CN114382718A - Fan fault identification method and system of central range hood - Google Patents
Fan fault identification method and system of central range hood Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/008—Stop safety or alarm devices, e.g. stop-and-go control; Disposition of check-valves
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D29/00—Details, component parts, or accessories
- F04D29/05—Shafts or bearings, or assemblies thereof, specially adapted for elastic fluid pumps
- F04D29/056—Bearings
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
- F24C15/00—Details
- F24C15/20—Removing cooking fumes
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Abstract
The embodiment of the invention discloses a fan fault identification method and a system of a central range hood, which comprises the following steps: respectively acquiring a fan vibration value, a fan current value and a fan noise value of the central range hood; determining a health state coefficient of the fan bearing according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value; and judging whether the health state coefficient of the fan bearing is greater than a preset threshold value or not, and controlling the fan of the central range hood to stop running when the health state coefficient of the fan bearing is greater than the preset threshold value. The embodiment of the invention can solve the problem that the central range hood cannot accurately judge the fault of the fan bearing in the operation process, improve the accuracy and intelligence of fan fault identification, simultaneously ensure the safe and reliable operation of the central range hood and improve the experience of users.
Description
Technical Field
The embodiment of the invention relates to the technical field of central range hoods, in particular to a fan fault identification method and system of a central range hood.
Background
The central fume exhaust fan is an outdoor product, a host machine of the central fume exhaust fan is usually arranged on the roof of a building, is connected with an air outlet of a public flue and is used for exhausting fume for kitchens of a plurality of users through the public flue, and a fan of the central fume exhaust fan is a power source for exhausting fume by the host machine.
The fan bearing is used as a core component of the fan in the central range hood, and the fan bearing is easy to break down when the service life of a motor of the central range hood is up or the motor of the central range hood is in an accident condition, so that the dynamic balance of the fan is invalid.
The current central authorities range hood is at the operation in-process, can't accurately judge out fan bearing and break down, causes central authorities range hood intelligent degree low, only can report the maintenance again after the user finds the problem, reduces user experience widely and experiences.
Disclosure of Invention
The invention provides a fan fault identification method and system of a central range hood, and aims to solve the problem that a fan bearing of the central range hood cannot be accurately judged to have a fault in the operation process.
In a first aspect, an embodiment of the present invention provides a method for identifying a fan fault of a central range hood, where the method includes:
respectively acquiring a fan vibration value, a fan current value and a fan noise value of the central range hood;
determining a health status coefficient of the fan bearing from the fan vibration value, the fan current value, and the fan noise value, wherein the health status coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value;
and judging whether the health state coefficient of the fan bearing is greater than a preset threshold value or not, and controlling the fan of the central range hood to stop running when the health state coefficient of the fan bearing is greater than the preset threshold value.
Optionally, determining a health state coefficient of the fan bearing according to the fan vibration value, the fan current value, and the fan noise value includes:
determining a vibration mass coefficient of the fan according to the fan vibration value;
determining a current mass coefficient of the fan according to the fan current value;
determining a noise quality coefficient of the fan according to the fan noise value;
determining a state of health coefficient for the fan bearing based on the vibration mass coefficient, the current mass coefficient, and the noise mass coefficient, wherein the state of health coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value.
Optionally, determining the health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient includes:
calculating the health state coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
Optionally, determining a vibration mass coefficient of the fan according to the fan vibration value includes:
calculating the vibration mass coefficient K of the fan according to the following formulaV：
Wherein, V0Presetting a reference value, V, for fan vibrationxAnd the value is the vibration value of the fan.
Optionally, determining a current quality coefficient of the fan according to the fan current value includes:
calculating the current mass coefficient K of the fan according to the following formulaI：
Wherein, I0Presetting a reference value for the fan current, IxThe value of the current of the fan is shown.
Optionally, determining the noise quality coefficient of the fan according to the fan noise value includes:
calculating the noise quality coefficient K of the fan according to the following formulaN：
Wherein N is0Presetting a reference value, N, for fan noisexIs the fan noise value.
Optionally, before determining the noise quality coefficient of the fan according to the fan noise value, the method further includes:
respectively acquiring an environmental noise value before the central range hood operates and an environmental noise value after the central range hood operates;
calculating the fan noise value N according to the following formula according to the environmental noise value before the central range hood operates and the environmental noise value after the central range hood operatesx：
Nx＝2N1-N2；
Wherein N is1Is the environmental noise value N of the central range hood before operation2The environmental noise value of the central range hood after operation.
In a second aspect, an embodiment of the present invention further provides a fan fault identification system of a central range hood, where the system includes a central range hood, where the central range hood includes a fan and an electric control cabinet electrically connected to the fan; the electric control cabinet comprises a main controller and a fan driving module;
the main controller is used for respectively acquiring a fan vibration value, a fan current value and a fan noise value of a central range hood, and determining a health state coefficient of the fan bearing according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value; judging whether the health state coefficient of the fan bearing is larger than a preset threshold value or not;
and the fan driving module is used for controlling the central range hood to stop running when the main controller determines that the health state coefficient of the fan bearing is greater than a preset threshold value.
Optionally, the central extractor hood further comprises a vibration sensor, a current sensor and a noise sensor;
the vibration sensor is arranged outside the fan and is in communication connection with the main controller; the vibration sensor is used for collecting a fan vibration value of the fan and sending the fan vibration value to the main controller;
the current sensor is electrically connected between the fan and the fan driving module; the current sensor is used for acquiring a fan current value of the fan and sending the fan current value to the main controller;
the noise sensor is arranged outside the fan; the noise sensor is used for collecting a fan noise value of the fan and sending the fan noise value to the main controller.
Optionally, the main controller is further configured to receive the fan vibration value sent by the vibration sensor, and determine a vibration mass coefficient of the fan according to the fan vibration value;
receiving the fan current value sent by the current sensor, and determining the current quality coefficient of the fan according to the fan current value;
receiving the fan noise value sent by the noise sensor, and determining the noise quality coefficient of the fan according to the fan noise value;
and determining a state of health coefficient for the fan bearing based on the vibration mass coefficient, the current mass coefficient, and the noise mass coefficient, wherein the state of health coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value.
Optionally, the main controller is further configured to calculate a health state coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
Optionally, the system further comprises a monitoring device and a cloud server in communication connection with the monitoring device, wherein the cloud server is in communication connection with the main controller;
the main controller is further used for sending a fan fault signal to the cloud server when the health state coefficient of the fan bearing is determined to be larger than a preset threshold value;
and the monitoring equipment is used for acquiring the fan fault signal through the cloud server and displaying or alarming.
In the embodiment of the invention, the fan vibration value, the fan current value and the fan noise value of the central range hood are respectively obtained, the health state coefficient of the fan bearing is determined according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value, the health state condition of the fan is accurately evaluated according to three parameter values related to the fan, then, the health state coefficient of the fan bearing is compared with a preset threshold value to determine whether the fan bearing has a fault, and when the health state coefficient of the fan bearing is greater than the preset threshold value, the fan of the central range hood is controlled to stop running to avoid damaging the central range hood, so the health state coefficient of the fan bearing is comprehensively evaluated by collecting the fan vibration value, the fan current value and the fan noise value, and the judgment and analysis are carried out, so that the accuracy and intelligence of fan fault identification are improved, meanwhile, the safe and reliable operation of the central range hood is ensured, and the experience of users are improved.
Drawings
Fig. 1 is a flowchart of a fan fault identification method of a central range hood according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a central range hood according to an embodiment of the present invention;
fig. 3 is a flowchart of another method for identifying a fan fault of a central range hood according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a fan fault recognition system of a central range hood according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of another fan fault identification system of a central range hood according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a fan fault recognition system of a central range hood according to another embodiment of the present invention;
fig. 7 is a flowchart of a practical method for identifying a fan fault of a central range hood according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Fig. 1 is a flowchart of a fan fault identification method for a central range hood according to an embodiment of the present invention, which is shown in fig. 1 and mainly includes:
s101, respectively obtaining a fan vibration value, a fan current value and a fan noise value of the central range hood.
S102, determining a health state coefficient of the fan bearing according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value.
S103, judging whether the health state coefficient of the fan bearing is larger than a preset threshold value or not, and controlling the fan of the central range hood to stop running when the health state coefficient of the fan bearing is larger than the preset threshold value.
It can be understood that central authorities ' range hood is installed outdoors usually, and in the operation process, the bearing that has avoided the fan motor to appear in the small probability receives the environmental impact, and the motor operation is unstable, phenomenons such as noise and vibration appear, but hardly confirms concrete fault reason through modes such as visual inspection, ear listening, in other words, can't confirm whether the fan trouble is because the bearing damage of fan makes the dynamic balance of fan invalid and arouses through effectual detection means, even the personnel also can't accurately confirm through the relevant parameter that detects the fan after sale. Therefore, the existing central range hood fault identification method is still incomplete, the central range hood intelligence degree is low, a single detection means cannot accurately position whether a fan bearing has a fault, and a detection value is influenced by other environments to the system and is inaccurate. Based on this, in this embodiment, after the fan bearing fault is comprehensively considered, the dynamic balance failure of the fan may cause the fan noise to become large, the current to become large, and the vibration to become large, so that an evaluation model, i.e., a functional relationship, relating the fan bearing health state to the fan vibration, the fan current, and the fan noise is established. According to the functional relation and the fan vibration value, the fan current value and the fan noise value which are detected in real time, the health state of the fan bearing in actual operation can be determined.
Further, fig. 2 is a schematic structural diagram of a central range hood according to an embodiment of the present invention, as shown in fig. 2, the central range hood 1 mainly includes two parts, namely a fan 10 and a main control cabinet 20, a fan vibration sensor 30 may be disposed outside the fan 10 to collect a fan vibration value, and the fan vibration value is sent to a main controller 201 in the main control cabinet 20 of the fan; meanwhile, a current transformer 40 is arranged on a loop of the fan bearing 101 and the fan driving device 202 in the main control cabinet 20 to collect a fan current value and send the fan current value to the main controller 201; and a noise sensor 50 is arranged outside the control cabinet 20 to collect a fan noise value and send the fan noise value to the main controller 201, so that the main controller 201 substitutes the received fan vibration value, fan current value and fan noise value into the established health state coefficient calculation formula of the fan bearing to obtain the health state coefficient of the fan bearing, and compares the health state coefficient of the fan bearing with a preset threshold value to judge the health state condition of the fan bearing, in other words, the health state condition of the fan bearing is evaluated by comprehensively considering the influence of the fan vibration value, the fan current value and the fan noise value on the fan bearing to avoid the influence of the singleness of the detection value on the accuracy of fault identification, and further, when the health state coefficient of the fan bearing is judged to be larger than the preset threshold value, the fan bearing has a serious fault, the operation of the central range hood needs to be stopped immediately to avoid burning or damage of the central range hood.
It should be noted that the health coefficient is a mathematical function related to the fan vibration value, the fan current value, and the fan noise value, and the functional expression thereof can be considered as: the health state coefficient is f (fan vibration value, fan current value, fan noise figure), changes when any one in three variable, all can influence the change of health state coefficient, and only under three variable combined action, just can accurately confirm the state coefficient of fan bearing, and then accurately judge the fan trouble. In addition, the specific value of the preset threshold is not limited in this embodiment, and may be set according to different types of fans in the central range hood, for example, any value greater than zero and less than or equal to 1.
In the embodiment, the fan vibration value, the fan current value and the fan noise value of the central range hood are respectively obtained, the health state coefficient of the fan bearing is determined according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value, so that the health state condition of the fan is accurately evaluated according to three parameter values related to the fan, then the health state coefficient of the fan bearing is compared with a preset threshold value to determine whether the fan bearing has a fault, and when the health state coefficient of the fan bearing is greater than the preset threshold value, the fan of the central range hood is controlled to stop running to avoid damaging the central range hood, so that the health state coefficient of the fan bearing is comprehensively evaluated by collecting the fan vibration value, the fan current value and the fan noise value, and the judgment and analysis are carried out, so that the accuracy and intelligence of fan fault identification are improved, meanwhile, the safe and reliable operation of the central range hood is ensured, and the experience of users are improved.
Optionally, fig. 3 is a flowchart of another fan fault identification method for a central range hood according to an embodiment of the present invention, where on the basis of the above embodiment, step S102 determines a health state coefficient of a fan bearing according to a fan vibration value, a fan current value, and a fan noise value, and includes:
and S1021, determining the vibration mass coefficient of the fan according to the fan vibration value.
And S1022, determining the current mass coefficient of the fan according to the current value of the fan.
And S1023, determining the noise quality coefficient of the fan according to the fan noise value.
And S1024, determining a health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient, wherein the health state coefficient is a mathematical function related to a fan vibration value, a fan current value and a fan noise value.
It is understood that the vibration mass coefficient refers to whether the vibration generated during the operation of the fan is severe or slight compared to the standard vibration. Exemplarily, when the vibration mass coefficient is larger than zero, the vibration of the fan is slight, and the fan is in a normal condition; when the vibration mass coefficient is less than zero, the fan is indicated to vibrate seriously. Likewise, the current quality factor and the noise quality factor can also be analyzed using the same principle.
Specifically, the central range hood can further calculate a vibration mass coefficient of the fan according to a detected fan vibration value, further calculate a current mass coefficient of the fan according to a detected fan current value, further calculate a noise mass coefficient of the fan according to a detected fan noise value, and then determine a health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient, namely establish the health state coefficient about the vibration mass coefficient, the current mass coefficient and the noise mass coefficient, so that the fault of the fan can be accurately identified according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient, the fault of the fan bearing is further determined, and the intelligence and the accuracy of the fault identification function of the central range hood are improved.
Optionally, determining the health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient includes: calculating the health state coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
Specifically, considering that the vibration mass coefficient, the current mass coefficient and the noise mass coefficient have different influences on the health state of the fan bearing, the three mass coefficients are averaged, and then the health state coefficient which finally represents the fan bearing is obtained through calculation, and K is known according to the calculation formula of the health state coefficient of the fan bearingV、KIAnd KNAll coefficients of (1), i.e. KV、KIAnd KNThe influence degree on K is the same, so that the sensitivity and the accuracy of fan bearing fault identification can be ensured.
For example, when the vibration mass coefficient is greater than zero, it indicates that the fan vibrates slightly, and when the vibration mass coefficient is less than zero, it indicates that the fan vibrates severely, and similarly, the current mass coefficient and the noise mass coefficient may also be the sameSo that when KV、KIAnd KNWhen the values are all 0, the fan operates normally, and at the moment, the health state coefficient K of the fan bearing is 1 according to the calculation formula of the health state coefficient of the fan bearing; when K isV、KIAnd KNWhen the values are all larger than 0, the fan runs normally and belongs to a good state, and the health state coefficient K of the fan bearing obtained by calculation is smaller than 1; when K isV、KIAnd KNWhen the values are all smaller than 0, the fan breaks down, the health state coefficient K of the fan bearing obtained through calculation at the moment is larger than 1, the preset threshold value is set to be 1, when the condition that K is larger than 1 is detected, the fan bearing breaks down, the fan is controlled to stop running, and the fan is prevented from being further damaged.
Further optionally, determining a vibration mass coefficient of the fan according to the fan vibration value includes: calculating the vibration mass coefficient K of the fan according to the following formulaV：
Wherein, V0Presetting a reference value, V, for fan vibrationxAnd the value is the vibration value of the fan.
It can be understood that the preset reference value of the fan vibration may be a standard value corresponding to the full-power operation condition of the fan, or a standard value corresponding to the current operation power or wind speed of the fan, and the comparison in the embodiment of the present invention is not particularly limited. The fan under the operating mode operation of difference, the fan vibration value that corresponds can be different, and is preferred, under the different operating mode of fan, can set up that the fan vibration preset reference value is different to improve the accuracy nature of fan trouble recognition function. It should be noted that the preset reference value of the fan vibration under different operating conditions may be a standard value obtained by factory test, a corresponding database is established for the standard value, and when the vibration mass coefficient of the fan is actually calculated, the preset reference value of the fan vibration is set by a table look-up method according to the current operating condition of the fan.
In particular, vibration of the fanCoefficient of dynamic mass KVCan be regarded as the vibration value V of the fanxPreset reference value V for fan vibration0Difference value of (A) and fan vibration preset reference value V0The ratio of (A) to (B) can be seen from a calculation formula of the vibration mass coefficient of the fan when V isxGreater than V0When the vibration condition of the fan of the current central range hood exceeds the preset standard condition, the fan vibrates greatly, and the understandable reason causing the large vibration of the fan can be the failure of the dynamic balance of a fan bearing, and the vibration mass coefficient K is obtained through calculation correspondinglyVLess than zero; when V isxIs equal to V0When the vibration condition of the fan of the current central range hood just meets the preset standard condition, the vibration mass coefficient K is obtained through calculation correspondinglyVIs equal to zero; when V isxLess than V0When the vibration condition of the fan of the current central range hood is good, the preset standard condition is met, and the vibration mass coefficient K is obtained correspondingly to calculationVGreater than zero. Therefore, the vibration condition of the fan can be quickly judged through the calculation formula of the vibration mass coefficient of the fan, and the response speed of fault identification is improved.
Further optionally, determining a current quality coefficient of the fan according to the fan current value includes: calculating the current mass coefficient K of the fan according to the following formulaI：
Wherein, I0Presetting a reference value for the fan current, IxThe value of the current of the fan is shown.
It can be understood that the preset reference value of the fan current may be a standard value corresponding to the full-power operation condition of the fan, or a standard value corresponding to the current operating power or the current wind speed of the fan.
Specifically, the current mass coefficient K of the fanICan be regarded as fan powerFlow value IxPresetting a reference value I relative to the current of the fan0Difference value of (A) and fan current preset reference value I0The ratio of (A) to (B) can be seen from a calculation formula of the current mass coefficient of the fan when I isxIs greater than I0When the current value of the fan current of the current central range hood exceeds the preset standard condition, the fan current is larger, and the current quality coefficient K is obtained through calculationIWhen the current is less than zero, it can be understood that the current of the fan is large, for example, the fan may be locked, the fan bearing may be damaged, or the common flue may be blocked; when I isxIs equal to I0When the current value of the fan of the current central range hood just meets the preset standard condition, the current quality coefficient K is obtained through calculationIIs equal to zero; when I isxIs less than I0When the current central range hood fan is in good condition, the current quality coefficient K is obtained through calculation corresponding to the condition that the preset standard condition is metIGreater than zero. Therefore, whether the fan current is normal or not can be quickly judged through a calculation formula of the current mass coefficient of the fan, and the response speed of fault identification is improved.
Further optionally, determining a noise quality coefficient of the fan according to the fan noise value includes: calculating the noise quality coefficient K of the fan according to the following formulaN：
Wherein N is0Presetting a reference value, N, for fan noisexIs the fan noise value;
it can be understood that the preset reference value of the fan noise may be a standard value corresponding to the full-power operation condition of the fan, or a standard value corresponding to the current operating power or wind speed of the fan.
In particular, the noise quality coefficient K of the fanNCan be regarded asFan noise value NxPresetting a reference value N relative to fan noise0Difference value of (A) and fan noise preset reference value N0The ratio of (A) to (B) can be seen from a calculation formula of the noise quality coefficient of the fan when N isxGreater than N0When the noise value of the fan of the current central range hood exceeds the preset standard condition, the noise generated by the fan is larger, and the noise quality coefficient K is obtained through calculationNWhen the noise is less than zero, it can be understood that the noise generated by the central range hood in the operation process belongs to the normal condition, but the too large noise of the fan will seriously affect the use experience of the user, and the noise is set to be the physical and mental health of the user, so that the reason for the too large noise of the fan can be that the fan is blocked, the fan bearing is damaged or the public flue is blocked; when N is presentxIs equal to N0When the central range hood noise value meets the preset standard, the noise quality coefficient K is calculatedNIs equal to zero; when N is presentxLess than N0When the central range hood is used, the condition of the fan of the current central range hood is good, the preset standard condition is met, and the noise quality coefficient K is obtained through calculation correspondinglyNGreater than zero. Therefore, whether the noise generated by the fan is normal or not can be quickly judged through the calculation formula of the noise quality coefficient of the fan, and the response speed of fault identification is improved.
Further, before determining the noise quality coefficient of the fan according to the fan noise value, the method further includes: respectively acquiring an environmental noise value before the central range hood operates and an environmental noise value after the central range hood operates; according to the environmental noise value before the central range hood operates and the environmental noise value after the central range hood operates, the fan noise value N is calculated according to the following formulax：
Nx＝2N1-N2；
Wherein N is1Is the environmental noise value N of the central range hood before operation2The environmental noise value of the central range hood after operation.
It will be appreciated that the noise detection device is typically employed in detecting the noise level of the fan, and the noise detection device is installedThe device is arranged on a central range hood, and when the noise in the environment where the current fan is located is collected, other noise interference exists inevitably, so that the accurate acquisition of the noise value of the fan is influenced. Therefore, in this embodiment, the environmental noise value before the central range hood operates and the environmental noise value after the central range hood operates are obtained respectively, and the fan noise value N actually generated by the fan itself can be calculated according to the calculation formula of the fan noise valuexTherefore, the accurate extraction of the noise value of the fan is improved, and the accuracy of the fault identification function is ensured.
Based on the same inventive concept, an embodiment of the present invention further provides a fan fault recognition system of a central range hood, fig. 4 is a schematic structural diagram of the fan fault recognition system of the central range hood provided by the embodiment of the present invention, as shown in fig. 4, the system includes a central range hood 1, the central range hood 1 includes a fan 10 and an electric control cabinet 20 electrically connected to the fan 10; the electric control cabinet 2 comprises a main controller 201 and a fan driving module 202; the main controller 201 is configured to obtain a fan vibration value, a fan current value, and a fan noise value of the central extractor hood 1, and determine a health state coefficient of the fan bearing according to the fan vibration value, the fan current value, and the fan noise value, where the health state coefficient is a mathematical function related to the fan vibration value, the fan current value, and the fan noise value; judging whether the health state coefficient of the fan bearing is larger than a preset threshold value or not; the fan driving module 202 is configured to control the central extractor hood 1 to stop operating when the main controller 201 determines that the health state coefficient of the fan bearing is greater than a preset threshold.
In this embodiment, the main controller 201 obtains the fan vibration value, the fan current value and the fan noise value of the central range hood in real time, so that the health state coefficient of the fan bearing can be determined according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value, so as to accurately evaluate the health state condition of the fan according to three parameter values related to the fan, then, the main controller 201 compares the health state coefficient of the fan bearing with a preset threshold value to determine whether the fan bearing has a fault, and when the health state coefficient of the fan bearing is greater than the preset threshold value, the fan driving module 202 controls the fan 10 of the central range hood 1 to stop operating, so as to avoid damaging the central range hood, and so, the fan vibration value, the fan noise value and the fan noise value are collected, The fan current value and the fan noise value are used for comprehensively evaluating the health state coefficient of the fan bearing and carrying out judgment and analysis, so that the accuracy and the intelligence of fan fault identification are improved, meanwhile, the safe and reliable operation of the central range hood is ensured, and the experience and the feeling of a user are improved.
Optionally, fig. 5 is a schematic structural diagram of another fan fault identification system of a central range hood according to an embodiment of the present invention, and as shown in fig. 5, the central range hood 1 further includes a vibration sensor 30, a current sensor 40, and a noise sensor 50; the vibration sensor 30 is arranged outside the fan and is in communication connection with the main controller 201; the vibration sensor 30 is configured to collect a fan vibration value of the fan 10, and send the fan vibration value to the main controller 201; the current sensor 40 is electrically connected between the fan 10 and the fan driving module 202; the current sensor 40 is configured to collect a fan current value of the fan 10 and send the fan current value to the main controller 201; the noise sensor 50 is disposed outside the fan 10; the noise sensor 50 is configured to collect a fan noise value of the fan, and send the fan noise value to the main controller 201.
The specific location of the vibration sensor 30 is not particularly limited in the embodiment of the present invention, and may be any location outside the fan or any location outside the central range hood, for example. The specific type of vibration sensor is not limited in this embodiment, and may be, for example, an electric type or a piezoelectric type. The current sensor 40 is used to obtain a fan current value, and may be, for example, a current hall sensor, which is not particularly limited in this embodiment of the present invention. The noise sensor 50 is used for detecting environmental noise, and may be a noise tester, for example, and converts the collected sound wave signal into an electrical signal and sends the electrical signal to the main controller 201 for processing. The embodiment of the present invention is not particularly limited thereto.
Specifically, the vibration sensor 30 collects fan vibration parameters caused by rotation of a fan bearing in the current fan operation process, converts the fan vibration parameters into electric signals (namely fan vibration values) and sends the electric signals to the main controller 201, meanwhile, the current sensor 40 collects fan current values generated in the fan operation process and sends the fan current values to the main controller 201, the noise sensor 50 collects noise values generated in the fan operation process and sends the noise values to the main controller 201, and the main controller receives the fan vibration values, the fan current values and the fan noise values and further processes and analyzes the fan vibration values, so that parameters required by fault identification are obtained among the vibration sensor 30, the current sensor 40 and the noise sensor 50, and response time and accuracy of fault identification are improved.
It should be noted that, in this embodiment, the vibration sensor 30 is in communication connection with the main controller 201, so that the fan vibration value acquired by the main controller 201 is more accurate, and the accuracy of data is not affected by electromagnetic interference.
Further optionally, as shown in fig. 5, the main controller 201 is further configured to receive the fan vibration value sent by the vibration sensor 30, and determine a vibration mass coefficient of the fan according to the fan vibration value; receiving a fan current value sent by a current sensor 40, and determining a current quality coefficient of the fan according to the fan current value; receiving a fan noise value sent by the noise sensor 50, and determining a noise quality coefficient of the fan according to the fan noise value; and determining a health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient, wherein the health state coefficient is a mathematical function related to a fan vibration value, a fan current value and a fan noise value.
Further optionally, the main controller 201 is further configured to calculate the health condition coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
Specifically, the main controller 201 calculates the vibration mass coefficient K of the fan according to the fan vibration value after receiving the fan vibration value sent by the vibration sensor 30, the fan current value sent by the current sensor 40, and the fan noise value sent by the noise sensor 50VCalculating to obtain the current mass coefficient K of the fan according to the current value of the fanIAnd calculating the noise quality coefficient K of the fan according to the noise value of the fanNAnd then, the health state coefficient K of the fan bearing is calculated according to a health state coefficient calculation formula of the fan bearing, and the K is compared with a preset threshold value, so that the fault of the fan can be accurately identified, the fault of the fan bearing is further determined, and the intelligence and the accuracy of the fault identification function of the central range hood are improved.
Optionally, fig. 6 is a schematic structural diagram of a fan fault recognition system of a central range hood according to an embodiment of the present invention, as shown in fig. 6, the system further includes a monitoring device 3, and a cloud server 2 in communication connection with the monitoring device 3, where the cloud server 2 is in communication connection with a main controller 201; the main controller 201 is further configured to send a fan fault signal to the cloud server 2 when it is determined that the health state coefficient of the fan bearing is greater than a preset threshold; the monitoring device 3 is used for acquiring a fan fault signal through the cloud server 2 and displaying or giving an alarm.
Wherein, supervisory equipment 3 can realize long-range working condition to central range hood 1 and monitor to show or send out alarm etc. when central range hood 1 breaks down, the after-sales personnel of so being convenient for in time provide service such as inspection of going to the door or maintenance. Illustratively, the monitoring device 3 may be a terminal device such as a computer.
The cloud server 2 generally refers to a "virtual" server running on the same physical hardware, which is also called a cloud computing server or a cloud host, has a large amount of data storage and processing capacity, and is a computing service with simplicity, high efficiency, safety, reliability, and elastically scalable processing capacity. In this embodiment, the cloud server 2 is configured to implement receiving, sending, and storing of data, that is, receive a fan fault signal sent by the main controller 201 for caching, and send the fan fault signal to the monitoring device 3.
In this embodiment, through setting up main control unit 201 and pass through cloud ware 2 and supervisory equipment 3 communication connection, after main control unit 201 determines that the health status coefficient of fan bearing is greater than the predetermined threshold value, send instruction control fan drive adjusting module 202 drive central range hood 1 out of service, and simultaneously, still send fan fault signal to cloud ware 2, cloud ware 2 sends fan fault signal for supervisory equipment 3 again, supervisory equipment 3 shows and reports to the police according to received fan fault signal, in order to remind the staff in time to carry out maintenance processing, promote user's product experience and experience.
To explain a specific embodiment, fig. 7 is a flowchart of a practical method for identifying a fan fault of a central range hood according to an embodiment of the present invention, as shown in fig. 7, including:
and S701, judging whether the central range hood is started to operate or not.
S702, if the operation is not started, recording the noise value measured by the noise meter as an environmental noise value N1。
S703, if the computer is started to operate, recording the noise value measured by the noise meter as an environmental noise value N2Calculating formula N according to the fan noise valuex＝2N1-N2Calculating to obtain a fan noise value Nx。
S704, if the machine is started to operate, recording the vibration value measured by the vibration meter as the vibration value V of the fanx。
S705, if the machine is started to operate, recording the current value measured by the mutual inductor as the current value I of the fanx。
S706, calculating formula according to noise quality coefficient of fan
Calculating to obtain a noise quality coefficient KN。
S707, calculating formula according to vibration mass coefficient of fan
ComputingObtaining the vibration mass coefficient KV。
S708, calculating a formula according to the current mass coefficient of the fan
Calculating to obtain a current mass coefficient KI。
S709, calculating formula according to health state coefficient of fan bearing
And calculating to obtain the health state coefficient K of the fan bearing.
S710, judging whether the health state coefficient K of the fan bearing is larger than a preset threshold value K or not0。
S711, if the health state coefficient K is larger than a preset threshold value K0And if so, identifying the fault of the fan bearing, controlling the central range hood to stop running, and executing the step S712. If the health state coefficient K is less than or equal to the preset threshold value K0Then, the process continues to return to step S703 to step S710.
And S712, sending a fan fault signal to the cloud server, and sending the fan fault signal to the monitoring equipment through the cloud server for displaying or alarming.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious modifications, rearrangements, combinations and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (12)
1. A fan fault identification method of a central range hood is characterized by comprising the following steps:
respectively acquiring a fan vibration value, a fan current value and a fan noise value of the central range hood;
determining a health status coefficient of the fan bearing from the fan vibration value, the fan current value, and the fan noise value, wherein the health status coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value;
and judging whether the health state coefficient of the fan bearing is greater than a preset threshold value or not, and controlling the fan of the central range hood to stop running when the health state coefficient of the fan bearing is greater than the preset threshold value.
2. The method for identifying the fan fault of the central range hood according to claim 1, wherein determining the health state coefficient of the fan bearing according to the fan vibration value, the fan current value and the fan noise value comprises:
determining a vibration mass coefficient of the fan according to the fan vibration value;
determining a current mass coefficient of the fan according to the fan current value;
determining a noise quality coefficient of the fan according to the fan noise value;
determining a state of health coefficient for the fan bearing based on the vibration mass coefficient, the current mass coefficient, and the noise mass coefficient, wherein the state of health coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value.
3. The fan fault identification method of the central range hood according to claim 2, wherein determining the health state coefficient of the fan bearing according to the vibration mass coefficient, the current mass coefficient and the noise mass coefficient comprises:
calculating the health state coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
4. The method for identifying the fan fault of the central range hood according to claim 2, wherein the step of determining the vibration mass coefficient of the fan according to the fan vibration value comprises the following steps:
calculating the vibration mass coefficient K of the fan according to the following formulaV：
Wherein, V0Presetting a reference value, V, for fan vibrationxAnd the value is the vibration value of the fan.
5. The fan fault identification method of the central range hood according to claim 2, wherein determining the current quality coefficient of the fan according to the fan current value comprises:
calculating the current mass coefficient K of the fan according to the following formulaI：
Wherein, I0Presetting a reference value for the fan current, IxThe value of the current of the fan is shown.
6. The method for identifying the fan fault of the central range hood according to claim 2, wherein the step of determining the noise quality coefficient of the fan according to the fan noise value comprises the following steps:
calculating the noise quality coefficient K of the fan according to the following formulaN：
Wherein N is0Presetting a reference value, N, for fan noisexIs the fan noise value.
7. The method for identifying the fan fault of the central range hood according to claim 6, wherein before determining the noise quality coefficient of the fan according to the fan noise value, the method further comprises:
respectively acquiring an environmental noise value before the central range hood operates and an environmental noise value after the central range hood operates;
calculating the fan noise value N according to the following formula according to the environmental noise value before the central range hood operates and the environmental noise value after the central range hood operatesx：
Nx＝2N1-N2；
Wherein N is1Is the environmental noise value N of the central range hood before operation2The environmental noise value of the central range hood after operation.
8. A fan fault recognition system of a central range hood is characterized by comprising a central range hood, wherein the central range hood comprises a fan and an electric control cabinet electrically connected with the fan; the electric control cabinet comprises a main controller and a fan driving module;
the main controller is used for respectively acquiring a fan vibration value, a fan current value and a fan noise value of a central range hood, and determining a health state coefficient of the fan bearing according to the fan vibration value, the fan current value and the fan noise value, wherein the health state coefficient is a mathematical function related to the fan vibration value, the fan current value and the fan noise value; judging whether the health state coefficient of the fan bearing is larger than a preset threshold value or not;
and the fan driving module is used for controlling the central range hood to stop running when the main controller determines that the health state coefficient of the fan bearing is greater than a preset threshold value.
9. The fan fault identification system of a central range hood according to claim 8, wherein the central range hood further comprises a vibration sensor, a current sensor and a noise sensor;
the vibration sensor is arranged outside the fan and is in communication connection with the main controller; the vibration sensor is used for collecting a fan vibration value of the fan and sending the fan vibration value to the main controller;
the current sensor is electrically connected between the fan and the fan driving module; the current sensor is used for acquiring a fan current value of the fan and sending the fan current value to the main controller;
the noise sensor is arranged outside the fan; the noise sensor is used for collecting a fan noise value of the fan and sending the fan noise value to the main controller.
10. The fan fault identification system of the central range hood according to claim 9, wherein the main controller is further configured to receive the fan vibration value sent by the vibration sensor, and determine a vibration mass coefficient of the fan according to the fan vibration value;
receiving the fan current value sent by the current sensor, and determining the current quality coefficient of the fan according to the fan current value;
receiving the fan noise value sent by the noise sensor, and determining the noise quality coefficient of the fan according to the fan noise value;
and determining a state of health coefficient for the fan bearing based on the vibration mass coefficient, the current mass coefficient, and the noise mass coefficient, wherein the state of health coefficient is a mathematical function of the fan vibration value, the fan current value, and the fan noise value.
11. The fan fault identification system of a central range hood according to claim 10, wherein the main controller is further configured to calculate the health coefficient K of the fan bearing according to the following formula:
wherein, KVIs the coefficient of vibration mass, KIIs the current mass coefficient, KNIs the noise quality coefficient.
12. The fan fault identification system of the central range hood according to claim 8, further comprising a monitoring device and a cloud server in communication connection with the monitoring device, wherein the cloud server is in communication connection with the main controller;
the main controller is further used for sending a fan fault signal to the cloud server when the health state coefficient of the fan bearing is determined to be larger than a preset threshold value;
and the monitoring equipment is used for acquiring the fan fault signal through the cloud server and displaying or alarming.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6135718A (en) * | 1999-03-25 | 2000-10-24 | System General Corporation | Interface apparatus for fan monitoring and control |
| JP2006009752A (en) * | 2004-06-29 | 2006-01-12 | Loopwing Kk | Axial flow type blower device |
| JP2010065594A (en) * | 2008-09-10 | 2010-03-25 | Mitsubishi Electric Corp | Failure diagnostic system of electric blower and electric equipment mounted with the same |
| CN104612992A (en) * | 2013-11-03 | 2015-05-13 | 西安扩力机电科技有限公司 | Wireless remote monitoring system for fan |
| CN105275858A (en) * | 2015-11-24 | 2016-01-27 | 浙江金盾风机股份有限公司 | Internet of things intelligent fan system |
| CN206071925U (en) * | 2016-08-04 | 2017-04-05 | 苏州云白环境设备股份有限公司 | A kind of lampblack fan exception automatic monitoring device |
| JP2018088179A (en) * | 2016-11-29 | 2018-06-07 | ファナック株式会社 | Machine learning apparatus which learns failure prediction of fan, device containing machine learning apparatus and method of learning machine |
| CN208024609U (en) * | 2018-01-08 | 2018-10-30 | 浙江工业大学 | A kind of windy group of planes failure warning system |
| CN109581211A (en) * | 2018-11-13 | 2019-04-05 | 国网江苏省电力有限公司南京供电分公司 | A kind of load ratio bridging switch mechanical breakdown on-line monitoring method based on current of electric |
| CN113158705A (en) * | 2020-01-07 | 2021-07-23 | 株洲中车时代电气股份有限公司 | Fan fault prediction and health management device and method |
| CN113673083A (en) * | 2021-07-16 | 2021-11-19 | 国网浙江省电力有限公司杭州供电公司 | Transformer direct-current magnetic biasing risk assessment method |
-
2022
- 2022-01-05 CN CN202210004906.5A patent/CN114382718A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6135718A (en) * | 1999-03-25 | 2000-10-24 | System General Corporation | Interface apparatus for fan monitoring and control |
| JP2006009752A (en) * | 2004-06-29 | 2006-01-12 | Loopwing Kk | Axial flow type blower device |
| JP2010065594A (en) * | 2008-09-10 | 2010-03-25 | Mitsubishi Electric Corp | Failure diagnostic system of electric blower and electric equipment mounted with the same |
| CN104612992A (en) * | 2013-11-03 | 2015-05-13 | 西安扩力机电科技有限公司 | Wireless remote monitoring system for fan |
| CN105275858A (en) * | 2015-11-24 | 2016-01-27 | 浙江金盾风机股份有限公司 | Internet of things intelligent fan system |
| CN206071925U (en) * | 2016-08-04 | 2017-04-05 | 苏州云白环境设备股份有限公司 | A kind of lampblack fan exception automatic monitoring device |
| JP2018088179A (en) * | 2016-11-29 | 2018-06-07 | ファナック株式会社 | Machine learning apparatus which learns failure prediction of fan, device containing machine learning apparatus and method of learning machine |
| CN208024609U (en) * | 2018-01-08 | 2018-10-30 | 浙江工业大学 | A kind of windy group of planes failure warning system |
| CN109581211A (en) * | 2018-11-13 | 2019-04-05 | 国网江苏省电力有限公司南京供电分公司 | A kind of load ratio bridging switch mechanical breakdown on-line monitoring method based on current of electric |
| CN113158705A (en) * | 2020-01-07 | 2021-07-23 | 株洲中车时代电气股份有限公司 | Fan fault prediction and health management device and method |
| CN113673083A (en) * | 2021-07-16 | 2021-11-19 | 国网浙江省电力有限公司杭州供电公司 | Transformer direct-current magnetic biasing risk assessment method |
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