, and detecting sound waves in a desired manner. For the acoustic wave sensing system in the non-fault state, its sound source component can generate and transmit the desired detection sound wave, its sound wave transmission path can transmit the sound wave in a desired manner, and the transmission of the sound wave is not affected by unwanted obstacles such as oil stains or unstable contact between the cooking container and the support leg. Its acoustic wave detection component can generate an acoustic wave detection signal based on the received sound wave in a desired manner.
[0046] The fault condition indicates that the acoustic wave sensing system is unable to generate, transmit, or detect acoustic waves in the desired manner.
[0047] Therefore, this embodiment of the present disclosure determines signal characteristic parameters based on acoustic wave detection signals and performs fault identification processing based on the signal characteristic parameters to obtain fault identification results. This enables timely detection of the fault status of the acoustic wave sensing system, avoiding safety hazards caused by users' inability to detect the fault status of the acoustic wave sensing system in a timely manner. For example, it can avoid safety hazards caused by the inability to perform anti-overflow or dry-burning monitoring due to system abnormalities when using the acoustic wave sensing system for anti-overflow or dry-burning monitoring.
[0048] In an optional implementation, the signal characteristic parameters include signal strength and signal-to-noise ratio, the fault identification result includes first fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the signal strength is within a first strength range and the signal-to-noise ratio is less than or equal to a preset signal-to-noise ratio threshold, a first fault information is generated, which is used to indicate that the acoustic wave sensing system is in an external interference state.
[0049] Specifically, the first intensity range is used to indicate the normal signal intensity range, and a signal intensity within the first intensity range indicates that the signal intensity of the acoustic wave detection signal is normal. Optionally, the first intensity range includes a first lower limit value and a first upper limit value. The first lower limit value is -50dBm to -30dBm, for example, -35dBm, -40dBm, or -45dBm, and the first upper limit value is -20dBm to -5dBm, for example, -15dBm, -10dBm, or -8dBm. For example, the first intensity range is -50dBm to -5dBm, -45dBm to -8dBm, or -40dBm to -10dBm.
[0050] Optionally, if the signal-to-noise ratio is less than or equal to a preset signal-to-noise ratio threshold, the signal noise is considered to be too large. For example, the sound wave sensing system is subjected to strong external vibration interference or electromagnetic interference. For example, the preset signal-to-noise ratio threshold is 10~40dB, preferably 15~35dB, such as 18dB, 20dB, 22dB, 25dB, 30dB or 32dB.
[0051] For embodiments including an acoustic wave detection component, the aforementioned fault identification processing and subsequent fault identification processing steps can be performed using the signal strength and signal-to-noise ratio of the acoustic wave detection signal generated by the acoustic wave detection component, and will not be repeated hereafter. In various embodiments of this disclosure, the amplitude of the acoustic wave detection signal can be used to indicate its signal strength, and the amplitude or average amplitude of the acoustic wave detection signal can be used as the signal strength of the acoustic wave detection signal.
[0052] In an implementation including multiple acoustic wave detection components, the signal characteristic parameters include multiple sub-signal intensities and multiple sub-signal-to-noise ratios corresponding to the multiple acoustic wave detection components respectively. The sub-signal intensity corresponding to the acoustic wave detection component can be determined based on the acoustic wave detection signal generated by the acoustic wave detection component, and the sub-signal-to-noise ratio corresponding to the acoustic wave detection component can be determined based on the acoustic wave detection signal generated by the acoustic wave detection component. The first intensity range and the preset signal-to-noise ratio threshold corresponding to different acoustic wave detection components can be set to be the same or different. Then, when at least one sub-signal intensity is in the corresponding first intensity range, and the sub-signal-to-noise ratio corresponding to the sub-signal intensity is less than or equal to the corresponding preset signal-to-noise ratio threshold, a first fault information is generated. The first fault information is used to indicate that the acoustic wave sensing system is in an external interference state. The sub-signal intensity and sub-signal-to-noise ratio of the acoustic wave detection signal generated by the same acoustic wave detection component have a corresponding relationship, that is, the sub-signal-to-noise ratio corresponding to the sub-signal intensity is the sub-signal-to-noise ratio of the acoustic wave detection signal corresponding to the sub-signal intensity.
[0053] In an optional implementation, the signal characteristic parameters include signal strength, the fault identification result includes second fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the fluctuation range of the signal strength within a preset time period is greater than or equal to the preset fluctuation range, a second fault information is generated, which is used to indicate that the cooking container is in an unstable support state.
[0054] Specifically, if the signal strength fluctuates drastically within a short period of time, it is considered that the cooking container is not stably supported by the bracket, and the contact between the cooking container and the support feet is unstable. The preset duration can be 0.5-5 seconds, and the preset fluctuation amplitude can be a percentage of the signal strength, which can be 20% to 50%, preferably 25% to 45%, for example, 30%, 35%, or 40%. For example, if the preset duration is 1 second and the preset fluctuation amplitude is 30%, then if the signal strength fluctuates by more than or equal to 30% within 1 second, a second fault message is generated.
[0055] In an alternative example, a second fault message is generated when the signal strength is within a first strength range and the fluctuation range of the signal strength within a preset duration is greater than or equal to a preset fluctuation range.
[0056] For an implementation of an acoustic wave sensing system including multiple acoustic wave detection components spaced apart, the signal characteristic parameters include multiple sub-signal intensities corresponding to each of the multiple acoustic wave detection components, the fault identification result includes second fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the fluctuation amplitude of any one of the multiple sub-signal intensities is greater than or equal to the preset fluctuation amplitude within a preset duration, a second fault information is generated. The second fault information is used to indicate that the cooking container is in an unstable support state.
[0057] Specifically, the preset duration and preset fluctuation amplitude corresponding to multiple acoustic wave detection components can be set to the same value. The setting method for the preset duration and preset fluctuation amplitude is the same as the previous setting method, and will not be repeated here.
[0058] In an alternative example, a second fault message is generated when all of the sub-signal strengths are within a first strength range and the fluctuation amplitude of any one of the sub-signal strengths within a preset duration is greater than or equal to a preset fluctuation amplitude.
[0059] In an optional implementation, the fault identification result includes third fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the signal strength is less than or equal to a preset strength threshold, a third fault information is generated, which indicates that at least one of the sound source component and the sound wave detection component is in a failure state.
[0060] Optionally, the preset intensity threshold is less than the lower limit of the first intensity range, that is, less than the lower limit of the first intensity. For example, the preset intensity threshold is -80dBm to -50dBm, preferably -75dBm to -55dBm, such as -60dBm, -65dBm or -70dBm.
[0061] Optionally, the difference between the preset intensity threshold and the first intensity lower limit is -30dBm to -5dBm, for example -10dBm, -15dBm, -20dBm or -25dBm.
[0062] In an alternative implementation, if the duration of the signal strength being less than or equal to a preset strength threshold is greater than or equal to a target duration, a third fault message is generated, wherein the target duration is 1-60s, preferably 2-40s, for example 3s, 5s, 8s, 10s, 15s, 20s or 30s.
[0063] For example, if the signal strength is less than or equal to -60dBm within 5 seconds, a third fault message is generated.
[0064] The failure of the sound source component indicates that the sound source component is unable to provide detection sound waves, for example, a failure of the sound wave generator in the sound source component or a failure of the connection structure between the sound wave generator and its sound wave conduction component.
[0065] The failure of the acoustic wave detection component indicates that the acoustic wave detection component is unable to generate an acoustic wave detection signal based on the received acoustic waves. For example, the vibration sensor in the acoustic wave detection component may be faulty, or the connection structure between the acoustic wave conduction component and the vibration sensor in the acoustic wave detection component may be faulty.
[0066] Optionally, the acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include signal strength, the signal strength includes multiple sub-signal strengths corresponding to the multiple acoustic wave detection components respectively, and the fault identification result includes fourth fault information; The fault identification process based on the signal feature parameters to obtain the fault identification result includes: If at least one of the plurality of sub-signal intensities is within the corresponding first intensity range, and another of the plurality of sub-signal intensities is less than the corresponding preset intensity threshold, a fourth fault information is generated, which is used to indicate that the acoustic wave detection component corresponding to the other sub-signal intensity is in a failure state.
[0067] Specifically, the preset intensity thresholds corresponding to different acoustic wave detection components may be the same or different. If the intensity of at least one sub-signal is within the corresponding first intensity range and the intensity of another sub-signal is less than the corresponding preset intensity threshold, a fourth fault information is generated. The fourth fault information is used to indicate that the acoustic wave detection component corresponding to the intensity of the other sub-signal is in a failed state.
[0068] In an alternative implementation, the fourth fault information is generated when at least one of the plurality of sub-signal strengths is within a corresponding first strength range, and the duration of another sub-signal strength less than a corresponding preset strength threshold is greater than or equal to a target duration. The target duration can be set according to a previously configured method, which will not be elaborated upon here.
[0069] In an optional embodiment, the acoustic wave sensing system includes a bracket with multiple legs, the multiple acoustic wave detection components being connected to different legs respectively, the fault identification result including fifth fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result including: When at least one of the plurality of sub-signal strengths is within the corresponding second strength range, a fifth fault information is generated. The fifth fault information is used to indicate that the pin corresponding to the sub-signal strength within the second strength range is in a contaminated state. The upper limit of the second strength range corresponding to the sub-signal strength is less than the lower limit of the first strength range corresponding to the sub-signal strength.
[0070] Specifically, when at least one of the multiple sub-signal strengths is within the corresponding second strength range, the sub-signal strength is at a low strength level, and a fifth fault message is generated accordingly. The upper limit of the second strength range corresponding to the sub-signal strength is less than the lower limit of the first strength range corresponding to the sub-signal strength, and the lower limit of the second strength range corresponding to the sub-signal strength is greater than the preset strength threshold corresponding to the sub-signal strength.
[0071] In an optional implementation, the step of performing fault identification processing based on the signal characteristic parameters to obtain a fault identification result includes: If, within a first set time period, the decrease in the intensity of at least one of the plurality of sub-signal intensities is greater than or equal to a first preset intensity amplitude, and at least another sub-signal intensity is within a corresponding first intensity range, and the signal-to-noise ratio corresponding to the at least another sub-signal intensity is greater than a corresponding preset signal-to-noise ratio threshold, temporary fault information is generated. This temporary fault information indicates that the pin corresponding to the at least one sub-signal intensity is in a temporary contaminated state, such as being temporarily covered by liquid or dirt. The first set time period can be 30~80s, for example 40s, 50s, or 60s, and the first preset intensity amplitude can be a percentage value, for example 30%~70%, for example 40%, 50%, or 60%.
[0072] In an optional implementation, the step of performing fault identification processing based on the signal characteristic parameters to obtain a fault identification result includes: If, within a second set time period, the decrease in the strength of at least one of the plurality of sub-signal strengths is greater than or equal to a second preset strength amplitude, cumulative fault information is generated. This cumulative fault information indicates that the pin corresponding to the at least one sub-signal strength is in a state of cumulative contamination, such as accumulated oil or other contaminants on the pin surface. The second set time period can be from 1 day to 60 days, for example, 5 days, 10 days, 20 days, or 30 days. The second preset strength amplitude can be a percentage value, for example, 20% to 60%, for example, 30%, 40%, or 50%.
[0073] In an optional implementation, the fault identification result includes seventh fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the signal strength is within the second strength range, a seventh fault message is generated, which indicates that the foot is in a contaminated state.
[0074] The upper limit of the second intensity range is less than the lower limit of the first intensity range, and the lower limit of the second intensity range is greater than the preset intensity threshold.
[0075] In an alternative implementation, the acoustic wave sensing system includes a bracket with multiple legs, and the acoustic wave detection component is connected to one of the multiple legs respectively; the fault identification result includes a seventh fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When at least one of the sub-signal strengths is within the second strength range, a seventh fault message is generated, which indicates that the pin corresponding to the sub-signal strength is in a contaminated state.
[0076] Wherein, the upper limit of the second intensity range is less than the lower limit of the first intensity range, the lower limit of the second intensity range is greater than the preset intensity threshold, and the pin corresponding to the sub-signal intensity refers to the pin connected to the acoustic wave detection component that generates the acoustic wave detection signal with the sub-signal intensity.
[0077] In an optional implementation, the acoustic wave sensing system includes a plurality of acoustic wave detection components spaced apart. The signal characteristic parameters include signal strength, which includes a plurality of sub-signal strengths corresponding to the plurality of acoustic wave detection components. The fault identification result includes a sixth fault information. The step of performing fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the strength of each of the multiple sub-signals is less than the corresponding preset strength threshold, a sixth fault message is generated, which is used to indicate that the sound source component is in a failure state.
[0078] Specifically, if the sound wave sensing device is equipped with a sound source component, then multiple sound wave detection components in the sound wave sensing system share a sound source component. When the intensity of the multiple sub-signals is less than a preset intensity threshold, the received sound waves formed by the detected sound waves corresponding to the multiple sound wave detection components basically disappear, and a sixth fault information is generated. The sixth fault information is used to indicate that the sound source component is in a failed state.
[0079] Figure 2 A schematic diagram of the structure of a fault identification device according to an embodiment of the present disclosure is shown, such as... Figure 2 As shown, the above-mentioned fault identification device includes: The signal acquisition module is used to acquire a sound wave detection signal. The sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave. The received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container. The detection sound wave is provided by the sound source component. The extraction module is used to perform extraction processing on the acoustic wave detection signal to obtain the signal feature parameters; The identification module is used to perform fault identification processing based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the sound wave sensing system is in one of a non-fault state or a fault state. The sound wave sensing system includes the sound source component, the sound wave detection group, and the sound wave transmission path including the cooking container.
[0080] In some embodiments, the functions or modules of the fault identification device provided in this disclosure can be used to execute the fault identification method described in the above embodiments. The specific implementation can be referred to the description in the above embodiments, and for the sake of brevity, it will not be repeated here.
[0081] This disclosure also proposes a cooktop, which includes the sound wave sensing device, which includes a sound source component and a sound wave detection component. The cooktop employs the fault identification method described in the above technical solution.
[0082] This disclosure also proposes a computer-readable storage medium storing at least one instruction or at least one program segment, which is loaded and executed by a processor to implement the fault identification method as described above. The computer-readable storage medium may be a non-volatile computer-readable storage medium.
[0083] This disclosure also proposes an electronic device, including at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the at least one processor implements the fault identification method as described above by executing the instructions stored in the memory.
[0084] Electronic devices can be provided as terminals, servers, or other forms of devices.
[0085] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A fault identification method, characterized in that, include: Acquire a sound wave detection signal, wherein the sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave, wherein the received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container, and the detection sound wave is provided by the sound source component; The acoustic wave detection signal is processed to obtain signal feature parameters; Fault identification processing is performed based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the acoustic wave sensing system is in one of a non-fault state or a fault state. The acoustic wave sensing system includes the sound source component, the acoustic wave detection component, and an acoustic wave transmission path including the cooking container.
2. The fault identification method according to claim 1, characterized in that, The signal characteristic parameters include signal strength and signal-to-noise ratio, the fault identification result includes first fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: When the signal strength is within a first strength range and the signal-to-noise ratio is less than or equal to a preset signal-to-noise ratio threshold, a first fault information is generated, which is used to indicate that the acoustic wave sensing system is in an external interference state.
3. The fault identification method according to claim 1, wherein the signal characteristic parameters include signal strength, the fault identification result includes second fault information, and the step of performing fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the fluctuation range of the signal strength within a preset time period is greater than or equal to the preset fluctuation range, a second fault information is generated, which is used to indicate that the cooking container is in an unstable support state.
4. The fault identification method according to claim 1, characterized in that, The signal characteristic parameters include signal strength, the fault identification result includes third fault information, and the fault identification processing based on the signal characteristic parameters to obtain the fault identification result includes: If the signal strength is less than or equal to a preset strength threshold, a third fault information is generated, which indicates that at least one of the sound source component and the sound wave detection component is in a failure state.
5. The fault identification method according to claim 1, characterized in that, The acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include multiple sub-signal intensities corresponding to the multiple acoustic wave detection components, and the fault identification result includes second fault information. The fault identification process based on the signal feature parameters to obtain the fault identification result includes: If the fluctuation amplitude of any one of the multiple sub-signal intensities is greater than or equal to the preset fluctuation amplitude within a preset duration, a second fault information is generated. The second fault information is used to indicate that the cooking container is in an unstable support state.
6. The fault identification method according to claim 1, characterized in that, The acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include signal strength, the signal strength includes multiple sub-signal strengths corresponding to the multiple acoustic wave detection components, and the fault identification result includes fourth fault information. The fault identification process based on the signal feature parameters to obtain the fault identification result includes: If at least one of the plurality of sub-signal intensities is within the corresponding first intensity range, and another of the plurality of sub-signal intensities is less than the corresponding preset intensity threshold, a fourth fault information is generated, which is used to indicate that the acoustic wave detection component corresponding to the other sub-signal intensity is in a failure state.
7. The fault identification method according to claim 6, characterized in that, The acoustic wave sensing system includes a bracket with multiple legs, and the multiple acoustic wave detection components are respectively connected to different legs; The fault identification result includes fifth fault information. The fault identification processing based on the signal feature parameters to obtain the fault identification result includes: When at least one of the plurality of sub-signal strengths is within the corresponding second strength range, a fifth fault information is generated. The fifth fault information is used to indicate that the pin corresponding to the sub-signal strength within the second strength range is in a contaminated state. The upper limit of the second strength range corresponding to the sub-signal strength is less than the lower limit of the first strength range corresponding to the sub-signal strength.
8. The fault identification method according to claim 1, characterized in that, The acoustic wave sensing system includes multiple acoustic wave detection components spaced apart, the signal characteristic parameters include signal strength, the signal strength includes multiple sub-signal strengths corresponding to the multiple acoustic wave detection components, and the fault identification result includes a sixth fault information. The fault identification process based on the signal feature parameters to obtain the fault identification result includes: When the strength of each of the multiple sub-signals is less than the corresponding preset strength threshold, a sixth fault message is generated, which is used to indicate that the sound source component is in a failure state.
9. The fault identification method according to claim 1, characterized in that, The fault identification result includes a seventh fault information. The fault identification processing based on the signal feature parameters to obtain the fault identification result includes: When the signal strength is within the second strength range, a seventh fault message is generated, which indicates that the foot is in a contaminated state.
10. A fault identification device, characterized in that, include: The signal acquisition module is used to acquire a sound wave detection signal. The sound wave detection signal is obtained by the sound wave detection component detecting and processing the received sound wave. The received sound wave includes the sound wave formed by the detection sound wave passing through the cooking container. The detection sound wave is provided by the sound source component. The extraction module is used to extract and process the acoustic wave detection signal to obtain the signal feature parameters; The identification module is used to perform fault identification processing based on the signal characteristic parameters to obtain a fault identification result. The fault identification result is used to indicate that the sound wave sensing system is in one of a non-fault state and a fault state. The sound wave sensing system includes the sound source component, the sound wave detection component, and a sound wave transmission path including the cooking container.
11. A stove, characterized in that, The cooktop includes the sound wave sensing device, which includes a sound source component and a sound wave detection component. The cooktop employs the fault identification method as described in any one of claims 1-9.