Fan fault detection method and device and air conditioning system

Abstract

The invention provides a fan fault detection method and device and an air conditioning system, and relates to the technical field of air conditioners. The draught fan fault detection method comprises the steps that the characterization temperature of the working environment where a draught fan is located is obtained; under the condition that the characterization temperature is larger than or equal to a temperature threshold value, the deviation threshold value of the rotating speed of the draught fan is determined according to the characterization temperature; and according to a comparison result of the deviation between the target rotating speed and the actual rotating speed of the fan and the deviation threshold value, whether the fan has a fault or not is determined. Through the method, the rotating speed deviation threshold value used for fault detection can be dynamically determined according to the working condition when the working condition of the fan is severe, so that the accuracy of fan fault detection is improved, and the operation reliability of an air conditioning unit is effectively improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of air conditioning, and in particular to a fan fault detection method, device and air conditioning system. Background Art

[0002] As an important component of the air conditioning system, the fan plays a decisive role in the heat exchange of the whole machine. The detection of the fan operating status is crucial to the stable operation of the entire air conditioning system.

[0003] In the related art, the fan failure is generally detected based on the deviation between the target speed and the actual speed of the fan. Specifically, when the deviation between the target speed and the actual speed of the fan exceeds a preset threshold, the fan is considered to be faulty; when the deviation does not exceed the threshold, the fan is considered to be normal. Summary of the invention

[0004] The present disclosure provides a fan fault detection method, device and air conditioning system.

[0005] According to a first aspect of the present disclosure, a fan fault detection method is provided, comprising: obtaining a characteristic temperature of a working environment in which the fan is located; when the characteristic temperature is greater than or equal to a temperature threshold, determining a deviation threshold of a rotation speed of the fan according to the characteristic temperature; and determining whether the fan has a fault according to a deviation between a target rotation speed of the fan and an actual rotation speed and a comparison result of the deviation threshold.

[0006] In some embodiments, determining the deviation threshold of the fan speed based on the characterization temperature includes: determining the severity level of the fan's current operating condition based on the characterization temperature and the actual power supply voltage of the fan; determining the deviation threshold of the fan speed based on the severity level of the fan's current operating condition and a pre-set deviation reference value.

[0007] In some embodiments, determining the severity level of the current operating condition of the fan based on the characterization temperature and the actual supply voltage of the fan includes: determining a first severe operating condition characterization item based on the characterization temperature of the working environment of the fan and the temperature value of the fan under rated operating conditions; determining a second severe operating condition characterization item based on the actual supply voltage of the fan and the rated voltage of the fan; determining the severity level of the current operating condition of the fan based on the first severe operating condition characterization item and the second severe operating condition characterization item.

[0008] In some embodiments, the first severe operating condition characterization item is positively correlated with the characterization temperature of the working environment of the fan, and the second severe operating condition characterization item is negatively correlated with the actual power supply voltage of the fan.

[0009] In some embodiments, determining the severity level of the current operating condition of the wind turbine based on the first severe operating condition characterization item and the second severe operating condition characterization item includes: taking a weighted sum of the first severe operating condition characterization item and the second severe operating condition characterization item to obtain the severity level of the current operating condition of the wind turbine.

[0010] In some embodiments, determining the deviation threshold of the speed of the fan according to the severity level of the operating condition of the fan and a preset deviation reference value includes: determining the deviation threshold according to the product of the severity level of the current operating condition of the fan and a preset deviation reference value.

[0011] In some embodiments, determining whether the fan is faulty based on the deviation between the target speed and the actual speed of the fan and the comparison result of the deviation threshold includes: continuously detecting whether the deviation is greater than the deviation threshold; if the duration for which the deviation is greater than the deviation threshold is greater than a detection time threshold, determining that the fan is faulty; otherwise, determining that the fan is not faulty.

[0012] In some embodiments, the fan fault detection method further includes: when the characterization temperature is greater than or equal to a temperature threshold, determining the detection time threshold according to the characterization temperature.

[0013] In some embodiments, determining the detection time threshold based on the characterization temperature includes: determining the severity level of the current operating condition of the fan based on the characterization temperature and the actual power supply voltage of the fan; and determining the detection time threshold corresponding to the severity level of the current operating condition of the fan based on a pre-set correspondence between the severity level of the operating condition and the detection time threshold.

[0014] In some embodiments, the correspondence between the severity of the operating condition level and the detection time threshold is used to indicate that: when the severity of the operating condition level is in a first value range, the detection time threshold corresponding to the first value range is a first duration; when the severity of the operating condition level is in a second value range, the detection time threshold corresponding to the second value range is a second duration, wherein the lower limit boundary value of the second value range is greater than or equal to the upper limit boundary value of the first value range, and the second duration is greater than the first duration.

[0015] In some embodiments, the characteristic temperature of the working environment of the fan is the ambient temperature of the frequency conversion unit connected to the fan, or the air outlet temperature of the fan.

[0016] In some embodiments, the fan fault detection method further includes: when the characteristic temperature is less than the temperature threshold, determining whether the fan has a fault based on a comparison result between a deviation between the target speed and the actual speed of the fan and a preset deviation reference value.

[0017] In some embodiments, obtaining the representative temperature of the working environment of the fan includes: obtaining the representative temperature of the working environment of the fan when the running time of the fan is greater than or equal to a specified time.

[0018] According to a second aspect of the present disclosure, a wind turbine fault detection device is provided, comprising: a module for executing the wind turbine fault detection method as described above.

[0019] According to a third aspect of the present disclosure, a wind turbine fault detection device is provided, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute the wind turbine fault detection method as described above based on instructions stored in the memory.

[0020] According to a fourth aspect of the present disclosure, an air conditioning system is provided, comprising: the fan fault detection device as described above; and a temperature sensor for collecting a representative temperature of a working environment in which the fan is located.

[0021] According to a fifth aspect of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored, and when the instructions are executed by a processor, the wind turbine fault detection method as described above is implemented.

[0022] According to a sixth aspect of the present disclosure, a computer program product is provided, on which computer program instructions are stored, and when the instructions are executed by a processor, the wind turbine fault detection method as described above is implemented.

[0023] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments of the present disclosure with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0025] Figure 1 is a flow chart of a fan fault detection method according to some embodiments of the present disclosure;

[0026] Figure 2 is a flow chart of a step of determining a deviation threshold value in a method for detecting a fan fault according to some embodiments of the present disclosure;

[0027] Figure 3is a flow chart of a fan fault detection method according to other embodiments of the present disclosure;

[0028] Figure 4 is a schematic diagram of a flow chart of determining a deviation threshold and a detection time threshold in a fan fault detection method according to other embodiments of the present disclosure;

[0029] Figure 5 is a structural schematic diagram of a fan fault detection device according to some embodiments of the present disclosure;

[0030] Figure 6 is a structural schematic diagram of a fan fault detection device according to other embodiments of the present disclosure;

[0031] Figure 7 is a structural schematic diagram of a fan fault detection system according to some embodiments of the present disclosure;

[0032] Figure 8 is a schematic structural diagram of an air conditioning system according to some embodiments of the present disclosure.

[0033] The present disclosure can be more clearly understood from the following detailed description with reference to the accompanying drawings. DETAILED DESCRIPTION

[0034] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless otherwise specifically stated.

[0035] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0036] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0037] Technologies, methods, and apparatus known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the authorization specification.

[0038] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0039] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0040] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0041] In the related art, the fan fault is usually detected based on the comparison result between the fan speed deviation and the preset threshold. Considering that the actual operating conditions of the unit vary greatly, the above-mentioned single fault detection scheme based on a fixed threshold does not consider the impact of the severity of the working conditions on fault detection, resulting in low fault detection accuracy and affecting the stability of unit operation.

[0042] In view of this, the present disclosure proposes a fan fault detection method, device and air-conditioning system, which can dynamically determine a speed deviation threshold based on the operating conditions, thereby improving the accuracy of the fan fault detection results based on the speed deviation threshold, and effectively improving the reliability of the air-conditioning unit operation.

[0043] Figure 1 FIG. 1 is a flow chart of a method for detecting a fan fault according to some embodiments of the present disclosure. Figure 1 As shown, the fan fault detection method includes steps S11 to S13.

[0044] Step S11: obtaining a characteristic temperature of the working environment of the fan.

[0045] In some examples, the representative temperature of the working environment of the fan is obtained according to the following method:

[0046] The representative temperature of the working environment of the fan reported by the receiving temperature sensor.

[0047] In other examples, the representative temperature of the working environment of the fan is determined by calculation. For example, temperature values ​​reported by temperature sensors installed at different parts of the fan are first received; then, the representative temperature of the working environment of the fan is calculated based on the temperature values ​​reported by these temperature sensors.

[0048] The representative temperature of the working environment of the fan may be the ambient temperature of the frequency conversion unit connected to the fan, or the air outlet temperature of the fan. In addition, the representative temperature of the working environment of the fan may also be determined based on the ambient temperature of the frequency conversion unit and the air outlet temperature of the fan. For example, the average value of the ambient temperature of the frequency conversion unit and the air outlet temperature of the fan is used as the representative temperature of the working environment of the fan.

[0049] Step S12: when the representative temperature is greater than or equal to the temperature threshold, determining a deviation threshold of the rotation speed of the fan according to the representative temperature.

[0050] The inventors of the present disclosure have discovered that: the higher temperature characteristic of the working environment of the fan indicates that the working conditions are relatively severe. In this case, the fan easily accumulates heat, causing the temperature rise of the device to be too high, so that the actual speed of the fan cannot be increased, and the deviation between the target speed and the actual speed of the fan is increased. In other words, when the working conditions are relatively severe, the larger speed deviation may be caused by the severe working conditions rather than the fan failure. In the related art, fan fault detection is performed based on a fixed deviation threshold, which does not take into account the impact of the severe working conditions on fan fault detection. Therefore, the accuracy of the fault detection result is low, and false faults are prone to occur.

[0051] In view of this, in order to improve the accuracy of fan fault detection in the embodiment of the present disclosure, when the working conditions are relatively bad, the influence of the bad working conditions on the deviation threshold used for fan fault detection is considered. Specifically, the fan speed deviation threshold is determined dynamically according to the characteristic temperature.

[0052] In specific implementation, step S12 may have multiple implementations, which are described below in conjunction with two exemplary implementations.

[0053] In a first embodiment, in step S12, according to Figure 2 The process shown in the figure determines the deviation threshold of the fan speed. Figure 2 As shown, determining the deviation threshold includes: step S121: determining the severity of the current working condition of the fan according to the characterization temperature and the actual power supply voltage of the fan; step S122: determining the deviation threshold of the speed of the fan according to the severity of the current working condition of the fan and a preset deviation reference value. Among them, the characterization temperature of the working environment of the fan can be the ambient temperature of the frequency conversion unit connected to the fan, and the actual power supply voltage of the fan can be the bus voltage connected to the fan. In the embodiment of the present disclosure, not only the influence of the characterization temperature of the working environment of the fan on the deviation threshold is considered, but also the influence of the actual power supply voltage of the fan on the deviation threshold is considered, which helps to determine the deviation threshold more accurately and further improve the accuracy of fan fault detection.

[0054] Specifically, in step S121, the severity level of the current working condition of the fan can be determined according to the following exemplary method: step a1, determining the first severe working condition characterization item according to the characterization temperature of the environment in which the fan is located and the temperature value of the fan under rated working conditions; step a2, determining the second severe working condition characterization item according to the actual power supply voltage of the fan and the rated voltage of the fan; step a3, determining the severity level of the current working condition of the fan according to the first severe working condition characterization item and the second severe working condition characterization item.

[0055] The following is a detailed description of steps a1 to a3. In some examples, in step a1, the first severe working condition characterization item can be positively correlated with the characterization temperature of the working environment of the fan. When the temperature of the working environment of the fan is higher, it is more unfavorable for the heat dissipation of the fan and the worse the working condition. By making the first severe working condition characterization item positively correlated with the characterization temperature, the influence of temperature on the severity of the working condition can be more intuitively expressed.

[0056] For example, in step a1, the first severe working condition characterization item is calculated as follows: the first difference between the characterization temperature of the environment in which the fan is located and the lowest temperature of the temperature sensor range is calculated; the second difference between the temperature value of the fan under rated working conditions and the lowest temperature of the temperature sensor range is calculated; the ratio of the first difference to the second difference is used as the first severe working condition characterization item. In specific implementation, the lowest temperature of the temperature sensor range and the temperature value of the fan under rated working conditions can be flexibly set according to actual conditions. For example, the lowest temperature of the temperature sensor range is set to minus 30°C, and the temperature value of the fan under rated working conditions is set to 20°C.

[0057] In some examples, in step a2, the second severe working condition characterization item may be made negatively correlated with the actual power supply voltage of the fan. When the actual power supply voltage of the fan is smaller, the current of the fan at rated power is larger, the temperature rise of the device is higher, and the working condition is worse. By making the second severe working condition characterization item negatively correlated with the power supply voltage, the influence of the power supply voltage on the severity of the working condition can be more intuitively expressed.

[0058] For example, in step a2, the second severe working condition characterization item is calculated as follows: the ratio of the rated voltage of the fan to the actual supply voltage of the fan is calculated, and the ratio is used as the second severe working condition characterization item. In specific implementation, the rated voltage of the fan can be flexibly set according to actual conditions.

[0059] In some examples, in step a3, the severity level of the current working condition of the wind turbine can be obtained by weighted summing the first severe working condition characterization item and the second severe working condition characterization item. In specific implementation, the weight coefficient corresponding to the first severe working condition characterization item and the weight coefficient corresponding to the second severe working condition characterization item can be flexibly set.

[0060] In the disclosed embodiment, by calculating the first severe working condition characterization item according to the characterization temperature of the environment in which the fan is located and the temperature value of the fan under rated working conditions, the contribution of temperature to the severe working condition can be more accurately evaluated; by calculating the second severe working condition characterization item according to the actual power supply voltage of the fan and the rated voltage of the fan, the contribution of the power supply voltage of the fan to the severe working condition can be more accurately evaluated. The combination of the above two aspects can improve the accuracy of the severe level of the current working condition of the fan determined thereby, and thus help to improve the accuracy of the subsequently determined deviation threshold. Furthermore, by performing weighted summation of the first severe working condition characterization item and the second severe working condition characterization item, the accuracy of the calculated severe level of the current working condition of the fan can be further improved.

[0061] In step 122, the deviation threshold value may be determined according to the following exemplary method: the deviation threshold value is determined according to the product of the severity level of the current working condition of the fan and the preset deviation reference value. When the severity level of the current working condition of the fan is higher, the determined deviation threshold value is also larger. By adopting the above processing method, the deviation threshold value can be determined more accurately, and the accuracy of fan fault detection can be further improved.

[0062] Back to Figure 1 Step S12 may also adopt the following second implementation mode: determine the severity of the fan's current working condition according to the characteristic temperature and the actual current of the fan; determine the deviation threshold of the fan's speed according to the severity of the fan's current working condition and a preset deviation reference value.

[0063] For example, in the second implementation of step S12, the severity level of the current working condition of the fan can be determined according to the following formula: m1[(Th-T0) / (Tmid - T0)] + m2(Im0 / Ie). Wherein, m1 and m2 are weight coefficients, Th is the characteristic temperature of the current working environment of the fan, T0 is the lowest temperature of the temperature sensor range, Tmid is the temperature value of the fan under rated working conditions, Im0 is the actual current of the fan, and Ie is the rated current of the fan.

[0064] Step S13: Determine whether the fan has a fault based on the comparison result between the deviation between the target rotation speed and the actual rotation speed of the fan and the deviation threshold.

[0065] In some examples, step S13 includes: determining whether the deviation between the target speed and the actual speed of the fan is greater than a deviation threshold; if the judgment result is yes, determining that the fan is faulty; if the judgment result is no, determining that the fan is not faulty.

[0066] In other examples, step S13 includes: continuously detecting whether the deviation between the target speed and the actual speed of the fan is greater than the deviation threshold; when the duration of the deviation being greater than the deviation threshold is greater than the detection time threshold, determining that the fan is faulty; otherwise, determining that the fan is not faulty. Among them, the detection time threshold can be a pre-set fixed value, or a value dynamically determined according to the characterization temperature. By continuously detecting whether the deviation between the target speed and the actual speed of the fan is greater than the deviation threshold, and determining the fan fault based on the continuous detection results, the interference of external environmental factors (such as sudden wind blowing, causing the fan resistance to increase, resulting in a large deviation in the fan speed) on the fan fault detection can be eliminated, and the reliability of the fan fault detection can be further improved. Furthermore, by dynamically determining the detection time threshold according to the characterization temperature when the characterization temperature is greater than the temperature threshold, the impact of the severity of the working conditions on the fault detection can be better reflected, and the accuracy of the fan fault detection can be further improved.

[0067] In some embodiments, the fan fault detection method further includes: when the representative temperature of the working environment of the fan is less than the temperature threshold, determining whether the fan is faulty according to the deviation between the target speed of the fan and the actual speed and the comparison result of the preset deviation reference value. By adopting different fan fault detection conditions according to the different representative temperatures of the working environment of the fan, it is possible to dynamically calculate the threshold information required for fault detection when the working conditions are bad, and ignore the influence of the working conditions on the threshold information required for fault detection when the working conditions are not bad, so that not only the accuracy of fan fault detection can be improved, but also the efficiency of fan fault detection can be improved.

[0068] In the disclosed embodiment, through the above process, when the working conditions are relatively severe, the speed deviation threshold can be dynamically determined based on the working conditions, thereby improving the accuracy of the fan fault detection results based on the speed deviation threshold, and effectively improving the reliability of the air-conditioning unit operation.

[0069] Figure 3 FIG. 1 is a flow chart of a method for detecting a fan fault according to other embodiments of the present disclosure. Figure 3 As shown, the fan fault detection method includes steps S31 to S39.

[0070] Step S31: Determine whether the operation time of the fan is greater than or equal to a specified time.

[0071] In some embodiments, the controller performs Figure 3The process shown. After receiving the power-on command, the controller can first determine whether the operating conditions of the inverter unit are met. If the operating conditions of the inverter unit are met, the controller performs the power-on action; otherwise, the power-on action is not performed. After the inverter unit is turned on, the controller sends a fan operation signal to the fan to start the fan. When the controller detects that the fan operation time is greater than or equal to the specified time, step S32 is executed. When the controller detects that the fan operation time is less than the specified time, it continues to wait until the fan operation time is greater than or equal to the specified time and then executes step S32.

[0072] In the embodiment of the present disclosure, by first determining that the running time of the fan is greater than the specified time and then executing the subsequent fan fault detection process, the reliability of fan fault detection can be improved and the possibility of incorrect fault detection results due to unstable speed during initial startup of the fan can be reduced.

[0073] Step S32: Determine whether the characteristic temperature of the environment in which the fan is located is greater than or equal to a temperature threshold.

[0074] If the judgment result of step S32 is yes, execute steps S33 to S35; if the judgment result of step S32 is no, execute steps S37 to S38.

[0075] Step S33: determining a deviation threshold and a first detection time threshold according to the characteristic temperature and voltage.

[0076] In the embodiment of the present disclosure, when the characteristic temperature of the environment in which the fan is located is high, it indicates that the working condition is relatively bad. In this case, the bad working condition is characterized according to the characteristic temperature and voltage, and the deviation threshold and the first detection time threshold are determined accordingly.

[0077] In specific implementation, step S33 can be implemented in a variety of ways. Figure 4 Step S33 is exemplarily described. Figure 4 As shown, step S33 specifically includes steps S331 to S333.

[0078] Step S331: Determine the severity level of the current working condition of the fan according to the characteristic temperature and the actual power supply voltage of the fan.

[0079] Regarding how to determine the severity of the current working condition of the fan, reference may be made to the relevant description of the aforementioned embodiment.

[0080] Step S332: Determine a deviation threshold value of the rotation speed of the fan according to the severity level of the current working condition of the fan and a preset deviation reference value.

[0081] Regarding how to determine the deviation threshold of the rotation speed of the fan, reference may be made to the relevant description of the aforementioned embodiment.

[0082] Step S333: According to the preset correspondence between the severity level of the working condition and the detection time threshold, determine the detection time threshold corresponding to the severity level of the current working condition of the wind turbine, and use it as the first detection time threshold.

[0083] In some examples, the correspondence between the severity of the working condition and the detection time threshold includes: multiple severity of the working condition value intervals, and the detection time threshold corresponding to each severity of the working condition value interval. Specifically, the correspondence is used to indicate that: when the severity of the working condition is in the first value interval, the detection time threshold corresponding to the first value interval is the first duration; when the severity of the working condition is in the second value interval, the detection time threshold corresponding to the second value interval is the second duration. The lower limit boundary value of the second value interval is greater than or equal to the upper limit boundary value of the first value interval, and the second duration is greater than the first duration.

[0084] For example, the corresponding relationship includes: when the working condition level q1 satisfies 2.1≤q1 <2.3, the corresponding detection time threshold is 10 seconds; when the working condition level q1 satisfies 2.3≤q1 <2.4, the corresponding detection time threshold is 15 seconds; when the working condition level q1 satisfies 2.4≤q1 <2.5, the corresponding detection time threshold is 20 seconds; when the working condition level q1 satisfies q1≥2.5, the corresponding detection time threshold is 30 seconds. Assuming that the working condition level of the fan is currently 2.2, the corresponding detection time threshold is determined to be 10 seconds according to the above corresponding relationship. By presetting multiple working condition level value intervals and the detection time thresholds corresponding to each value interval, it is convenient to determine the detection time threshold matching the current working condition more conveniently and efficiently when performing fan fault detection. Furthermore, by making the working condition level value interval with a larger value correspond to a larger detection time threshold, the reliability of fan fault detection under severe working conditions can be further improved.

[0085] In the disclosed embodiment, by considering not only the characteristic temperature of the working environment in which the fan is located but also the power supply voltage of the fan when determining the severity level of the current working condition of the fan, the accuracy of the severity level of the current working condition of the fan determined thereby can be improved. Furthermore, by dynamically determining not only the fan speed deviation threshold value according to the severity level of the current working condition of the fan but also the detection time threshold value according to the severity level of the current working condition of the fan, the threshold information of the fan fault detection can be adjusted more comprehensively according to the severity level of the working condition, thereby helping to further improve the accuracy of the fan fault detection, effectively identify the fan that has a fault under severe working conditions, and improve the reliability of the operation of the air conditioning unit.

[0086] Back to Figure 3Step S34: Continuously monitor the deviation between the target speed and the actual speed of the fan.

[0087] Step S35: Determine whether the duration during which the deviation is greater than the deviation threshold is greater than the first detection time threshold.

[0088] If the judgment result of step S35 is yes, execute step S36; otherwise, execute step S32 again.

[0089] Step S36: Determine that the fan is faulty.

[0090] Step S37: Continuously detect the deviation between the target speed and the actual speed of the fan.

[0091] Step S38: Determine whether the duration for which the deviation is greater than the deviation reference value is greater than a second detection time threshold.

[0092] The deviation reference value and the second detection time threshold are preset values. In specific implementation, the deviation reference value and the second detection time threshold can be flexibly set according to actual conditions.

[0093] If the judgment result of step S38 is yes, execute step S39; otherwise, execute step S32 again.

[0094] Step S39: Determine that the fan is faulty.

[0095] In some embodiments, the fan fault detection method further includes: after determining that the fan has failed, outputting a shutdown command.

[0096] In the embodiment of the present disclosure, through the above process, the detection conditions of fan faults can be dynamically adjusted according to the characteristic temperature of the working environment of the fan and the power supply voltage, thereby effectively identifying faulty fans under harsh conditions, reducing the possibility of the unit being mistakenly shut down due to incorrect fan fault detection results under harsh working conditions, and effectively improving the stability and reliability of the unit operation.

[0097] Figure 5 is a schematic diagram of the structure of a fan fault detection device according to some embodiments of the present disclosure. Figure 5 As shown, the fan fault detection device 50 is used to execute the fan fault detection method as described above, and includes an acquisition module 51 , a threshold determination module 52 , and a fault detection module 53 .

[0098] The acquisition module 51 is configured to acquire a characteristic temperature of the working environment of the fan.

[0099] The characteristic temperature of the working environment of the fan may be the ambient temperature of a frequency conversion unit connected to the fan, or the air outlet temperature of the fan.

[0100] The threshold determination module 52 is configured to determine a deviation threshold of the rotation speed of the fan according to the characteristic temperature when the characteristic temperature is greater than or equal to the temperature threshold.

[0101] In some examples, the threshold determination module 52 is configured to determine the severity of the current operating condition of the fan based on the characteristic temperature and the actual power supply voltage of the fan; and determine the deviation threshold of the fan speed based on the severity of the current operating condition of the fan and a pre-set deviation reference value.

[0102] Further, the threshold determination module 52 can determine the severity level of the current working condition of the fan in the following manner: determine a first severe working condition characterization item based on a characteristic temperature of the working environment in which the fan is located and a temperature value of the fan under rated working conditions; determine a second severe working condition characterization item based on the actual power supply voltage of the fan and the rated voltage of the fan; determine the severity level of the current working condition of the fan based on the first severe working condition characterization item and the second severe working condition characterization item.

[0103] Further, the threshold determination module 52 may determine the deviation threshold of the rotation speed of the fan in the following manner: determine the deviation threshold according to the product of the severity level of the current working condition of the fan and the preset deviation reference value. For example, the product of the severity level of the current working condition of the fan and the preset deviation reference value is used as the deviation threshold.

[0104] The fault detection module 53 is configured to determine whether the fan has a fault based on a comparison result between a deviation between a target rotation speed of the fan and an actual rotation speed and a deviation threshold.

[0105] In some embodiments, the fault detection module 53 is further configured to determine whether the fan is faulty based on a comparison result between a deviation between the target speed and the actual speed of the fan and a preset deviation reference value when the characteristic temperature is less than a temperature threshold.

[0106] In the disclosed embodiment, the above device can dynamically determine the speed deviation threshold used for fault detection according to the operating conditions when the fan is in a severe operating condition, thereby helping to improve the accuracy of fan fault detection and effectively improve the reliability of air-conditioning unit operation.

[0107] Figure 6 Schematic diagram of the structure of a fan fault detection device according to other embodiments of the present disclosure. Figure 6 As shown, the fan fault detection device 60 includes a memory 61 and a processor 62 coupled to the memory 61. The memory 61 is used to store instructions for executing the corresponding embodiments of the fan fault detection method. The processor 62 is configured to execute the fan fault detection method in any of the embodiments of the present disclosure based on the instructions stored in the memory 61.

[0108] Figure 7 FIG. 1 is a schematic diagram of a fan fault detection system according to some embodiments of the present disclosure. Figure 7 As shown, the fan fault detection system includes a control mainboard 71 , a display screen 72 , a temperature sensor 73 , and a power supply 74 .

[0109] The control mainboard 71 includes the above-mentioned fan fault detection device, which is used to execute the above-mentioned fan fault detection method. The control mainboard 71 can determine the ambient temperature of the fan according to the information reported by the temperature sensor, determine the bus voltage of the unit according to the relevant detection circuit, and dynamically determine the threshold information required for fan fault detection according to the ambient temperature and the bus voltage, and then perform fault detection on the fan according to the threshold information. In addition, the control mainboard 71 can also receive feedback signals from the fan, and output control signals to the fan.

[0110] The display screen 72 is used to display the parameter information during the fan fault detection and fan control process (such as at least one of the parameters such as the fan ambient temperature, the actual fan speed, the speed deviation, and the fan fault detection result) so that the user can understand the fan operation status in time.

[0111] The temperature sensor 73 is used to detect the temperature of the working environment of the fan or the temperature of the fan outlet. In specific implementation, multiple temperature sensors can be set in the air conditioning variable frequency unit to comprehensively detect the temperature of different parts of the unit (such as the fan outlet temperature, cooling water temperature, etc.).

[0112] The power supply 74 is used to supply power to the control mainboard 71 .

[0113] In the disclosed embodiment, the above system can more accurately detect fan failures and effectively improve the reliability of the air-conditioning unit operation.

[0114] Figure 8 Schematic diagram of the structure of an air conditioning system according to some embodiments of the present disclosure. Figure 8 As shown, the air conditioning system 80 includes a fan fault detection device 81 and a temperature sensor 82 .

[0115] The fan fault detection device 81 is used to execute the fan fault detection method as described above.

[0116] The temperature sensor 82 is used to collect the representative temperature of the working environment of the fan.

[0117] In the disclosed embodiment, the above system can more accurately detect fan failures and effectively improve the reliability of the air-conditioning unit operation.

[0118] Here, various aspects of the present disclosure are described with reference to flowcharts and / or block diagrams of methods, devices, and computer program products according to embodiments of the present disclosure. It should be understood that each frame of the flowchart and / or block diagram and the combination of frames can be implemented by computer-readable program instructions.

[0119] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable device to produce a machine, so that the processor executes the instructions to produce means for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0120] These computer-readable program instructions may also be stored in a computer-readable memory, which cause the computer to work in a specific manner to produce an article of manufacture, including instructions for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0121] The present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.

[0122] So far, the fan fault detection method, device and air conditioning system according to the present disclosure have been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed here.

Claims

1. A fan fault detection method, comprising: Obtain the representative temperature of the working environment of the fan; When the characteristic temperature is greater than or equal to the temperature threshold, determining a deviation threshold of the rotation speed of the fan according to the characteristic temperature; Whether the fan has a fault is determined according to a comparison result between a deviation between a target rotation speed and an actual rotation speed of the fan and the deviation threshold.

2. The fan fault detection method according to claim 1, wherein: The step of determining the deviation threshold of the rotation speed of the fan according to the characteristic temperature includes: Determining the severity level of the current working condition of the fan according to the characterized temperature and the actual power supply voltage of the fan; The deviation threshold of the rotation speed of the fan is determined according to the severity level of the current working condition of the fan and a preset deviation reference value.

3. The fan fault detection method according to claim 2, wherein: Determining the severity level of the current working condition of the fan according to the characterized temperature and the actual power supply voltage of the fan includes: Determining a first severe working condition characterization item according to a characterization temperature of a working environment of the fan and a temperature value of the fan under rated working conditions; Determining a second severe operating condition characterization item according to an actual power supply voltage of the wind turbine and a rated voltage of the wind turbine; The severity level of the current operating condition of the wind turbine is determined according to the first severe operating condition characterization item and the second severe operating condition characterization item.

4. The fan fault detection method according to claim 3, wherein: The first severe working condition characterization item is positively correlated with the characterization temperature of the working environment of the fan, and the second severe working condition characterization item is negatively correlated with the actual power supply voltage of the fan.

5. The fan fault detection method according to claim 3, wherein: Determining the severity level of the current working condition of the wind turbine according to the first severe working condition characterization item and the second severe working condition characterization item includes: A weighted sum is performed on the first severe operating condition characterization item and the second severe operating condition characterization item to obtain the severity level of the current operating condition of the wind turbine.

6. The fan fault detection method according to claim 2, wherein: Determining the deviation threshold of the rotation speed of the fan according to the severity level of the working condition of the fan and a preset deviation reference value includes: The deviation threshold is determined according to the product of the severity level of the current working condition of the wind turbine and a preset deviation reference value.

7. The fan fault detection method according to claim 1, wherein: Determining whether the fan has a fault according to a comparison result between a deviation between a target speed and an actual speed of the fan and the deviation threshold comprises: Continuously detecting whether the deviation is greater than the deviation threshold; When the duration that the deviation is greater than the deviation threshold is greater than the detection time threshold, it is determined that the fan is faulty; otherwise, it is determined that the fan is not faulty.

8. The fan fault detection method according to claim 7, further comprising: When the characteristic temperature is greater than or equal to the temperature threshold, the detection time threshold is determined according to the characteristic temperature.

9. The fan fault detection method according to claim 8, wherein: Determining the detection time threshold according to the characteristic temperature includes: Determining the severity level of the current working condition of the fan according to the characterized temperature and the actual power supply voltage of the fan; According to the preset correspondence between the severity level of the working condition and the detection time threshold, the detection time threshold corresponding to the severity level of the current working condition of the wind turbine is determined.

10. The fan fault detection method according to claim 9, wherein: The corresponding relationship between the severity level of the working condition and the detection time threshold is used to indicate: When the severity level of the working condition is within a first value interval, the detection time threshold corresponding to the first value interval is a first duration; When the severity level of the operating condition is in the second value range, the detection time threshold corresponding to the second value range is a second duration, wherein the lower limit boundary value of the second value range is greater than or equal to the upper limit boundary value of the first value range, and the second duration is greater than the first duration.

11. The fan fault detection method according to any one of claims 1 to 10, wherein: The characteristic temperature of the working environment of the fan is the ambient temperature of the frequency conversion unit connected to the fan, or the air outlet temperature of the fan.

12. The fan fault detection method according to any one of claims 1 to 10, further comprising: When the characteristic temperature is less than the temperature threshold, it is determined whether the fan has a fault according to a comparison result between a deviation between the target rotation speed and the actual rotation speed of the fan and a preset deviation reference value.

13. The method for detecting fan fault according to any one of claims 1 to 10, wherein: The step of obtaining the characteristic temperature of the working environment of the fan comprises: When the running time of the fan is greater than or equal to the specified time, a characteristic temperature of the working environment of the fan is obtained.

14. A fan fault detection device, comprising: A module for executing the fan fault detection method as claimed in any one of claims 1 to 13.

15. A fan fault detection device, comprising: Memory; as well as A processor coupled to the memory, wherein the processor is configured to execute the wind turbine fault detection method according to any one of claims 1 to 13 based on instructions stored in the memory.

16. An air conditioning system, comprising: The fan fault detection device according to claim 14 or 15; The temperature sensor is used to collect the representative temperature of the working environment of the fan.

17. A computer-readable storage medium having computer program instructions stored thereon, wherein the instructions, when executed by a processor, implement the wind turbine fault detection method according to any one of claims 1 to 13.

18. A computer program product having computer program instructions stored thereon, wherein the instructions, when executed by a processor, implement the wind turbine fault detection method according to any one of claims 1 to 13.

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