Fault diagnosis method and system for water station equipment

Abstract

The invention relates to the technical field of equipment fault diagnosis, and particularly discloses a fault diagnosis method and system for water station equipment, and the method comprises an information collection module which collects the operation data information of all equipment of a water station in real time; the data processing module is used for receiving the operation data information of each device and preprocessing the operation data information; the fault diagnosis module is used for comparing the operation data information of each device with the normal operation parameters to judge whether a fault exists or not, and predicting the fault occurrence rate of the corresponding device within a period of time according to the previous data; and the display control module is used for automatically displaying a fault judgment result of the fault diagnosis module when a fault occurs and giving a possible reason. According to the invention, the real-time operation parameters of each device of the water station are collected, the abnormal state of the device is found in time, the fault is quickly responded, the influence of the fault on the operation of the water station is reduced, possible reasons and the fault occurrence rate are given, workers are reminded to overhaul and maintain in time, the overhaul efficiency is improved, and the fault probability is reduced.

Description

Technical Field

[0001] The present invention relates to the field of health detection, and in particular to a fault diagnosis method and system for water station equipment. Background Art

[0002] Community direct drinking water stations provide residents with a convenient source of high-quality drinking water. Their equipment covers several key parts such as filtration systems, disinfection systems, and water pump systems.

[0003] Currently, water station equipment fault diagnosis relies primarily on regular manual inspections and simple sensor alarms. This leads to problems such as delayed fault detection and difficulty accurately determining the root cause. Manual inspections are not only labor-intensive and time-consuming, but also make it difficult to monitor equipment operating status in real time. Simple sensor alarms cannot accurately locate faulty components, nor can they deeply analyze the specific cause or predict potential failures, impacting the normal operation of water stations and the safety of residents' water supply.

[0004] Therefore, it is necessary to design a fault diagnosis system for water station equipment to solve the problem that the fault diagnosis of existing water station equipment is not timely and difficult to accurately determine the root cause of the fault. Summary of the Invention

[0005] In view of this, the present invention proposes a fault diagnosis system for water station equipment, which aims to solve the problem that fault diagnosis of existing water station equipment is not timely and it is difficult to accurately determine the root cause of the fault.

[0006] In one aspect, the present invention provides a fault diagnosis system for water station equipment, comprising:

[0007] Information collection module, used to collect real-time flow information, pressure information, current information, voltage information, water quality information and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment;

[0008] A data processing module, configured to receive the data information collected by the information collection module and pre-process the data information;

[0009] A fault diagnosis module, having a built-in deep learning model and threshold values ​​for operating parameters of each device, is used to determine whether the filtration device, reverse osmosis device, water pump device, and disinfection device have failed based on the preprocessed data information and the threshold values ​​for operating parameters of each device, and to predict the probability of failure of each device using the deep learning model based on the preprocessed data information;

[0010] The display control module is used to control the system operation and display the fault judgment results of each device and the subsequent fault probability prediction results.

[0011] Furthermore, the data processing module is configured to: perform cleaning, filtering and normalization preprocessing on the collected information data; and classify and store the data information of each device collected by the information collection module.

[0012] Furthermore, the fault diagnosis module has a built-in coarse filtration equipment fault diagnosis unit, a fine filtration equipment fault diagnosis unit, a reverse osmosis equipment fault diagnosis unit, a water pump equipment fault diagnosis unit, an ultraviolet disinfection equipment fault diagnosis unit, and a chlorination disinfection equipment fault diagnosis unit, and each of the fault diagnosis units has a built-in fault diagnosis rule.

[0013] Furthermore, the coarse filtration equipment fault diagnosis unit is preset with an inlet and outlet water pressure difference threshold value A, an outlet water flow threshold value B, and an outlet water turbidity threshold value C. The coarse filtration equipment fault diagnosis unit is configured as follows:

[0014] Receive in real time the inlet and outlet water pressure difference A1, outlet water flow B1 and outlet water turbidity C1 of the coarse filtration equipment collected by the information collection module;

[0015] When A1≥A and the duration is greater than 60 minutes, it is determined that the coarse filtration equipment has a blockage fault;

[0016] When B1≤B and the duration is greater than 30 minutes, it is determined that the flow of the coarse filtration equipment is abnormal;

[0017] When C1≥C and the duration is greater than 120 minutes, it is determined that the purification element of the coarse filtration equipment is faulty.

[0018] Furthermore, the fault diagnosis unit for the precision filtration equipment is preset with an inlet and outlet pressure difference threshold value D and an outlet chlorine content threshold value E. The fault diagnosis unit for the precision filtration equipment is configured as follows:

[0019] Receive in real time the inlet and outlet water pressure difference D1 and outlet water chlorine content E1 of the precision filtration equipment collected by the information collection module;

[0020] When D1≥D and the duration is greater than 45 minutes, it is determined that the precision filtration equipment is blocked;

[0021] When E1≥E and the duration is greater than 60 minutes, it is determined that the adsorption performance of the precision filtration equipment has declined.

[0022] Furthermore, the reverse osmosis equipment fault diagnosis unit is preset with an inlet and concentrate pressure difference threshold F, a production water flow threshold G, and a production water conductivity threshold S. The reverse osmosis equipment fault diagnosis unit is configured as follows:

[0023] Receive in real time the inlet concentrated water pressure difference F1, the produced water flow rate G1 and the produced water conductivity S1 of the reverse osmosis equipment collected by the information collection module;

[0024] When F1≥F and the duration is greater than 60 minutes, it is determined that the reverse osmosis membrane in the reverse osmosis equipment is faulty;

[0025] When G1≤G and the duration is greater than 30 minutes, it is determined that the flow of the reverse osmosis equipment is abnormal;

[0026] When S≥S1 and the duration is greater than 60 minutes, it is determined that the performance of the reverse osmosis membrane has deteriorated.

[0027] Furthermore, the water pump equipment fault diagnosis unit is preset with a current threshold I, a voltage fluctuation threshold V, an inlet and outlet pressure threshold H, and a flow threshold K. The water pump equipment fault diagnosis unit is configured as follows:

[0028] Receive in real time the current I1, voltage fluctuation V1, inlet and outlet pressure H1 and flow K1 of the water pump equipment collected by the information collection module;

[0029] When I1≥I or V1≥V, it is determined that the water pump electrical system is faulty;

[0030] When H1≤H and the duration is greater than 20 minutes, it is determined that the water pump pressure is abnormal;

[0031] When K1≤K and the duration is greater than 30 minutes, it is determined that the water pump flow is abnormal.

[0032] Furthermore, the ultraviolet radiation intensity threshold W and the total bacterial count threshold U in the water after disinfection are preset in the ultraviolet disinfection equipment fault diagnosis unit. The ultraviolet disinfection equipment fault diagnosis unit is configured as follows:

[0033] Receive in real time the ultraviolet radiation intensity W1 in the ultraviolet disinfection equipment and the total number of bacteria U1 in the water after disinfection collected by the information collection module;

[0034] When W1≤W and the duration is greater than 60 minutes or U1≥U, it is determined that the disinfection intensity of the ultraviolet disinfection equipment is insufficient;

[0035] The chlorination disinfection equipment fault diagnosis unit is preset with a first preset residual chlorine content M max and the second preset residual chlorine content M min , and M max >M min , the chlorination equipment fault diagnosis unit is configured to:

[0036] Receiving in real time the residual chlorine content M1 in the chlorine disinfection equipment collected by the information collection module;

[0037] When M1≥M max Or M1≤M min, and the duration is greater than 60 minutes, it is determined that the chlorination disinfection equipment has an abnormal chlorine addition failure.

[0038] Furthermore, the display control module is configured to: display the fault determined by the fault diagnosis module, give the specific cause of the fault and issue an audible and visual alarm.

[0039] On the other hand, the present invention also provides a fault diagnosis method for water station equipment, comprising the following steps:

[0040] Real-time collection of flow information, water quality information, pressure information, current information, voltage information, and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment;

[0041] pre-processing the flow information, water quality information, pressure information, current information, voltage information and ultraviolet intensity information;

[0042] Comparing the pre-processed quantity information, water quality information, pressure information, current information, voltage information, and ultraviolet intensity information with normal parameters to determine whether the corresponding device is faulty;

[0043] When it is determined that the equipment is in failure, an alarm is issued, the corresponding equipment failure is displayed, and the specific cause of the failure is given.

[0044] Compared with the existing technology, the beneficial effects of the present invention are: by collecting the real-time operating parameters of each device in the water station, abnormal equipment conditions can be discovered in time, and the faulty equipment can be quickly responded to and accurately located, thereby reducing the impact of the fault on the operation of the water station. At the same time, possible causes and predicted fault occurrence rates are given to promptly remind staff to inspect and maintain, thereby improving inspection and maintenance efficiency and reducing the probability of failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0046] Figure 1 This is a functional block diagram of a fault diagnosis system for water station equipment provided by an embodiment of the present invention.

[0047] Figure 2 This is a flow chart of a fault diagnosis method for water station equipment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0049] Reference Figure 1 As shown, in some embodiments of the present application, a fault diagnosis system for water station equipment includes:

[0050] Information collection module, used to collect real-time flow information, pressure information, current information, voltage information, water quality information and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment;

[0051] A data processing module, configured to receive the data information collected by the information collection module and pre-process the data information;

[0052] A fault diagnosis module, having a built-in deep learning model and threshold values ​​for operating parameters of each device, is used to determine whether the filtration device, reverse osmosis device, water pump device, and disinfection device have failed based on the preprocessed data information and the threshold values ​​for operating parameters of each device, and to predict the probability of failure of each device using the deep learning model based on the preprocessed data information;

[0053] The display control module is used to control the system operation and display the fault judgment results of each device and the subsequent fault probability prediction results.

[0054] Specifically, sensors are installed on various devices to collect data. Each sensor node is equipped with a ZigBee wireless module, which sends the collected data in the form of data packets to the ZigBee coordinator. The coordinator aggregates and initially processes the received data before transmitting it to the data processing module via Ethernet or GPRS.

[0055] Specifically, the data processing module can use a distributed file system to store large amounts of raw sensor data and historical data. Distributed file systems have high reliability, high scalability, and fault tolerance. The fault diagnosis module can use a relational database to store structured data such as basic device information, fault diagnosis rules, and processing results.

[0056] Specifically, the deep learning model is a long short-term memory (LSTM) model. LSTM is a special type of recurrent neural network capable of processing long-term dependencies in sequential data. After training it with historical data and taking a period of equipment operating data as input, the LSTM model can predict equipment operating parameters and the probability of failure in the future.

[0057] like Figure 1 As shown, in some embodiments of the present application, the data processing module is configured to: clean, filter and normalize the collected information data; and classify and store the data information of each device collected by the information collection module.

[0058] Specifically, the cleaning process involves removing noise and outliers from the data using statistical analysis methods. For continuous data, the mean and standard deviation are calculated. Data points that deviate from the mean by more than three standard deviations are considered outliers and are removed or corrected. For discrete data, a range is set to remove out-of-range data.

[0059] Specifically, the filtering process is to use a moving average filtering algorithm to smooth the sensor data to reduce data fluctuations. For each data point, the average value of a certain number of data points before and after it is calculated as the filtered value of the point.

[0060] Specifically, the normalization process is to normalize sensor data of different ranges to the interval [0, 1] using the minimum-maximum normalization method, and the formula used is:

[0061]

[0062] Among them, X is the original data, X max is the maximum value in the original data, X min is the minimum value in the original data.

[0063] like Figure 1 As shown, in some embodiments of the present application, the fault diagnosis module has built-in coarse filtration equipment fault diagnosis unit, fine filtration equipment fault diagnosis unit, reverse osmosis equipment fault diagnosis unit, water pump equipment fault diagnosis unit, ultraviolet disinfection equipment fault diagnosis unit, and chlorination disinfection equipment fault diagnosis unit, and each of the fault diagnosis units has built-in fault diagnosis rules.

[0064] It is understandable that a fault diagnosis unit is separately provided for each device in the water station, and each fault diagnosis unit stores a corresponding fault diagnosis rule, which greatly improves the accuracy of fault diagnosis.

[0065] like Figure 1As shown, in some embodiments of the present application, the coarse filtration equipment fault diagnosis unit is preset with an inlet and outlet water pressure difference threshold value A, an outlet water flow threshold value B, and an outlet water turbidity threshold value C. The coarse filtration equipment fault diagnosis unit is configured as follows:

[0066] Receive in real time the inlet and outlet water pressure difference A1, outlet water flow B1 and outlet water turbidity C1 of the coarse filtration equipment collected by the information collection module;

[0067] When A1≥A and the duration is greater than 60 minutes, it is determined that the coarse filtration equipment has a blockage fault;

[0068] When B1≤B and the duration is greater than 30 minutes, it is determined that the flow of the coarse filtration equipment is abnormal;

[0069] When C1≥C and the duration is greater than 120 minutes, it is determined that the purification element of the coarse filtration equipment is faulty.

[0070] The fault diagnosis unit for the precision filtration equipment is preset with an inlet and outlet pressure difference threshold value D and an outlet chlorine content threshold value E. The fault diagnosis unit for the precision filtration equipment is configured as follows:

[0071] Receive in real time the inlet and outlet water pressure difference D1 and outlet water chlorine content E1 of the precision filtration equipment collected by the information collection module;

[0072] When D1≥D and the duration is greater than 45 minutes, it is determined that the precision filtration equipment is blocked;

[0073] When E1 ≥ E and lasts for more than 60 minutes, the adsorption performance of the precision filtration equipment is determined to have degraded. Specifically, the filtration equipment in the water station includes coarse filtration of large particles of impurities and sediment in the raw water, and precision filtration equipment for adsorbing residual chlorine, organic matter, and foreign colors and odors in the water to further remove impurities.

[0074] Specifically, high-precision flow sensors (such as electromagnetic flow sensors with a measurement accuracy of up to ±0.5%) and pressure sensors (such as diffused silicon pressure sensors with a measurement range of 0-1MPa and an accuracy of ±0.2%) are installed at the water inlet and outlet of the coarse filtration equipment to monitor water flow and pressure changes in real time. In precision filtration equipment, in addition to flow and pressure sensors, water quality sensors (such as residual chlorine sensors with a measurement range of 0-5mg / L and an accuracy of ±0.05mg / L) are also installed to monitor changes in the residual chlorine content in the filtered water to determine the adsorption effect of the activated carbon.

[0075] like Figure 1 As shown, in some embodiments of the present application, the reverse osmosis equipment fault diagnosis unit is preset with an inlet concentrate pressure difference threshold F, a production water flow threshold G, and a production water conductivity threshold S. The reverse osmosis equipment fault diagnosis unit is configured as follows:

[0076] Receive in real time the inlet concentrated water pressure difference F1, the produced water flow rate G1 and the produced water conductivity S1 of the reverse osmosis equipment collected by the information collection module;

[0077] When F1≥F and the duration is greater than 60 minutes, it is determined that the reverse osmosis membrane in the reverse osmosis equipment is faulty;

[0078] When G1≤G and the duration is greater than 30 minutes, it is determined that the flow of the reverse osmosis equipment is abnormal;

[0079] When S≥S1 and the duration is greater than 60 minutes, it is determined that the performance of the reverse osmosis membrane has deteriorated.

[0080] Specifically, pressure sensors, flow sensors, and water quality sensors (such as conductivity sensors with a measurement range of 0-2000μS / cm and an accuracy of ±1%) are installed at the inlet, concentrate, and product water ends of the reverse osmosis membrane module. By monitoring the pressure difference, flow ratio, and product water conductivity at each end, the operating status and performance of the reverse osmosis membrane can be determined.

[0081] like Figure 1 As shown, in some embodiments of the present application, the water pump equipment fault diagnosis unit is preset with a current threshold I, a voltage fluctuation threshold V, an inlet and outlet pressure threshold H, and a flow threshold K. The water pump equipment fault diagnosis unit is configured as follows:

[0082] Receive in real time the current I1, voltage fluctuation V1, inlet and outlet pressure H1 and flow K1 of the water pump equipment collected by the information collection module;

[0083] When I1≥I or V1≥V, it is determined that the water pump electrical system is faulty;

[0084] When H1≤H and the duration is greater than 20 minutes, it is determined that the water pump pressure is abnormal;

[0085] When K1≤K and the duration is greater than 30 minutes, it is determined that the water pump flow is abnormal.

[0086] Specifically, current sensors (such as Hall effect current sensors with a measurement range of 0-50A and an accuracy of ±0.5%) and voltage sensors (such as resistor divider voltage sensors with a measurement range of 0-400V and an accuracy of ±0.5%) are installed on the water pump motor to monitor the motor's electrical parameters. Simultaneously, pressure sensors and flow sensors are installed at the pump's inlet and outlet to monitor the pump's operating pressure and flow rate, thereby determining the pump's operating efficiency and the presence of cavitation issues.

[0087] like Figure 1As shown, in some embodiments of the present application, the ultraviolet radiation intensity threshold W and the total bacterial count threshold U in the water after disinfection are preset in the ultraviolet disinfection equipment fault diagnosis unit, and the ultraviolet disinfection equipment fault diagnosis unit is configured as follows:

[0088] Receive in real time the ultraviolet radiation intensity W1 in the ultraviolet disinfection equipment and the total number of bacteria U1 in the water after disinfection collected by the information collection module;

[0089] When W1≤W and the duration is greater than 60 minutes or U1≥U, it is determined that the disinfection intensity of the ultraviolet disinfection equipment is insufficient;

[0090] The chlorination disinfection equipment fault diagnosis unit is preset with a first preset residual chlorine content M max and the second preset residual chlorine content M min , and M max >M min， The chlorination equipment fault diagnosis unit is configured to:

[0091] Receiving in real time the residual chlorine content M1 in the chlorine disinfection equipment collected by the information collection module;

[0092] When M1≥M max Or M1≤M min , and the duration is greater than 60 minutes, it is determined that the chlorination disinfection equipment has an abnormal chlorine addition failure.

[0093] Specifically, for ultraviolet disinfection equipment, install an ultraviolet intensity sensor (measuring range 0-1000μW / cm 2 , accuracy ±5%), real-time monitoring of ultraviolet radiation intensity. For chlorination disinfection equipment, install a residual chlorine sensor to monitor the amount of chlorine added.

[0094] like Figure 1 As shown, the display control module is configured to: display the fault determined by the fault diagnosis module, give the specific cause of the fault and issue an audible and visual alarm.

[0095] Specifically, when there is a blockage fault in the coarse filtration equipment, the display control module gives the specific fault cause that the filter material in the coarse filtration equipment may be blocked by impurities; when there is a flow abnormality in the coarse filtration equipment, the display control module gives the specific fault cause that the filter material in the coarse filtration equipment may be compacted or foreign matter may exist in the filter layer; when there is a coarse filtration equipment purification element fault in the coarse filtration equipment, the display control module gives the specific fault cause that the filter material in the coarse filtration equipment fails or the backwash is not thorough; when there is a blockage fault in the precision filtration equipment, the display control module gives the specific fault cause that the activated carbon particles in the precision filtration equipment are broken or blocked by impurities; when there is a decrease in adsorption performance of the precision filtration equipment, the display control module gives the specific fault cause that the activated carbon adsorption in the precision filtration equipment is saturated or fails.

[0096] Specifically, when the reverse osmosis equipment has a reverse osmosis membrane failure, the display control module gives the specific fault cause of the reverse osmosis membrane being blocked, scaled or damaged; when the reverse osmosis equipment has a flow abnormality, the display control module gives the specific fault cause of the membrane element being blocked, damaged or insufficient system pressure; when the reverse osmosis equipment has a reverse osmosis membrane performance degradation failure, the display control module gives the specific fault cause of the reverse osmosis membrane being damaged, scaled or chemically contaminated.

[0097] Specifically, when there is an electrical system fault in the water pump equipment, the display control module gives the specific fault causes of water pump overload, motor failure, and power supply line problem; when there is an abnormal water pump pressure fault in the water pump equipment, the display control module gives the specific fault causes of water pump impeller wear, blockage, or water pump cavitation; when there is an abnormal water pump flow fault in the water pump equipment, the display control module gives the specific fault causes of insufficient water pump head, pipeline blockage or leakage.

[0098] Specifically, when the ultraviolet disinfection equipment has a fault of insufficient disinfection intensity of the external disinfection equipment, the display control module gives the specific fault causes of aging of the ultraviolet lamp, dirt adhesion or ballast failure; when the chlorination disinfection equipment has a fault of abnormal chlorine addition amount, the display control module gives the specific fault causes of chlorination pump failure, inaccurate chlorine solution concentration or chlorination control system failure.

[0099] like Figure 2 As shown, on the other hand, the present application also proposes a fault diagnosis method for water station equipment, comprising the following steps:

[0100] Real-time collection of flow information, water quality information, pressure information, current information, voltage information and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment;

[0101] pre-processing the flow information, water quality information, pressure information, current information, voltage information and ultraviolet intensity information;

[0102] Comparing the pre-processed quantity information, water quality information, pressure information, current information, voltage information, and ultraviolet intensity information with normal parameters to determine whether the corresponding device is faulty;

[0103] When it is determined that the equipment is in failure, an alarm is issued, the corresponding equipment failure is displayed, and the possible specific cause of the failure is given.

[0104] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0106] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A fault diagnosis system for water station equipment, characterized in that: include: Information collection module, used to collect real-time flow information, pressure information, current information, voltage information, water quality information and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment; A data processing module, configured to receive the data information collected by the information collection module and pre-process the data information; A fault diagnosis module, having a built-in deep learning model and threshold values ​​for operating parameters of each device, is used to determine whether the filtration device, reverse osmosis device, water pump device, and disinfection device have failed based on the preprocessed data information and the threshold values ​​for operating parameters of each device, and to predict the probability of failure of each device using the deep learning model based on the preprocessed data information; The display control module is used to control the system operation and display the fault judgment results of each device and the subsequent fault probability prediction results.

2. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The data processing module is configured to: perform cleaning, filtering and normalization preprocessing on the collected information data; and classify and store the data information of each device collected by the information collection module.

3. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The fault diagnosis module has built-in fault diagnosis units for coarse filtration equipment, fine filtration equipment, reverse osmosis equipment, water pump equipment, ultraviolet disinfection equipment, and chlorination disinfection equipment, and each fault diagnosis unit has built-in fault diagnosis rules.

4. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The coarse filtration equipment fault diagnosis unit is preset with an inlet and outlet water pressure difference threshold value A, an outlet water flow threshold value B, and an outlet water turbidity threshold value C. The coarse filtration equipment fault diagnosis unit is configured as follows: Receive in real time the inlet and outlet water pressure difference A1, outlet water flow B1 and outlet water turbidity C1 of the coarse filtration equipment collected by the information collection module; When A1≥A and the duration is greater than 60 minutes, it is determined that the coarse filtration equipment has a blockage fault; When B1≤B and the duration is greater than 30 minutes, it is determined that the flow of the coarse filtration equipment is abnormal; When C1≥C and the duration is greater than 120 minutes, it is determined that the purification element of the coarse filtration equipment is faulty.

5. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The fault diagnosis unit for the precision filtration equipment is preset with an inlet and outlet pressure difference threshold value D and an outlet chlorine content threshold value E. The fault diagnosis unit for the precision filtration equipment is configured as follows: Receive in real time the inlet and outlet water pressure difference D1 and outlet water chlorine content E1 of the precision filtration equipment collected by the information collection module; When D1≥D and the duration is greater than 45 minutes, it is determined that the precision filtration equipment is blocked; When E1≥E and the duration is greater than 60 minutes, it is determined that the adsorption performance of the precision filtration equipment has declined.

6. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The reverse osmosis equipment fault diagnosis unit is preset with an inlet and concentrate pressure difference threshold F, a production water flow threshold G, and a production water conductivity threshold S. The reverse osmosis equipment fault diagnosis unit is configured as follows: Receive in real time the inlet concentrated water pressure difference F1, the produced water flow rate G1 and the produced water conductivity S1 of the reverse osmosis equipment collected by the information collection module; When F1≥F and the duration is greater than 60 minutes, it is determined that the reverse osmosis membrane in the reverse osmosis equipment is faulty; When G1≤G and the duration is greater than 30 minutes, it is determined that the flow of the reverse osmosis equipment is abnormal; When S≥S1 and the duration is greater than 60 minutes, it is determined that the performance of the reverse osmosis membrane has deteriorated.

7. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The water pump equipment fault diagnosis unit is preset with a current threshold I, a voltage fluctuation threshold V, an inlet and outlet pressure threshold H, and a flow threshold K. The water pump equipment fault diagnosis unit is configured as follows: Receive in real time the current I1, voltage fluctuation V1, inlet and outlet pressure H1 and flow K1 of the water pump equipment collected by the information collection module; When I1≥I or V1≥V, it is determined that the water pump electrical system is faulty; When H1≤H and the duration is greater than 20 minutes, it is determined that the water pump pressure is abnormal; When K1≤K and the duration is greater than 30 minutes, it is determined that the water pump flow is abnormal.

8. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The ultraviolet radiation intensity threshold W and the total bacterial count threshold U in the water after disinfection are preset in the ultraviolet disinfection equipment fault diagnosis unit. The ultraviolet disinfection equipment fault diagnosis unit is configured as follows: Receive in real time the ultraviolet radiation intensity W1 in the ultraviolet disinfection equipment and the total number of bacteria U1 in the water after disinfection collected by the information collection module; When W1≤W and the duration is greater than 60 minutes or U1≥U, it is determined that the disinfection intensity of the ultraviolet disinfection equipment is insufficient; The chlorination disinfection equipment fault diagnosis unit is preset with a first preset residual chlorine content M max and the second preset residual chlorine content M min , and M max >M min , the chlorination equipment fault diagnosis unit is configured to: Receiving in real time the residual chlorine content M1 in the chlorine disinfection equipment collected by the information collection module; When M1≥M max Or M1≤M min , and the duration is greater than 60 minutes, it is determined that the chlorination disinfection equipment has an abnormal chlorine addition failure.

9. The fault diagnosis system for water station equipment according to claim 1, characterized in that: The display control module is configured to display the fault determined by the fault diagnosis module, give the specific cause of the fault and issue an audible and visual alarm.

10. A fault diagnosis method for water station equipment, characterized in that: The following steps are involved: Real-time collection of flow information, water quality information, pressure information, current information, voltage information and ultraviolet intensity information of water station filtration equipment, reverse osmosis equipment, water pump equipment and disinfection equipment; pre-processing the flow information, water quality information, pressure information, current information, voltage information and ultraviolet intensity information; Comparing the pre-processed quantity information, water quality information, pressure information, current information, voltage information, and ultraviolet intensity information with normal parameters to determine whether the corresponding device is faulty; When it is determined that the equipment is in failure, an alarm is issued, the corresponding equipment failure is displayed, and the specific cause of the failure is given.

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