Cooling Fault Detection Method, Device, Strip Steel Cooling Equipment and Storage Medium

Abstract

The present invention discloses a cooling fault detection method, device, strip steel cooling equipment and storage medium, belonging to the technical field of strip steel. Applied to strip steel cooling equipment, the strip steel cooling equipment is provided with a cooling system and an image acquisition device. The cooling system includes: a pressure stabilizing tank and a nozzle assembly. The present invention obtains the pressure change data of the pressure stabilizing tank and controls the image acquisition device to capture the operation image data of the nozzle assembly; determines the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data; determines the fault information according to the first characteristic data, achieving the beneficial effect of improving the qualified rate of the produced strip steel.

Description

Technical Field

[0001] The present invention relates to the field of strip steel, and particularly to a cooling fault detection method, device, strip steel cooling equipment and storage medium. Background Art

[0002] In the process of manufacturing strip steel, processes such as heating, descaling, cooling, and coiling are required. With the development of strip steel technology, higher requirements are placed on the surface quality of strip steel. Currently, the strip steel is generally cooled by an automated cooling system. A failure of any component during the cooling process can cause the coolant to fail to meet the cooling requirements. Usually, the machine is stopped to determine the cause of the failure only after the surface quality has deteriorated, resulting in a low qualified rate of the produced strip steel.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide a cooling fault detection method, aiming to improve the detection efficiency of faults, thereby improving the qualified rate of the produced strip steel. To achieve the above purpose, the present invention provides a cooling fault detection method applied to strip steel cooling equipment. The strip steel cooling equipment is provided with a cooling system and an image acquisition device. The cooling system includes a pressure stabilizing tank and a nozzle assembly. The cooling fault detection method includes the following steps:

[0005] Obtain the pressure change data of the pressure stabilizing tank and control the image acquisition device to capture the operation image data of the nozzle assembly;

[0006] Determine the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data;

[0007] Determine the fault information according to the first characteristic data.

[0008] Optionally, the step of determining the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data includes:

[0009] Determine the pressure change characteristic according to the pressure change data;

[0010] Determine the spraying characteristic of the nozzle assembly according to the operation image data;

[0011] Determine the first characteristic data according to the pressure change characteristic and the spraying characteristic data.

[0012] Optionally, the pressure change feature includes: a pressure change feature vector, and the step of determining the pressure change feature according to the pressure change data includes:

[0013] Normalize the pressure change data to obtain standard pressure change data;

[0014] Determine the feature values corresponding to the preset pressure feature types according to the standard pressure change data to obtain at least one feature value, where the preset pressure feature types include at least one of: pressure change direction, pressure mean value, pressure change waveform, and pressure change amplitude;

[0015] Determine the pressure change feature vector with the at least one feature value.

[0016] Optionally, the image acquisition device is an infrared camera, the injection feature is an injection feature vector, and the step of determining the injection feature of the nozzle assembly according to the operation image data includes:

[0017] Extract the feature values corresponding to the preset injection feature types from the operation image data according to image recognition, where the preset injection feature types include at least one of: injection direction, injection speed, geometric features of the temperature change of the strip steel, and texture features of the strip steel;

[0018] Determine the injection feature vector with the at least one feature value.

[0019] Optionally, the image acquisition device is a visible light camera, and the step of determining the injection feature of the nozzle assembly according to the operation image data includes:

[0020] Determine the clarity of each area of the strip steel according to the operation image data to obtain a plurality of clarity data;

[0021] Determine the amount of fog generated during the operation of the nozzle assembly according to the plurality of clarity data;

[0022] Use the amount of fog as the injection feature.

[0023] Optionally, the first feature data is a first feature vector, and the step of determining the fault information according to the first feature data includes:

[0024] Calculate the feature distance according to the first feature vector and each second feature vector, where the second feature vector is the feature vector corresponding to the fault condition of the strip steel cooling equipment before the current moment;

[0025] Determine the fault information according to the feature distance.

[0026] Optionally, before the step of determining the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data, the method further includes:

[0027] Determining identification information corresponding to each operation time according to the control data of the strip steel cooling equipment to obtain a first correspondence, where the first correspondence is the correspondence between the operation time and the identification information, and the identification information is the operation condition of the current cooling system;

[0028] Determining the first identification information corresponding to the pressure change data according to the first correspondence and the time corresponding to the pressure change data, and determining the second identification information corresponding to the operation image data according to the first correspondence and the time corresponding to the operation image data;

[0029] Matching the pressure change data and the operation image data according to the time sequence, the first identification information, and the second identification information.

[0030] In addition, to achieve the above object, the present invention further provides a cooling fault detection device. The cooling fault detection device is provided with a cooling system and an image acquisition device. The cooling system includes: a pressure stabilizing tank and a nozzle assembly. The cooling fault detection device includes:

[0031] An acquisition module, configured to acquire the pressure change data of the pressure stabilizing tank and control the image acquisition device to capture the operation image data of the nozzle assembly;

[0032] A calculation module, configured to determine the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data;

[0033] An identification module, configured to determine fault information according to the first characteristic data.

[0034] In addition, to achieve the above object, the present invention further provides a strip steel cooling equipment, which includes: a memory, a processor, and a cooling fault detection program stored on the memory and executable on the processor. The cooling fault detection program is configured to implement the steps of the cooling fault detection method described in any one of the above.

[0035] In addition, to achieve the above object, the present invention further provides a storage medium, on which a cooling fault detection program is stored. When the cooling fault detection program is executed by a processor, it implements the steps of the cooling fault detection method described in any one of the above.

[0036] The present invention provides a cooling fault detection method. This method obtains the pressure change data and operation image data of the pressure stabilizing tank, and determines the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data, thereby obtaining two mutually related characteristic data, so as to locate and identify fault information during operation, improve the identification efficiency of fault problems, and further improve the product yield of strip steel. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a schematic structural diagram of a strip steel cooling equipment in the hardware operating environment related to the embodiment solution of the present invention;

[0038] Figure 2 is a schematic flow chart of the first embodiment of the cooling fault detection method of the present invention;

[0039] Figure 3 is a schematic flow chart of the second embodiment of the cooling fault detection method of the present invention;

[0040] Figure 4 is a schematic flow chart of the third embodiment of the cooling fault detection method of the present invention;

[0041] Figure 5 is a schematic flow chart of the sixth embodiment of the cooling fault detection method of the present invention.

[0042] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] Refer to Figure 1 , Figure 1 is a schematic structural diagram of a strip steel cooling equipment in the hardware operating environment related to the embodiment solution of the present invention.

[0045] As Figure 1As shown in the figure, the strip steel cooling device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, an interaction device 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The interaction device 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the interaction device 1003 may also be connected to the communication bus through a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wireless-Fidelity (WI-FI) interface). The memory 1005 may be a high-speed Random Access Memory (RAM) or a stable Non-Volatile Memory (NVM), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0046] Those skilled in the art can understand that Figure 1 the structure shown in the figure does not constitute a limitation on the strip steel cooling device, and it may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0047] As Figure 1 shown, the memory 1005, as a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and a cooling fault detection program.

[0048] In Figure 1 the strip steel cooling device shown in the figure, the network interface 1004 is mainly used for data communication with other devices; the interaction device 1003 is mainly used for data interaction with users; the processor 1001 and the memory 1005 in the strip steel cooling device of the present invention may be arranged in the strip steel cooling device. The strip steel cooling device calls the cooling fault detection program stored in the memory 1005 through the processor 1001 and executes the cooling fault detection method provided by the embodiments of the present invention.

[0049] The embodiments of the present invention provide a cooling fault detection method. Referring to Figure 2 , Figure 2 is a schematic flowchart of the first embodiment of a cooling fault detection method of the present invention. In this embodiment, it is applied to a strip steel cooling device, and the strip steel cooling device is provided with a cooling system and an image acquisition device. The cooling system includes: a pressure stabilizing tank and a nozzle assembly. The cooling fault detection method includes the following steps:

[0050] Step S1, obtain the pressure change data of the pressure stabilizing tank and control the image acquisition device to capture the operation image data of the nozzle assembly;

[0051] In this embodiment, preferably, the coolant is water, and of course it can also be liquid nitrogen. In addition to the pressure stabilizing tank and the nozzle assembly, the cooling system further includes a water pump and a water tank. The number of nozzle assemblies here is not limited. It may include nozzle assemblies for cooling the upper surface of the strip steel and may also include nozzle assemblies for cooling the lower surface of the strip steel. The pressure stabilizing tank contains water and gas. Generally, the gas here can be air or nitrogen. The pressure stabilizing tank is mainly used to maintain pressure balance. When the pressure in the cooling system changes, the gas pressure in the pressure stabilizing tank will also change accordingly, so as to maintain the pressure balance of the system. When the cooling system pressure rises, the gas volume decreases and the gas pressure increases; when the cooling system pressure drops, the volume increases and the gas pressure decreases. The pressure stabilizing tank can effectively ensure the water pressure during the opening and closing process of the nozzles of the nozzle assembly under normal working conditions, and at the same time avoid the change of the nozzle pressure caused by the water replenishment of the water pump. During the actual operation process, the pressure change data will fluctuate within a range that meets the requirements, that is, within the working pressure range. Specifically, the image acquisition device captures the operation image data of the nozzle assembly. In addition to being able to capture the nozzle assembly, it can also capture the contact part between the coolant and the strip steel.

[0052] Step S2, determine the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data;

[0053] Specifically, extract the corresponding characteristics in the pressure change data and the corresponding characteristics in the operation image data as the first characteristic data. Here, the first characteristic data may include: pressure value, average pressure, coolant velocity, and spraying range.

[0054] Step S3, determine the fault information according to the first characteristic data.

[0055] Since the first characteristic data actually contains the final data of the sprayed coolant and the data of the container directly supplying the coolant, therefore, the location of the fault can be determined through the above first characteristic data to obtain the fault information.

[0056] In this embodiment, by obtaining the pressure change data and the operation image data of the pressure stabilizing tank, and determining the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data, two mutually related characteristic data can be obtained, so that the fault information can be located and identified during operation, improving the identification efficiency of fault problems, and further improving the product yield of the strip steel.

[0057] Further, based on the first embodiment, a second embodiment of the cooling fault detection method of the present invention is proposed. In this embodiment, referring to Figure 3 , the step of determining the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the operation image data includes:

[0058] Step S21, determining the pressure change characteristics according to the pressure change data;

[0059] Specifically, the pressure change data is statistically analyzed to obtain the mean, variance, standard deviation, maximum value, minimum value, etc. of the pressure change data. In addition, when the duration corresponding to the pressure change data is greater than the preset duration, the pressure change data can also be subjected to Fourier transform to extract the corresponding spectrum data as the pressure change characteristics. In addition, the fluctuation characteristics of the pressure change data can also be extracted. For example, the fluctuation characteristics during the opening and closing of the nozzle of the nozzle assembly are extracted, and the fluctuation characteristics during the operation of the water pump are extracted.

[0060] Step S22, determining the spraying characteristics of the nozzle assembly according to the operation image data;

[0061] Specifically, in this embodiment, the spraying characteristics are not only determined by extracting the image of the nozzle assembly in the operation image data and the image of the coolant sprayed by the nozzle assembly, but also by extracting the spraying direction of the coolant included in the operation image data and the contact area of the coolant on the strip steel through image recognition. Optionally, different types of spraying characteristics can be extracted according to different camera types. In addition, in this embodiment, the number and type of image acquisition devices are not limited, and multiple cameras can be included. The type of camera can be an infrared camera or a visible light camera.

[0062] Step S23, determining the first characteristic data according to the pressure change characteristics and the spraying characteristic data.

[0063] In this embodiment, the first characteristic data is determined according to the pressure change characteristics and the spraying characteristic data, thereby ensuring the diversity of data sources, increasing the dimension of the data, and effectively improving the accuracy of subsequent determination of fault information in the case of multi-data dimensions.

[0064] Further, the pressure change characteristics include: a pressure change characteristic vector, and the step of determining the pressure change characteristics according to the pressure change data includes:

[0065] Normalize the pressure change data to obtain the standard pressure change data;

[0066] Determine the characteristic values corresponding to the preset pressure characteristic types according to the standard pressure change data, and obtain at least one characteristic value. The preset pressure characteristic types include at least one of: pressure change direction, pressure mean value, pressure change waveform, and pressure change amplitude;

[0067] Determine the pressure change feature vector based on the at least one characteristic value.

[0068] After each detection of the pressure stabilizing tank, it is necessary to correct the pressure data of the pressure stabilizing tank. After replacing the pressure stabilizing tank, the corresponding correction coefficient needs to be set according to the parameters of the pressure stabilizing tank. Specifically, determine the characteristic values that need to be extracted from the standard pressure change data according to the preset pressure characteristic types. And determine the corresponding pressure change feature vector according to the preset pressure characteristic types. Preferably, the preset pressure characteristic types may include all of the following parameters: pressure change direction, pressure mean value, pressure change waveform, and pressure change amplitude.

[0069] In this embodiment, by determining the characteristic values corresponding to the preset pressure characteristic types from the standard pressure change data, at least one characteristic value is obtained, so that the amount of data for subsequent processing can be effectively reduced while obtaining the core pressure change situation, thereby improving the efficiency of subsequent fault analysis.

[0070] Further, based on the first embodiment or the second embodiment, a third embodiment of the cooling fault detection method of the present invention is proposed. In this embodiment, refer to Figure 4 , the image acquisition device is an infrared camera, the injection characteristic is an injection characteristic vector, and the step of determining the injection characteristic of the nozzle assembly according to the operation image data includes:

[0071] Step S221, extract the characteristic values corresponding to the preset injection characteristic types from the operation image data according to image recognition. The preset injection characteristic types include at least one of: injection direction, injection speed, geometric characteristics of the temperature change of the strip steel, and texture characteristics of the strip steel;

[0072] Step S222, determine the injection characteristic vector based on the at least one characteristic value.

[0073] If it is recognized that the image acquisition device includes an infrared camera, the specific execution process of the operation image data collected by the infrared camera in step S22 is to execute step S211 and step S222 of this embodiment. Specifically, in this embodiment, the temperature change situation can also be determined according to the operation image data corresponding to two different times before and after. In addition, the geometric feature of the temperature change of the strip steel specifically refers to the morphology of the image caused by the difference in temperature at each position on the surface of the strip steel. The texture feature is actually the texture that appears during the opening and closing of the nozzle assembly and the adjustment of the spraying position. For the operation of the automated cooling equipment, its texture should be the same under normal working conditions.

[0074] In this embodiment, the feature value corresponding to the preset spraying feature type is extracted from the operation image data according to image recognition, thereby improving the accuracy of the spraying feature vector.

[0075] Further, based on the first embodiment or the second embodiment, a fourth embodiment of the cooling fault detection method of the present invention is proposed. In this embodiment, the image acquisition device is a visible light camera, and the step of determining the spraying feature of the nozzle assembly according to the operation image data includes:

[0076] Determine the clarity of each area of the strip steel according to the operation image data to obtain a plurality of clarity data;

[0077] Determine the amount of mist generated during the operation of the nozzle assembly according to the plurality of clarity data;

[0078] Use the amount of mist as the spraying feature.

[0079] It should be noted that during the cooling process, water will form water vapor. Currently, during the production process, most of the water vapor can be removed by a fan. However, during the process of removing the water vapor, some of the water vapor will cool down, and thus the water vapor will atomize to form a water mist. In this embodiment, the amount of mist in each area should be stable. When the amount of mist changes, it indicates that there is a change in the operation of the cooling equipment. Of course, in this embodiment, the operation image data can also be used to determine the water spraying direction. In other embodiments, when the image acquisition device includes both a visible light camera and an infrared camera, corresponding processing steps can be determined for different data and the data can be mutually verified, such as the verification of the water spraying direction.

[0080] In this embodiment, the sharpness of each area of the strip steel is determined according to the running image data to obtain a plurality of sharpness data. The amount of mist generated during the operation of the nozzle assembly is determined according to the plurality of sharpness data. Taking the amount of mist as the spraying feature, compared with the extracted spraying speed and spraying direction, it is unique information that can be obtained by visible light energy, thereby increasing the data volume of the spraying feature. The calculation method of the sharpness data can be: extracting the sharpness of each area through an image sharpness analysis algorithm.

[0081] Further, based on any of the above embodiments, a fifth embodiment of the cooling fault detection method of the present invention is proposed. In this embodiment, the first feature data is a first feature vector, and the step of determining the fault information according to the first feature data includes:

[0082] Calculating a feature distance according to the first feature vector and each second feature vector, where the second feature vector is a feature vector corresponding to the fault condition of the strip steel cooling equipment before the current moment;

[0083] Determining the fault information according to the feature distance.

[0084] In this embodiment, optionally, a plurality of second feature vectors can form a vector space, and according to the clustering algorithm and the type of fault, the center point corresponding to each fault type is determined, and the distances from the center points of each fault type are calculated respectively, so as to determine the fault type. The fault types here can include: impurities in the coolant, insufficient water delivery by the water pump, partial blockage of the nozzle, too long valve response time, etc.

[0085] Further, based on any of the above embodiments, a sixth embodiment of the cooling fault detection method of the present invention is proposed. In this embodiment, referring to Figure 5 , before the step of determining the first feature data of the strip steel cooling equipment during operation according to the pressure change data and the running image data, it further includes:

[0086] Step S201, determining the identification information corresponding to each running time according to the control data of the strip steel cooling equipment to obtain a first correspondence, where the first correspondence is the correspondence between the running time and the identification information, and the identification information is the running condition of the current cooling system;

[0087] The running condition of the current cooling system can be in different situations, specifically including: opening the valve to make the nozzle spray the coolant, continuously spraying water for cooling, the water pump delivering water, etc.

[0088] Step S202: Determine the first identification information corresponding to the pressure change data according to the first correspondence relationship and the time corresponding to the pressure change data, and determine the second identification information corresponding to the running image data according to the first correspondence relationship and the time corresponding to the running image data;

[0089] In this embodiment, after determining the first identification information and the second identification information, mark the pressure change data and the running image data respectively.

[0090] Step S203: Match the pressure change data and the running image data according to the time sequence, the first identification information, and the second identification information.

[0091] Divide the data corresponding to the first identification information and the second identification information into the same groups, and arrange and match them according to the time sequence in the same groups. Thus, it can be determined that the pressure change data and the running image data match.

[0092] In addition, an embodiment of the present invention further provides a cooling failure detection device. The cooling failure detection device is provided with a cooling system and an image acquisition device. The cooling system includes: a pressure stabilizing tank and a nozzle assembly. The cooling failure detection device includes:

[0093] An acquisition module, configured to acquire the pressure change data of the pressure stabilizing tank and control the image acquisition device to capture the running image data of the nozzle assembly;

[0094] A calculation module, configured to determine the first characteristic data of the strip steel cooling equipment during operation according to the pressure change data and the running image data;

[0095] An identification module, configured to determine failure information according to the first characteristic data;

[0096] The cooling failure detection device here can execute the steps pointed out in the above embodiment.

[0097] In addition, an embodiment of the present invention further provides a strip steel cooling equipment, which includes: a memory, a processor, and a cooling failure detection program stored on the memory and executable on the processor. The cooling failure detection program is configured to implement the steps of the cooling failure detection method described in any one of the above.

[0098] In addition, an embodiment of the present invention further provides a storage medium, on which a cooling failure detection program is stored. When the cooling failure detection program is executed by a processor, it implements the steps of the cooling failure detection method described in any one of the above.

[0099] It should be noted that in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent in such a process, method, article or system. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or system including that element.

[0100] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0101] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that makes a contribution to the prior art can be embodied in the form of a software product. This computer software product is stored in a storage medium as described above (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0102] The above are only the preferred embodiments of the present invention and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A cooling fault detection method, characterized in that: Applied to a plate and strip steel cooling device, the plate and strip steel cooling device is provided with a cooling system and an image acquisition device, the cooling system comprises: a pressure stabilizing tank and a nozzle assembly, and the cooling fault detection method comprises the following steps: Acquiring pressure change data of the pressure stabilizing tank and controlling the image acquisition device to capture operation image data of the nozzle assembly; Determine first characteristic data of the plate and strip steel cooling device during operation according to the pressure change data and the operation image data; determining fault information according to the first characteristic data; The step of determining the first characteristic data of the plate strip cooling device during operation according to the pressure change data and the operation image data comprises: determining a pressure change characteristic according to the pressure change data; determining a spray characteristic of the nozzle assembly based on the operational image data; Determine the first characteristic data according to the pressure change characteristic and the injection characteristic data; The first characteristic data is a first characteristic vector, and the step of determining fault information according to the first characteristic data includes: Calculating a characteristic distance according to the first characteristic vector and each second characteristic vector, wherein the second characteristic vector is a characteristic vector corresponding to a fault condition of the plate strip cooling device before the current moment; Determining the fault information according to the characteristic distance; The image acquisition device is a visible light camera, and the step of determining the injection characteristics of the nozzle assembly according to the operation image data includes: Determine the clarity of each area of ​​the plate and strip steel according to the running image data to obtain a plurality of clarity data; determining an amount of mist generated during operation of the nozzle assembly based on the plurality of clarity data; According to the mist volume as the spray feature; or The image acquisition device is an infrared camera, the injection feature is an injection feature vector, and the step of determining the injection feature of the nozzle assembly according to the running image data includes: Extracting a feature value corresponding to a preset injection feature type from the operation image data according to image recognition, wherein the preset injection feature type includes: at least one of an injection direction, an injection speed, a geometric feature of a temperature change of the plate and strip steel, and a texture feature of the plate and strip steel; The at least one characteristic value is used to determine the injection characteristic vector.

2. The cooling fault detection method according to claim 1, characterized in that: The pressure change feature includes: a pressure change feature vector, and the step of determining the pressure change feature according to the pressure change data includes: Standardizing the pressure change data to obtain standard pressure change data; Determine a characteristic value corresponding to a preset pressure characteristic type according to the standard pressure change data to obtain at least one characteristic value, wherein the preset pressure characteristic type includes: at least one of a pressure change direction, a pressure mean value, a pressure change waveform, and a pressure change amplitude; The at least one eigenvalue is used to determine the pressure variation eigenvector.

3. The cooling fault detection method according to claim 1, characterized in that: Before the step of determining the first characteristic data of the plate and strip steel cooling device during operation according to the pressure change data and the operation image data, the step further includes: Determine identification information corresponding to each operating time according to the control data of the plate and strip steel cooling device, and obtain a first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the operating time and the identification information, and the identification information is the current operating status of the cooling system; Determine first identification information corresponding to the pressure change data according to the first corresponding relationship and the time corresponding to the pressure change data, and determine second identification information corresponding to the operation image data according to the first corresponding relationship and the time corresponding to the operation image data; The pressure change data and the operation image data are matched according to the time sequence, the first identification information and the second identification information.

4. A cooling fault detection device, characterized in that: The cooling fault detection device implements the steps of the cooling fault detection method according to any one of claims 1 to 3, and is provided with a cooling system and an image acquisition device, wherein the cooling system comprises: a pressure stabilizing tank and a nozzle assembly, and the cooling fault detection device comprises: An acquisition module, used for acquiring pressure change data of the pressure stabilizing tank and controlling the image acquisition device to capture operation image data of the nozzle assembly; A calculation module is used to determine the first characteristic data of the plate and strip steel cooling device during operation according to the pressure change data and the operation image data; the step of determining the first characteristic data of the plate and strip steel cooling device during operation according to the pressure change data and the operation image data comprises: determining the pressure change characteristics according to the pressure change data; determining the injection characteristics of the nozzle assembly according to the operation image data; determining the first characteristic data according to the pressure change characteristics and the injection characteristic data An identification module is used to determine fault information according to the first characteristic data.

5. A strip steel cooling device, characterized in that: The plate and strip steel cooling equipment comprises: a memory, a processor and a cooling fault detection program stored in the memory and executable on the processor, wherein the cooling fault detection program is configured to implement the steps of the cooling fault detection method according to any one of claims 1 to 3.

6. A storage medium, characterized in that: The storage medium stores a cooling fault detection program, and when the cooling fault detection program is executed by the processor, the steps of the cooling fault detection method according to any one of claims 1 to 3 are implemented.

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