Detection method, apparatus and storage medium

Abstract

The application discloses a detection method for a product with a built-in fan, and comprises the following steps: controlling a data acquisition device to move relative to the built-in fan, and collecting real-time relative operation parameters of the built-in fan; determining real-time relative operation characteristics of the built-in fan according to the real-time relative operation parameters; and determining an operation state of the built-in fan according to the real-time relative operation characteristics. The application also discloses a detection device and a storage medium. The application can automatically identify fan operation faults and improve identification efficiency.

Description

Technical Field

[0001] This invention relates to the field of detection technology, and in particular to a detection method, apparatus and storage medium. Background Technology

[0002] Fans are an important component of power electronic products. Generally speaking, multiple fans may work in parallel in power electronic products. If a fan malfunctions, the product may not work properly. During the assembly or trial of power electronic products, fans may experience abnormal speed or reverse rotation. In the current technology, abnormal fan speed or reverse installation requires manual identification by the commissioning personnel. Due to mutual interference between fans or noise in the production workshop, manual identification is inefficient and prone to errors. Summary of the Invention

[0003] The main objective of this invention is to provide a detection method, apparatus, and storage medium, which aims to solve the problems of low efficiency and high error rate of manual identification in the prior art.

[0004] To achieve the above objectives, the present invention provides a detection method, the detection method comprising:

[0005] The control data acquisition device moves relative to the built-in fan and acquires the real-time relative operating parameters of the built-in fan;

[0006] The real-time relative operating characteristics of the built-in fan are determined based on the real-time relative operating parameters.

[0007] The operating status of the built-in fan is determined based on the real-time relative operating characteristics.

[0008] Optionally, the step of determining the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters includes:

[0009] Plot the real-time operating status curve based on the real-time relative operating parameters;

[0010] The curve features of the real-time running status curve are extracted and used as the real-time relative running features.

[0011] Optionally, the curve characteristics include fluctuation amplitude characteristics, and the step of determining the operating state of the built-in fan based on the real-time relative operating characteristics includes:

[0012] The fluctuation amplitude characteristics are compared with preset fluctuation amplitude characteristics or average fluctuation amplitude characteristics;

[0013] The operating status of the built-in fan is determined based on the comparison results.

[0014] Optionally, the curve features include fluctuation direction features, and the step of determining the operating state of the built-in fan based on the real-time relative operating features includes:

[0015] The fluctuation direction feature is compared with a preset fluctuation direction feature or a reference fluctuation direction feature, wherein the reference fluctuation direction feature is determined based on multiple fluctuation direction features of the real-time running state curve.

[0016] The operating status of the built-in fan is determined based on the comparison results.

[0017] Optionally, the step of determining the operating status of the built-in fan based on the comparison results includes:

[0018] If the wave direction feature is opposite to the preset wave direction feature or the reference wave direction feature, the built-in fan operates in a reverse rotation state.

[0019] Optionally, the step of determining the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters includes:

[0020] Extract the target relative operating parameters of the preset reference point from the real-time relative operating parameters;

[0021] Calculate the average value of the extracted target relative to the operating parameters;

[0022] Calculate the deviation between the target relative operating parameters and the average value at each preset reference point;

[0023] The step of determining the operating status of the built-in fan based on the real-time relative operating characteristics includes:

[0024] Determine whether there is a preset number of consecutive points with a deviation greater than a preset deviation;

[0025] If present, it is determined that the built-in fan is in an abnormal operating state.

[0026] Optionally, the step of controlling the data acquisition device to move relative to the built-in fan includes:

[0027] Keeping the built-in fan fixed, the data acquisition device is controlled to move relative to the built-in fan along a first preset trajectory; or

[0028] Keep the data acquisition device fixed, and control the built-in fan to move relative to the data acquisition device along a second preset trajectory.

[0029] Optionally, the data acquisition device includes an anemometer and / or a noise meter, and the real-time relative operating parameters include real-time relative wind speed parameters and / or real-time relative noise parameters.

[0030] To achieve the above objectives, the present invention also provides a detection device, the detection device comprising:

[0031] The data acquisition module is used to control the relative movement between the data acquisition device and the built-in fan, and to acquire the real-time relative operating parameters of the built-in fan;

[0032] The first determining module is used to determine the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters;

[0033] The second determining module is used to determine the operating status of the built-in fan based on the real-time relative operating characteristics.

[0034] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a detection program, which, when executed by a processor, implements the steps of the detection method described above.

[0035] The testing method, apparatus, and computer-readable storage medium provided by this invention offer the following advantages over existing technologies: They control a data acquisition device to move relative to the built-in fan and collect real-time relative operating parameters of the built-in fan; determine the real-time relative operating characteristics of the built-in fan based on these parameters; and determine the operating state of the built-in fan based on these characteristics. Through this method, the relative operating parameters can be obtained when the data acquisition device and the built-in fan are in different relative positions during their relative movement. This allows for the determination of the real-time relative operating characteristics detected when the data acquisition device and the built-in fan are in different relative positions, thereby accurately identifying whether the built-in fan is malfunctioning based on these real-time relative operating characteristics, eliminating the need for manual judgment and improving detection efficiency and accuracy. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the system structure of the hardware operating environment involved in the embodiments of the present invention;

[0037] Figure 2 This is a schematic flowchart of an embodiment of the detection method for the built-in fan of the present invention;

[0038] Figure 3 This is an example diagram of the motion trajectory of a data acquisition device according to an embodiment of the present invention;

[0039] Figure 4 This is a detailed flowchart of step S20 in one embodiment of the detection method of the present invention;

[0040] Figure 5 This is a detailed flowchart of step S30 in an embodiment of the detection method of the present invention;

[0041] Figure 6 This is a detailed flowchart illustrating steps S22 and S30 in one embodiment of the detection method of the present invention. Detailed Implementation

[0042] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] In the existing technology, abnormal fan speed or reverse installation requires manual identification by the adjustment personnel. Due to mutual interference between fans or noise in the production workshop, manual identification is inefficient and prone to errors.

[0045] To address the aforementioned technical problems, this invention provides a testing method. In this method, during the relative movement between the data acquisition device and the built-in fan, the relative operating parameters are determined when the data acquisition device and the built-in fan are in different relative positions. This allows for the determination of real-time relative operating characteristics detected when the data acquisition device and the built-in fan are in different relative positions. Based on these real-time relative operating characteristics, the method can accurately identify whether the built-in fan is in a faulty state, eliminating the need for manual judgment and improving detection efficiency and accuracy.

[0046] like Figure 1 As shown, Figure 1 This is a schematic diagram of the system structure of the hardware operating environment involved in the embodiments of the present invention.

[0047] The terminal in this embodiment of the invention can be a terminal device with computing capabilities, a PC, or a smartphone, tablet computer, e-book reader, MP3 (Moving Picture Experts Group Audio Layer III) player, MP4 (Moving Picture Experts Group Audio Layer IV) player, portable computer, or other portable terminal devices with display functions.

[0048] like Figure 1As shown, the terminal may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0049] Optionally, the terminal may also include a camera, RF (Radio Frequency) circuitry, sensors, audio circuitry, a WiFi module, and so on. Sensors may include light sensors, motion sensors, and other sensors. Specifically, light sensors may include ambient light sensors and proximity sensors. The ambient light sensor can adjust the display brightness according to the ambient light level, while the proximity sensor can turn off the display and / or backlight when the mobile terminal is moved to the ear. As a type of motion sensor, a gravity accelerometer can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity, and can be used for applications that identify the mobile terminal's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition functions (such as pedometers, taps), etc. Of course, the mobile terminal may also be equipped with other sensors such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, which will not be elaborated here.

[0050] Those skilled in the art will understand that Figure 1 The terminal structure shown does not constitute a limitation on the terminal and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0051] like Figure 1 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a detection program.

[0052] exist Figure 1 In the terminal shown, network interface 1004 is mainly used to connect to the backend server and communicate with it; user interface 1003 is mainly used to connect to the client (user terminal) and communicate with it; while processor 1001 can be used to call the detection program stored in memory 1005 and perform the following operations:

[0053] The control data acquisition device moves relative to the built-in fan and acquires the real-time relative operating parameters of the built-in fan;

[0054] The real-time relative operating characteristics of the built-in fan are determined based on the real-time relative operating parameters.

[0055] The operating status of the built-in fan is determined based on the real-time relative operating characteristics.

[0056] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0057] Plot the real-time operating status curve based on the real-time relative operating parameters;

[0058] The curve features of the real-time running status curve are extracted and used as the real-time relative running features.

[0059] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0060] The fluctuation amplitude characteristics are compared with preset fluctuation amplitude characteristics or average fluctuation amplitude characteristics;

[0061] The operating status of the built-in fan is determined based on the comparison results.

[0062] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0063] The fluctuation direction feature is compared with a preset fluctuation direction feature or a reference fluctuation direction feature, wherein the reference fluctuation direction feature is determined based on multiple fluctuation direction features of the real-time running state curve.

[0064] The operating status of the built-in fan is determined based on the comparison results.

[0065] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0066] If the wave direction feature is opposite to the preset wave direction feature or the reference wave direction feature, the built-in fan operates in a reverse rotation state.

[0067] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0068] Extract the target relative operating parameters of the preset reference point from the real-time relative operating parameters;

[0069] Calculate the average value of the extracted target relative to the operating parameters;

[0070] Calculate the deviation between the target relative operating parameters and the average value at each preset reference point;

[0071] Determine whether there is a preset number of consecutive points with a deviation greater than a preset deviation;

[0072] If present, it is determined that the built-in fan is in an abnormal operating state.

[0073] Furthermore, the processor 1001 can call the detection program stored in the memory 1005 and also perform the following operations:

[0074] Keeping the built-in fan fixed, the data acquisition device is controlled to move relative to the built-in fan along a first preset trajectory; or

[0075] Keep the data acquisition device fixed, and control the built-in fan to move relative to the data acquisition device along a second preset trajectory.

[0076] Reference Figure 2 , Figure 2 This is a schematic flowchart of an embodiment of the detection method for the built-in fan of the present invention. In some embodiments, the detection method includes:

[0077] Step S1 0: Control the data acquisition device to move relative to the built-in fan, and collect the real-time relative operating parameters of the built-in fan.

[0078] The detection method of the present invention can be applied to the detection process during the production and assembly of power electronic products, or to the detection process during the use or maintenance of power electronic products.

[0079] Specifically, in some embodiments, the data acquisition device includes an anemometer and / or a noise meter, and the real-time relative operating parameters correspond to real-time relative wind speed parameters and / or real-time relative noise parameters. Here, real-time relative operating parameters specifically refer to data related to the fan's operating state collected in real-time by the data acquisition device at various relative positions to the built-in fan during the relative motion between the data acquisition device and the built-in fan, including real-time wind speed parameters and / or real-time relative noise parameters, rather than specifically referring to operating performance parameters.

[0080] In some embodiments, the step of controlling the data acquisition device to move relative to the built-in fan in step S10 includes:

[0081] Step S1 1: Keep the built-in fan fixed and control the data acquisition device to move relative to the built-in fan along a first preset trajectory.

[0082] Specifically, such as Figure 3 As shown, Figure 3 This is an example diagram illustrating the motion trajectory of a data acquisition device according to an embodiment of the present invention, specifically an example diagram illustrating the trajectories of a noise meter and an anemometer. In some embodiments, the built-in fan (the entire power electronics product chassis) can be kept fixed, and the data acquisition device can be controlled to move relative to the built-in fan (the entire chassis) along a path such as... Figure 3 The device moves along the preset trajectory shown, thereby achieving relative motion between the data acquisition device and the built-in fan.

[0083] In some embodiments, the step of controlling the data acquisition device to move relative to the built-in fan in step S10 includes:

[0084] Step S1 2: Keep the data acquisition device fixed and control the built-in fan to move relative to the data acquisition device along a second preset trajectory.

[0085] Specifically, in some implementations, the data acquisition equipment, such as noise meters and / or anemometers, can be kept fixed while the built-in fan (the entire chassis) is controlled to move relative to the data acquisition equipment along a preset trajectory. During this process, the data acquisition equipment is kept in the data acquisition working state and the fan is kept on.

[0086] Furthermore, in some embodiments, both the first preset trajectory of the data acquisition device and the second preset trajectory of the built-in fan can be set according to the actual detection scenario. For example, it can be set according to the installation arrangement of the fan in the chassis. It can be a line segment trajectory, or two orthogonal line segment trajectories, or a closed rectangular trajectory or a circular trajectory, which is not limited here.

[0087] In some embodiments, the data acquisition device and the transmission device that carries the data acquisition device can be installed outside the chassis to build a detection system for testing. In some embodiments, the data acquisition device and related transmission device can also be installed inside the chassis, thereby enabling self-testing of the fan of each power electronic product without the need to build an additional detection system.

[0088] In some embodiments, real-time relative operating parameters can be collected by setting specific time intervals or data acquisition locations. For example... Figure 3 The data collected at the corresponding locations of each digital segment region for the motion trajectory scene shown are shown in the table below:

[0089]

[0090] Step S20: Determine the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters.

[0091] Specifically, relative operating characteristics refer to the features related to the fan's operating characteristics extracted based on real-time relative operating parameters collected by data acquisition equipment. They are also the relative features of the fan relative to a specific position.

[0092] Specifically, such as Figure 4 As shown, Figure 4 This is a detailed flowchart of step S20 in one embodiment of the present invention. In some embodiments, step S20 includes:

[0093] Step S21: Draw the real-time operating status curve based on the real-time relative operating parameters.

[0094] Specifically, in some embodiments, the real-time operating status curve can be plotted with the relative position of the data acquisition device and the fan (chassis as a whole) as the horizontal axis and the raw data acquired by the data acquisition device as the vertical axis. Alternatively, the real-time operating status curve can be plotted with time as the horizontal axis and the raw data acquired by the data acquisition device as the vertical axis.

[0095] In some embodiments, the original data can be processed, and a real-time operating status curve can be plotted based on the processed data. For example, the average value of the collected data can be calculated, and then the deviation of each collected data point from the average value can be calculated. The calculated deviation can be used as the ordinate to plot the real-time operating status curve.

[0096] Step S22: Extract the curve features of the real-time running status curve as the real-time relative running features.

[0097] Based on step S21, after plotting the real-time operating status curve, the curve features of the real-time operating status are extracted as relative operating features. Specifically, wind speed and noise curves are plotted. Generally, a normal curve is a regular curve with slight fluctuations. When irregular or violent fluctuations occur, or when the fluctuation direction is opposite to the set direction, it can reflect that the fan detected at the corresponding location has a fault or installation problem. Therefore, curve features such as fluctuation amplitude and fluctuation direction can be extracted as real-time relative operating features.

[0098] In some embodiments, instead of plotting real-time operating status curves, the collected data can be directly processed through calculations, and the calculation results can be directly used as real-time relative operating characteristics. For example, the deviation of each collected data from its average value can be directly used as the implementation relative operating characteristic.

[0099] Step S30: Determine the operating status of the built-in fan based on the real-time relative operating characteristics.

[0100] The operating status of the built-in fan can include normal operation and malfunction. Malfunction status can be further subdivided into abnormal fan speed and reverse rotation.

[0101] In some embodiments, relative operating characteristics can be compared with preset characteristic benchmarks, and the result of the comparison can be used to determine whether a fault state exists. For example... Figure 3 As shown in the data table in step S10, based on step S22, the path is divided into several segments. A fan malfunction is determined when the deviation of the average noise value of three consecutive segments from the preset noise benchmark value is greater than 1 dB (adjustable as needed), and the deviation of the average wind speed from the preset wind speed benchmark value is greater than 0.5 m / s (adjustable). Under normal circumstances, the actual operating status data at different relative positions may differ. Therefore, different preset benchmark values ​​can be set for each different relative position, and the actual characteristic values ​​can be compared with the preset benchmark values ​​corresponding to that relative position.

[0102] In some embodiments, instead of setting a fixed baseline value, the baseline value can be determined based on the actual collected data. For example, the maximum and minimum values ​​can be removed, and then the average value can be calculated as the baseline value.

[0103] For an embodiment of plotting real-time operating status curves, the amplitude characteristics of the peaks and troughs of the curve and the direction of fluctuation (positive or negative in the Y-axis direction) can be directly identified or calculated from the curve to determine whether it is in a fault state.

[0104] In some implementations, the faulty fan can also be located based on the acquisition location of the raw data corresponding to the abnormal relative operating characteristics.

[0105] In the above detection method, the data acquisition device is controlled to move relative to the built-in fan, and the real-time relative operating parameters of the built-in fan are collected. The real-time relative operating characteristics of the built-in fan are determined based on these parameters. The operating state of the built-in fan is then determined based on these characteristics. This method allows for the determination of the relative operating parameters when the data acquisition device and the built-in fan are in different relative positions during their relative movement. This enables the identification of real-time relative operating characteristics at these different positions, accurately identifying whether the built-in fan is malfunctioning without manual intervention, thus improving detection efficiency and accuracy.

[0106] In some embodiments, the curve feature includes a fluctuation amplitude feature, and step S30 includes:

[0107] Step S31: Compare the fluctuation amplitude feature with the preset fluctuation amplitude feature or the average fluctuation amplitude feature.

[0108] Specifically, generally speaking, if all the fans inside the computer case are operating normally, the data collected from different relative positions will not differ significantly and will exhibit a periodic fluctuation pattern, according to... Figure 3 The curve plotted from the data collected by the trajectory shown is a regular curve with slight fluctuations. If a fan malfunctions, such as not running, rotating too fast or too slow, or rotating in reverse, the collected data will show abnormal fluctuations. Therefore, the fluctuation amplitude characteristics can be extracted from the curve to determine the fault state.

[0109] The fluctuation amplitude characteristic can be the difference between the peaks and troughs in the curve, or it can be the values ​​of the peaks and troughs directly used as the fluctuation amplitude characteristic.

[0110] In some embodiments, a fixed preset fluctuation amplitude feature (amplitude reference value) can be preset, or different preset fluctuation amplitude features can be set for each relative position as a reference for comparison. Then, the fluctuation amplitude feature extracted from the curve is compared with the preset fluctuation amplitude feature. For example, the difference can be calculated by subtraction comparison.

[0111] In some embodiments, an average value can be calculated based on the actual extracted fluctuation amplitude characteristics from the curve as the average amplitude characteristic, and then the extracted fluctuation amplitude characteristics can be compared with the average amplitude characteristic. Alternatively, based on the periodic fluctuations of the curve, the corresponding average fluctuation amplitude characteristics can be calculated for different relative positions.

[0112] Step S32: Determine the operating status of the built-in fan based on the comparison results.

[0113] Specifically, based on step S31, after calculating the difference, it is determined whether the difference is within the preset difference benchmark range. If yes, it is determined that the built-in fan at the corresponding relative position is operating normally. If no, it is determined that there is an operational fault. Furthermore, for cases outside the preset difference benchmark range, the sign of the difference can be used to further determine whether the fan at the corresponding relative position is running too fast or too slow.

[0114] In the above detection method, the curve feature includes a fluctuation amplitude feature, which is compared with a preset fluctuation amplitude feature or an average fluctuation amplitude feature; the operating status of the built-in fan is determined based on the comparison result. Based on the fluctuation amplitude feature of the curve, the fan's fault status can be accurately and quickly identified.

[0115] refer to Figure 5 , Figure 5This is a detailed flowchart of step S30 of an embodiment of the detection method of the present invention.

[0116] In some implementations, the curve feature includes a ripple direction feature, and step S30 includes:

[0117] Step S33: Compare the fluctuation direction feature with a preset fluctuation direction feature or a reference fluctuation direction feature, wherein the reference fluctuation direction feature is determined based on multiple fluctuation direction features of the real-time running state curve.

[0118] Specifically, the fluctuation direction feature refers to the positive or negative directional characteristics of the peaks or troughs at specific relative positions of the curve along the vertical axis. In some embodiments, a preset fluctuation direction feature can be set in advance based on the fluctuation direction features of each relative position when all fans are operating normally. During step S20, the peaks and troughs of the plotted curve can be identified, and the positive and negative directional characteristics of each peak and trough can be determined. During step S33, the actual fluctuation direction features obtained from the curve are compared with the preset fluctuation direction features to determine if they are consistent. Using preset fluctuation direction features simplifies data processing and improves recognition efficiency.

[0119] In some embodiments, instead of setting a preset fluctuation direction feature, the periodicity of the fluctuation direction feature of the curve can be determined based on multiple fluctuation direction features of the real-time operating state curve, and the reference fluctuation direction feature for each relative position can be determined by combining the periodicity feature. Then, the fluctuation direction feature of the curve is compared with the determined reference fluctuation direction feature. Specifically, such as... Figure 3 As shown, normally, based on the periodicity, the relative positions corresponding to the numbers 2, 4, 6, and 8 should have the same fluctuation direction characteristics. The fluctuation direction characteristics that appear most frequently in these relative positions can be used as the reference fluctuation direction characteristics for these relative positions, and those that are inconsistent with the reference fluctuation direction characteristics are considered abnormal fluctuation direction characteristics.

[0120] Step S34: Determine the operating status of the built-in fan based on the comparison results.

[0121] Specifically, in some embodiments, step S34 includes:

[0122] Step S3 4 1: If the wave direction feature is opposite to the preset wave direction feature or the reference wave direction feature, the built-in fan operates in a reverse rotation state.

[0123] Based on step S33, if the fluctuation direction characteristics of a specific peak or trough of the curve are opposite to the preset fluctuation direction characteristics or reference fluctuation direction characteristics of the corresponding relative position, then the operating state of the built-in fan at the corresponding relative position is determined to be the reverse operating state. If all the fluctuation direction characteristics of the curve are consistent with the preset fluctuation direction characteristics or reference fluctuation direction characteristics, other judgment rules implemented above can be combined to determine whether there are other operating faults.

[0124] In the above detection method, the curve features include fluctuation direction features. These fluctuation direction features are compared with preset fluctuation direction features or reference fluctuation direction features, wherein the reference fluctuation direction features are determined based on multiple fluctuation direction features of the real-time operating status curve. The operating status of the built-in fan is determined based on the comparison results. Through this method, the existence of operational faults can be automatically and accurately identified based on the fluctuation direction features of the real-time operating status curve.

[0125] Reference Figure 6 , Figure 6 This is a detailed flowchart illustrating steps S22 and S30 in one embodiment of the detection method of the present invention. In some embodiments, step S22 includes:

[0126] Step S23: Extract the target relative operating parameters of the preset reference point from the real-time relative operating parameters.

[0127] In some embodiments, some or all of the data collected from all real-time relative operating parameters can be extracted as target relative operating parameters as needed. If only some data is extracted, the data collected by the data acquisition device and the built-in fan at specific relative positions can be selected as target relative operating parameters based on the speed at which the data acquisition device moves and the time interval between data collection.

[0128] Step S24: Calculate the average value of the extracted target relative operating parameters.

[0129] Step S25: Calculate the deviation between the target relative operating parameters and the average value for each preset reference point.

[0130] After extracting the target relative operating parameters based on step S2 and 3, the average value of the extracted target relative operating parameters is calculated, and the difference between each target relative operating parameter and the average value is calculated, i.e., the deviation. The calculated deviation is used as the real-time relative operating feature.

[0131] Step S30 includes:

[0132] Step S35: Determine whether there is a preset number of consecutive points with a deviation greater than a preset deviation.

[0133] Step S36: If it exists, then it is determined that the built-in fan is in an abnormal operating state.

[0134] If all fans inside the chassis are operating normally, the deviation is generally small. However, due to their different relative positions, the characteristics exhibit periodic fluctuations. Generally speaking, within a cycle, for several consecutive preset reference points, it's unlikely that all will deviate significantly from the average; some preset reference points will have target relative operating parameters that are only slightly different from the average. If a fan malfunctions, the target relative operating parameters for several consecutive preset reference points will generally deviate significantly from the average. Therefore, it's possible to determine whether there is a preset number of consecutive points where the deviation exceeds a preset deviation.

[0135] In some embodiments, the preset deviation can be determined by collecting a large amount of data from normally operating fans in advance, and the maximum deviation calculated from the data collected during normal fan operation can be used as the preset deviation. The preset number can be set as needed, and can be determined based on the spatial distance between the selected preset reference point and the actual distance to the fan; for example, it can be set to 3.

[0136] During step S35, each deviation can be compared with a preset deviation to determine if the calculated deviation is greater than the preset deviation. If so, counting begins. If the next deviation is greater than the preset deviation, counting continues until the count reaches a preset number or the count is reset to zero (if the next deviation is less than the preset deviation, the count is reset to zero and restarted). This determines whether there are a preset number of consecutive points with deviations greater than the preset deviation. If so, a fan malfunction is determined. Otherwise, the fan is determined to be operating normally, or it can be detected using other methods described in the above embodiments.

[0137] In the above detection method, target relative operating parameters of preset reference points are extracted from the real-time relative operating parameters; the average value of the extracted target relative operating parameters is calculated; the deviation between the target relative operating parameters of each preset reference point and the average value is calculated; it is determined whether there are a preset number of consecutive points with deviations greater than a preset deviation; if so, the built-in fan is determined to be in an abnormal operating state. Through this method, the abnormality of fan operation can be directly identified and determined by calculating the average value and deviation based on the collected data. The data processing method is relatively simple and efficient, which can improve the identification efficiency.

[0138] In addition, the present invention also provides a detection device.

[0139] The detection device of the present invention includes:

[0140] The data acquisition module is used to control the relative movement between the data acquisition device and the built-in fan, and to acquire the real-time relative operating parameters of the built-in fan;

[0141] The first determining module is used to determine the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters;

[0142] The second determining module is used to determine the operating status of the built-in fan based on the real-time relative operating characteristics.

[0143] The specific implementation of the detection device of the present invention can be referred to in the various embodiments of the detection method of the present invention, and will not be repeated here.

[0144] Furthermore, embodiments of the present invention also propose a computer-readable storage medium.

[0145] The present invention provides a detection program stored on a computer-readable storage medium, which, when executed by a processor, implements the steps of the detection method described above.

[0146] The method implemented when the detection program running on the processor is executed can be referred to in various embodiments of the detection method of the present invention, and will not be repeated here.

[0147] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0148] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0149] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0150] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for detecting a built-in fan in a product, characterized in that, The detection method includes: The control data acquisition device moves relative to the built-in fan and acquires the real-time relative operating parameters of the built-in fan; The real-time relative operating characteristics of the built-in fan are determined based on the real-time relative operating parameters. The operating status of the built-in fan is determined based on the real-time relative operating characteristics; The step of determining the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters includes: Plot the real-time operating status curve based on the real-time relative operating parameters; Extract the curve features of the real-time running status curve to serve as the real-time relative running features; The curve features include fluctuation direction features, and the step of determining the operating state of the built-in fan based on the real-time relative operating features includes: The fluctuation direction feature is compared with a preset fluctuation direction feature or a reference fluctuation direction feature, wherein the reference fluctuation direction feature is determined based on multiple fluctuation direction features of the real-time running state curve. The operating status of the built-in fan is determined based on the comparison results; The step of determining the operating status of the built-in fan based on the comparison results includes: If the wave direction feature is opposite to the preset wave direction feature or the reference wave direction feature, the built-in fan operates in a reverse rotation state. The number of built-in fans is multiple. A real-time operating status curve is plotted, with the relative position of the data acquisition device and the built-in fans as the horizontal axis and the raw data collected by the data acquisition device as the vertical axis.

2. The detection method as described in claim 1, characterized in that, The curve features include fluctuation amplitude features. The step of determining the operating status of the built-in fan based on the real-time relative operating characteristics includes: The fluctuation amplitude characteristics are compared with preset fluctuation amplitude characteristics or average fluctuation amplitude characteristics; The operating status of the built-in fan is determined based on the comparison results.

3. The detection method as described in claim 1, characterized in that, The step of determining the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters includes: Extract the target relative operating parameters of the preset reference point from the real-time relative operating parameters; Calculate the average value of the extracted target relative to the operating parameters; Calculate the deviation between the target relative operating parameters and the average value at each preset reference point; The step of determining the operating status of the built-in fan based on the real-time relative operating characteristics includes: Determine whether there is a preset number of consecutive points with a deviation greater than a preset deviation; If present, it is determined that the built-in fan is in an abnormal operating state.

4. The detection method as described in claim 1, characterized in that, The steps of controlling the data acquisition device to move relative to the built-in fan include: Keeping the built-in fan fixed, the data acquisition device is controlled to move relative to the built-in fan along a first preset trajectory; or Keep the data acquisition device fixed, and control the built-in fan to move relative to the data acquisition device along a second preset trajectory.

5. The detection method according to any one of claims 1-4, characterized in that, The data acquisition device includes an anemometer and / or a noise meter, and the real-time relative operating parameters include real-time relative wind speed parameters and / or real-time relative noise parameters.

6. A detection device, characterized in that, For applying the detection method according to any one of claims 1 to 4, the detection apparatus comprises: The data acquisition module is used to control the relative movement between the data acquisition device and the built-in fan, and to acquire the real-time relative operating parameters of the built-in fan; The first determining module is used to determine the real-time relative operating characteristics of the built-in fan based on the real-time relative operating parameters; The second determining module is used to determine the operating status of the built-in fan based on the real-time relative operating characteristics.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a detection program, which, when executed by a processor, implements the steps of the detection method as described in any one of claims 1 to 5.

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