High efficiency filter fault detection method, device, equipment and storage medium

Abstract

The application relates to a high-efficiency filter fault detection method, device and equipment and a storage medium, and is applied to the filter field, wherein the method comprises the following steps: acquiring equipment operation data, wherein the equipment operation parameter data at least comprises a plurality of operation parameter data and corresponding parameter types; searching for corresponding standard data ranges according to the parameter types; comparing the operation parameter data with endpoint values of the standard data ranges; if the operation parameter data is located outside the standard data ranges, searching for corresponding fault reasons in a preset fault database according to the parameter types; and generating a maintenance instruction according to the fault reasons. The application has the technical effect of realizing automatic detection of air filter faults.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of filters, in particular to a high-efficiency filter fault detection method, device, equipment and storage medium. BACKGROUND

[0002] An air filter is a device that captures dust from gas-solid two-phase flow through the action of a porous filter material and purifies the gas. It purifies the air with low dust content and sends it into the room to ensure the process requirements of the clean room and the air cleanliness in the general air conditioning room.

[0003] The air filter includes an initial filter, a medium-efficiency filter, a high-efficiency filter and a sub-high-efficiency filter; among them, the high-efficiency filter is mainly used for capturing 0.5um or more particulate dust and various suspended matters, and is used as the terminal filter of various filter fault detection systems. Ultrafine glass fiber paper is used as filter material, and materials such as adhesive board paper and aluminum foil plate are folded to form partition plates, which are sealed with new polyurethane sealant, and are made into an outer frame with galvanized sheet, stainless steel sheet and aluminum alloy profile.

[0004] At present, the air filter is used more and more frequently in people's daily production and life, so it is more and more important to realize the automatic detection of air filter faults. SUMMARY

[0005] In order to realize the automatic detection of air filter faults, the application provides a high-efficiency filter fault detection method, device, equipment and storage medium.

[0006] In the first aspect, the application provides a high-efficiency filter fault detection method, which adopts the following technical scheme: the method comprises:

[0007] Obtaining equipment operation data, wherein the equipment operation data at least includes a plurality of operation parameter data and corresponding parameter types;

[0008] According to the parameter type, the corresponding standard data range is found;

[0009] The operation parameter data is compared with the end point value of the standard data range;

[0010] If the operation parameter data is located outside the standard data range, the corresponding fault reason is found in the preset fault database according to the parameter type;

[0011] According to the fault reason, a maintenance instruction is generated.

[0012] In a specific implementation scheme, the obtaining of the equipment operation data specifically comprises:

[0013] According to a preset clock signal, initial equipment operation data is collected at fixed intervals to form an equipment operation data set, wherein the initial equipment operation data at least includes a plurality of initial operation parameter data and corresponding parameter types;

[0014] The initial operation parameter data of the same parameter type is screened to obtain maximum operation parameter data and minimum operation parameter data;

[0015] The equipment operation data is generated according to the maximum operation parameter data, the minimum operation parameter data and the corresponding parameter types.

[0016] In a specific embodiment, the corresponding standard data range is searched according to the parameter type, specifically including:

[0017] The equipment failure data is obtained, wherein the equipment failure data at least includes parameter types and corresponding failure times;

[0018] The plurality of operation parameter data in the equipment operation data is sorted according to the failure times corresponding to the parameter types;

[0019] According to the serial number value of the operation parameter data, the standard data range corresponding to the parameter type to which the operation parameter data belongs is searched in sequence.

[0020] In a specific embodiment, the method further includes:

[0021] The maintenance time of the last efficient filter is determined as a historical maintenance time;

[0022] The current time is obtained;

[0023] The time difference between the historical maintenance time and the current time is calculated;

[0024] It is determined whether the time difference reaches a preset maintenance period;

[0025] If the time difference reaches the maintenance period, a maintenance instruction is generated.

[0026] In a specific embodiment, after the maintenance instruction is generated according to the failure cause, the method further includes:

[0027] The failure times in the equipment failure data are searched according to the parameter types corresponding to the failure causes;

[0028] The failure times are modified as maximum failure times;

[0029] The maximum failure times are compared with a preset failure time threshold;

[0030] If the maximum number of failures exceeds the threshold number of failures, a first replacement instruction is generated.

[0031] In one specific implementation, after the number of failures is found according to the parameter type corresponding to the failure cause in the device failure data, the method further includes:

[0032] According to a preset number of values, a failure time closest to a current time node is found, which is recorded as a historical failure time set.

[0033] The maximum historical failure time and the minimum historical failure time in the historical failure time set are calculated.

[0034] If a time difference between the maximum historical failure time and the minimum historical failure time is less than a preset interval threshold, a second replacement instruction is generated.

[0035] In one specific implementation, the parameter type includes a rated air volume of a high-efficiency filter and a resistance parameter.

[0036] In a second aspect, the application provides a high-efficiency filter failure detection device, which adopts the following technical solution: the device includes:

[0037] A device operation data acquisition module is configured to acquire device operation data, the device operation data including at least a plurality of operation parameter data and corresponding parameter types.

[0038] A standard data range acquisition module is configured to find corresponding standard data ranges according to the parameter types.

[0039] A device operation data comparison module is configured to compare the operation parameter data with endpoint values of the standard data ranges.

[0040] A device failure cause finding module is configured to find corresponding failure causes in a preset failure database according to the parameter types if the operation parameter data is outside the standard data ranges.

[0041] A device failure instruction generation module is configured to generate a maintenance instruction according to the failure causes.

[0042] In a third aspect, the application provides a computer device, which adopts the following technical solution: including a memory and a processor, the memory stores a computer program capable of being loaded and executed by the processor and performing any of the above high-efficiency filter failure detection methods.

[0043] In a fourth aspect, the application provides a computer readable storage medium, which adopts the following technical solution: storing a computer program capable of being loaded and executed by a processor and performing any of the above high-efficiency filter failure detection methods. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 is a flow chart of the high-efficiency filter fault detection method in the embodiment of the present application.

[0045] Figure 2 is a structural block diagram of the high-efficiency filter fault detection device in the embodiment of the present application.

[0046] The reference signs: 301, device operation data acquisition module; 302, standard data range acquisition module; 303, device operation data comparison module; 304, device fault reason finding module; 305, device fault instruction generation module. DETAILED DESCRIPTION

[0047] The following will be described in detail in combination with the accompanying drawings. Figures 1-2 The present application will be further described in detail.

[0048] The embodiment of the present application discloses a high-efficiency filter fault detection method. The method is applied to a filter fault detection system, and corresponding instructions of the method are stored in a control unit of the filter fault detection system in advance.

[0049] As shown in the method, the method comprises the following steps: Figure 1

[0050] S10, acquiring device operation data.

[0051] Specifically, the device operation data at least comprises a plurality of operation parameter data and corresponding parameter types. In the embodiment, the parameter types comprise a rated air volume of the high-efficiency filter and a resistance parameter. The rated air volume refers to the maximum air volume that can pass through the filter, which depends on the area of the filter material. For example, when the air flow velocity passing through the filter material is the same, the larger the area of the filter material is, the larger the air volume passing through is. The resistance parameter refers to the resistance of the filter to the air flow. When the filter is used for a period of time, dust in the air is accumulated on the surface of the filter device, and the accumulation degree of the dust increases with the increase of the use time of the filter. The more dust attached to the filter device, the greater the resistance of the filter to the air flow is. When the resistance of the filter increases to a certain specified value, the filter is scrapped. The filter fault detection system detects the rated air volume and the resistance parameter of the high-efficiency filter by using a pre-set sensor to obtain corresponding operation parameter data. The operation parameter data is a group of real numbers greater than 0. When the detected operation parameter data is less than 0, it can be determined that the operation parameter data is error data, and the possible reason is that the sensor detects incorrectly. The filter fault detection system eliminates the error data in the operation parameter data to obtain effective data for fault detection of the filter.

[0052] S20, finding a corresponding standard data range according to the parameter type. ​

[0053] Specifically, since the equipment operation data is essentially a data set containing operation parameters of different parameter types, the parameter types are inconsistent, and the corresponding reasonable value range is also different. The filter fault detection system finds the standard data range matched with the parameter type in the preset standard database.

[0054] S30, comparing the operation parameter data with the endpoint value of the standard data range.

[0055] The filter fault detection system compares the operation parameter data found to be consistent with the standard data range of the parameter type. Specifically, the filter fault detection system first compares the operation parameter data with the minimum value in the standard data range. If the operation parameter data is higher than the minimum value in the standard data range, it is compared with the maximum value in the standard data range again. If the operation parameter data is lower than the maximum value in the standard data range, it indicates that the filter index under the parameter type is qualified.

[0056] S40, if the operation parameter data is outside the standard data range, the corresponding fault reason is found in the preset fault database according to the parameter type.

[0057] Specifically, if the operation parameter data is higher than the maximum value in the standard data range or lower than the minimum value in the standard data range, it indicates that the operation parameter data is outside the standard data range and is unqualified. At this time, the filter operation state is unstable, and the filter fault detection system finds the corresponding fault reason in the preset fault database according to the unqualified operation parameter data.

[0058] S50, generating a maintenance instruction according to the fault reason.

[0059] Specifically, the filter fault detection system sends the found fault reason to the intelligent terminal of the worker in the form of an instruction, so as to inform that the filter operation state is poor and needs to be stopped and maintained. The filter fault detection system judges the working state of the filter by monitoring the operation data of the filter. Once the operation data is abnormal, a message prompt is immediately given, realizing the effect of automatically detecting the fault of the filter.

[0060] In one embodiment, in order to better measure the operation state of the filter, the equipment operation data is obtained, which can be specifically implemented as follows:

[0061] The filter fault detection system controls the sensor to collect the operation parameter data of the filter according to the preset clock signal every fixed time interval, and each collection process lasts for a period of time, that is, the sensor monitors the operation state of the filter during the process to obtain a series of operation parameter data, and the collected operation parameter data is recorded as initial operation parameter data, and there are several initial operation parameter data under the same parameter type; next, the filter fault detection system filters the initial operation parameter data to obtain the maximum value and the minimum value, which are recorded as the maximum operation parameter and the minimum operation parameter respectively, and the filter fault detection system only retains the maximum operation parameter and the minimum operation parameter under the same parameter type, and removes the remaining initial operation parameter data from the equipment operation data set to obtain the operation parameter data used for judging whether the filter is faulty. The filter fault detection system sorts the operation parameter data, reduces the data amount as much as possible under the condition of retaining the data value, and helps to improve the fault detection efficiency of the filter fault detection system.

[0062] In one embodiment, in order to find out the fault reason of the filter as soon as possible in the case that the operation state of the filter is unstable, the corresponding standard data range is found according to the parameter type, which can be specifically performed as follows:

[0063] The filter fault detection system obtains equipment fault data, which at least includes parameter type, fault times and fault time. The fault time corresponds to the fault times, and the filter fault detection system sorts a plurality of operation parameters in the equipment operation parameter according to the fault times corresponding to different parameter types after obtaining the equipment fault data; in order to facilitate understanding, an example is given, for example, the parameter types are rated air volume and resistance parameter, the operation parameter data under the rated air volume is A data, the operation parameter data under the resistance parameter is B data, the fault times corresponding to the rated air volume is 3 times, and the fault times corresponding to the resistance parameter is 1 time, then the filter fault detection system divides the priority of A data and B data, that is, the filter fault detection system compares A data with the corresponding standard data range first, and then compares B data with the corresponding standard data range, and it should be noted that in order to ensure that all current faults of the filter can be investigated as much as possible, even if A data detection fails, the filter fault detection system will continue to detect B data. Setting priority for operation parameter data can make the filter fault detection system investigate the fault with the highest probability first, and thus help to improve the speed of finding out the fault reason.

[0064] In one embodiment, in order to reduce the possibility of filter failure, the method can also be performed as follows:

[0065] The filter fault detection system determines the last maintenance time of the high-efficiency filter as a historical maintenance time. The staff will regularly check the filter, and whenever the staff completes the current check task, the check date will be uploaded to the filter fault detection system. After the filter fault detection system receives the check date, it will update the originally stored maintenance time, that is, the historical maintenance time. Then, the filter fault detection system obtains the current time, calculates the time difference between the historical maintenance time and the current time, compares the calculated time difference with the preset check period, judges whether the current time point is the predetermined check time, and if so, generates a maintenance instruction and sends the generated maintenance instruction to the staff's intelligent terminal, thereby achieving the effect of regular maintenance of the filter, and further helping to reduce the possibility of filter failure during operation.

[0066] In one embodiment, to further reduce the possibility of filter failure, after generating the maintenance instruction according to the fault reason, the following steps can also be performed:

[0067] The filter fault detection system will look up the corresponding fault number in the equipment fault data according to the parameter type corresponding to the fault reason, modify the fault number, specifically, add one to the fault number, and update the fault number as the maximum fault number. Then, the filter fault detection system compares the maximum fault number with the preset fault number threshold. If the maximum fault number exceeds the fault number threshold, the filter fault detection system will generate a first replacement instruction to remind the staff that the filter needs to be updated. Since the occurrence of a certain fault of the filter reaches a certain number of values, it is extremely likely that the service life of the filter has reached the upper limit and needs to be eliminated. The filter fault detection system realizes the effect of automatically eliminating aging filters by measuring the fault number, further reducing the possibility of filter failure.

[0068] In one embodiment, to further reduce the possibility of filter failure, after looking up the fault number in the equipment fault data according to the parameter type corresponding to the fault reason, the following steps can also be performed:

[0069] The filter fault detection system searches for the nearest fault time to the current time point based on a preset quantity value, recording it as a historical fault time set. For example, if the preset quantity value is 5, it will query the five nearest fault times to the current time point under a certain parameter type, forming a historical fault time set. Then, it filters out the maximum and minimum historical fault times from the set—that is, the two fault times closest and farthest from the current time point. It calculates the time interval between the maximum and minimum historical fault times and compares it to a preset interval threshold. If the time difference is less than the preset threshold, the filter fault detection system generates a second replacement instruction, reminding staff to replace the relevant parts, and sends the generated second replacement instruction to the staff's smart terminal. When a filter fault occurs consecutively within a short period, it indicates that the filter and the related components are no longer usable and need to be replaced. The filter fault detection system effectively reminds staff to replace unusable parts.

[0070] Figure 1 This is a flowchart illustrating a high-efficiency filter fault detection method in one embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows; unless explicitly stated otherwise, there is no strict order requirement for the execution of these steps, and they can be executed in other orders; and Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0071] Based on the above method, this application also discloses a high-efficiency filter fault detection device.

[0072] like Figure 2 As shown, the device includes the following modules:

[0073] The equipment operation data acquisition module 301 is used to acquire equipment operation data, which includes at least several operation parameter data and corresponding parameter types.

[0074] The standard data range acquisition module 302 is used to find the corresponding standard data range according to the parameter type.

[0075] The device operation data comparison module 303 is configured to compare the operation parameter data with the endpoint value of the standard data range;

[0076] The device fault reason searching module 304 is configured to search for the corresponding fault reason in the preset fault database according to the parameter type if the operation parameter data is out of the standard data range;

[0077] The device fault instruction generating module 305 is configured to generate the maintenance instruction according to the fault reason.

[0078] In an embodiment, the device operation data obtaining module 301 is further configured to collect initial device operation data at a fixed interval according to a preset clock signal to form a device operation data set, wherein the initial device operation data at least includes a plurality of initial operation parameter data and corresponding parameter types;

[0079] The initial operation parameter data of the same parameter type is filtered to obtain the maximum operation parameter data and the minimum operation parameter data;

[0080] The device operation data is generated according to the maximum operation parameter data, the minimum operation parameter data and the corresponding parameter types.

[0081] In an embodiment, the standard data range obtaining module 302 is further configured to obtain device fault data, wherein the device fault data at least includes parameter types and corresponding fault times;

[0082] The plurality of operation parameter data in the device operation data is sorted according to the fault times corresponding to the parameter types;

[0083] The standard data range corresponding to the parameter type to which the operation parameter data belongs is searched according to the sequence number value corresponding to the operation parameter data.

[0084] In an embodiment, the device fault instruction generating module 305 is further configured to determine the maintenance time of the last efficient filter, which is recorded as a historical maintenance time;

[0085] The current time is obtained;

[0086] The time difference between the historical maintenance time and the current time is calculated;

[0087] It is judged whether the time difference reaches a preset maintenance period;

[0088] If the time difference reaches the maintenance period, the maintenance instruction is generated.

[0089] In an embodiment, the device fault reason searching module 304 is further configured to search for the fault times in the device fault data according to the parameter types corresponding to the fault reasons;

[0090] The fault number is modified, and is recorded as a maximum fault number;

[0091] The maximum fault number is compared with a preset fault number threshold value;

[0092] If the maximum fault number exceeds the fault number threshold value, a first replacement instruction is generated.

[0093] In an embodiment, the device fault reason searching module 304 is further configured to search for a fault time closest to a current time node according to a preset quantity value, and the fault time is recorded as a historical fault time set;

[0094] The maximum historical fault time and the minimum historical fault time in the historical fault time set are calculated;

[0095] If a time difference between the maximum historical fault time and the minimum historical fault time is less than a preset interval threshold value, a second replacement instruction is generated.

[0096] In an embodiment, the device running data obtaining module 301 is further configured to a parameter type, including a rated air volume of the high-efficiency filter and a resistance parameter.

[0097] The embodiment of the application further discloses a computer device.

[0098] Specifically, the computer device includes a memory and a processor, and the memory stores a computer program capable of being loaded and executed by the processor and performing the high-efficiency filter fault detection method.

[0099] The embodiment of the application further discloses a computer readable storage medium.

[0100] Specifically, the computer readable storage medium stores a computer program capable of being loaded and executed by the processor and performing the high-efficiency filter fault detection method, and the computer readable storage medium includes, for example, a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage program code mediums.

[0101] The embodiment is only an explanation of the application, and is not a limitation of the application. Those skilled in the art can make modifications to the embodiment without creative contribution, as long as the modifications are within the scope of the claims of the application.

Claims

1. A method of high efficiency filter failure detection, the method comprising: The method comprises: obtaining equipment operation data, the equipment operation data at least comprising a plurality of operation parameter data and corresponding parameter types; the parameter types comprising a rated air volume of a high-efficiency filter and a resistance parameter; finding corresponding standard data ranges according to the parameter types, specifically comprising: obtaining equipment failure data, the equipment failure data at least comprising parameter types and corresponding failure times; and sorting a plurality of operation parameter data in the equipment operation data according to the failure times corresponding to the parameter types; sequentially finding standard data ranges corresponding to the parameter types to which the operation parameter data belongs according to serial numbers of the operation parameter data; comparing the operation parameter data with end point values of the standard data ranges; if the operation parameter data is outside the standard data ranges, finding corresponding failure causes in a preset failure database according to the parameter types; generating a maintenance instruction according to the failure causes; wherein, after the generating of the maintenance instruction according to the failure causes, the method further comprises: finding failure times in the equipment failure data according to the parameter types corresponding to the failure causes; modifying the failure times as maximum failure times; comparing the maximum failure times with a preset failure time threshold; if the maximum failure times exceed the failure time threshold, generating a first replacement instruction; the equipment failure data further comprises failure times, and after finding the failure times in the equipment failure data according to the parameter types corresponding to the failure causes, the method further comprises: finding, according to a preset number of values, a failure time closest to a current time node as a historical failure time set; calculating a maximum historical failure time and a minimum historical failure time in the historical failure time set; if a time difference between the maximum historical failure time and the minimum historical failure time is less than a preset interval threshold, generating a second replacement instruction.

2. The method of claim 1, wherein, The obtaining of the equipment operation data specifically comprises: collecting initial equipment operation data at fixed intervals according to a preset clock signal to form an equipment operation data set, the initial equipment operation data at least comprising a plurality of initial operation parameter data and corresponding parameter types; screening the initial operation parameter data under the same parameter types to obtain maximum operation parameter data and minimum operation parameter data; generating the equipment operation data according to the maximum operation parameter data, the minimum operation parameter data and the corresponding parameter types.

3. The method of claim 1, wherein, The method further comprises: determining a maintenance time of a last high-efficiency filter as a historical maintenance time; obtaining a current time; calculating a time difference between the historical maintenance time and the current time; determining whether the time difference reaches a preset maintenance period; if the time difference reaches the maintenance period, generating a maintenance instruction.

4. A high efficiency filter failure detection apparatus for use in a high efficiency filter failure detection method as claimed in any one of claims 1 to 3, characterized by The device comprises: an equipment operation data obtaining module (301) for obtaining equipment operation data, the equipment operation data at least comprising a plurality of operation parameter data and corresponding parameter types; a standard data range obtaining module (302) for finding corresponding standard data ranges according to the parameter types; a device operation data comparison module (303) configured to compare the operation parameter data with the endpoint values of the standard data range; a device fault reason searching module (304) configured to search for a corresponding fault reason in a preset fault database according to the parameter type if the operation parameter data is outside the standard data range; a device fault instruction generation module (305) configured to generate a maintenance instruction according to the fault reason.

5. A computer device, comprising: A computer program product comprising a memory and a processor, the memory having stored thereon a computer program loadable and executable by the processor to perform any of the methods of claims 1-3.

6. A computer-readable storage medium, characterized in that, A computer program loadable and executable by a processor to perform any of the methods of claims 1-3.

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