Secondary water supply system fault early warning method and system based on data analysis

Abstract

The invention discloses a secondary water supply system fault early warning method and system based on data analysis, relates to the technical field of fault early warning, and aims to solve the problems of difficult troubleshooting and low repair efficiency caused by single alarm response and multiple abnormal problems of a water supply system. The method comprises the following steps: analyzing abnormal conditions in a water supply program, screening out abnormal parts, classifying and dividing equipment in a water supply system, determining repair time and repair cost required when the divided equipment is abnormal, dividing the equipment by integrating the repair time and the repair cost, and performing repair difficulty assessment on each divided equipment by using a superior sequence diagram method. Carrying out equipment classification on the screened abnormal parts to determine an abnormal equipment combination, grading the abnormal conditions by using a hierarchical classification method according to the repair difficulty of the equipment combination, making different alarm responses by using the grades of the abnormal conditions, and recording response behaviors; and storing the abnormal equipment combination information and the abnormal condition level of the corresponding equipment combination.

Description

Technical Field

[0001] The present invention relates to the technical field of fault warning, and more specifically, to a fault warning method and system for a secondary water supply system based on data analysis. Background Art

[0002] Fault warning technology is to timely identify potential faults and issue alarms through monitoring, analysis and prediction during the operation of equipment and systems, thereby avoiding or reducing the impact of faults on system performance and safety. Fault warning technology is applied in secondary water supply systems to promptly alarm when abnormalities occur in the water supply system, assisting managers to promptly detect abnormalities and repair faults.

[0003] The prior art has the following deficiencies:

[0004] Most abnormal problems in water supply systems will trigger chain reactions. In the past, the alarm thresholds set in water supply systems were single. When abnormal problems occurred in the water supply system, only the abnormal situation was reported. When the abnormal problems led to other water supply problems or multiple abnormal problems occurred in the water supply system at the same time, the alarm system gave too little information, resulting in difficulties in troubleshooting and low repair efficiency. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a secondary water supply system fault warning method and system based on data analysis, which analyzes the repair difficulty of each device in the water supply system by dividing it into different categories, and then matches the detected abnormal equipment in the water supply system with the classified categories to determine the abnormal situation of the water supply system, and then provides different alarm responses to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The secondary water supply system fault early warning method based on data analysis includes the following steps:

[0008] Step S1: Detect and obtain the secondary water supply operation status, and compare the preset standard threshold to analyze whether the secondary water supply is abnormal;

[0009] Step S2: Filter out abnormal parts according to abnormal conditions, classify the equipment in the water supply system into categories, compare the repair history data, calculate the repair time and repair cost of each category of equipment, and calculate the impact coefficient of each category and the repair difficulty assessment index of each equipment based on the repair time and repair cost;

[0010] Step S3: using the influence coefficient of each category to determine the influence weight of each category using the priority diagram method, combining the repair difficulty index of each device and the influence weight of its category to calculate the device score, matching each abnormal part with each category of equipment and determining the abnormal equipment combination;

[0011] Step S4: The abnormal situation is graded according to the device combination and the device score. The system makes different alarm responses according to the abnormal situation level, records the response behavior, and stores the abnormal device combination information and the abnormal situation level of the corresponding device combination.

[0012] In a preferred embodiment, in step S1, the secondary water supply operation status includes two aspects: on the one hand, detecting whether the water quality meets the standard during the secondary water supply; on the other hand, detecting the water supply status during the secondary water supply. The standard threshold is the prescribed threshold of the corresponding water quality index and the set standard water pressure threshold.

[0013] In a preferred embodiment, in step S1, it is detected whether the water quality meets the standard during the secondary water supply by detecting whether the corresponding water quality index in the water meets the specified threshold value during the water supply transmission, and the pollutants in the water are detected and compared with the specified threshold value of the corresponding water quality index. If any one of the conditions is not met or the condition does not meet the specified threshold value for more than a preset number of times within the monitoring period, it is judged that the water quality is abnormal;

[0014] When detecting the secondary water supply and transportation situation, the water pressure at the receiving end is detected. When the water pressure at the receiving end is within the set standard water pressure threshold range, the secondary water supply and transportation situation is judged to be normal. When the water pressure at the receiving end exceeds the set standard water pressure threshold for multiple times, the secondary water supply and transportation situation is judged to be abnormal. The number of water quality or water pressure detections and the number of times the corresponding thresholds are exceeded can be set according to the early warning needs.

[0015] In a preferred embodiment, in step S2, the water supply system equipment is divided into three parts, namely, the host computer, the data channel and the slave computer. After the system determines that the water quality is abnormal, the host computer, the data channel and the slave computer in the abnormal part are detected in turn to determine the abnormal equipment and its type.

[0016] In a preferred embodiment, in step S2, the repair time and repair cost of each category of equipment are counted against the repair history data, the repair time and repair cost of each device are normalized and summed to obtain the equipment's repair difficulty assessment index, and based on the equipment category, the median of the repair difficulty assessment index of the same category of equipment is taken as the category influence coefficient.

[0017] In a preferred embodiment, in step S3, the specific steps of using the priority diagram method to determine the impact weight of each category are as follows:

[0018] Construct a priority chart, arrange each category from large to small according to the category influence coefficient, compare the category influence coefficients pairwise, mark the category with a large category influence coefficient as 1, mark the categories with the same category influence coefficient as 0.5, and mark the category with a small category influence coefficient as 0. Count the sum of the number of marks for different categories and divide it by the sum of the number of marks for all categories as the influence weight of the corresponding category.

[0019] In a preferred embodiment, in step S3, the repair time and repair cost of each device are obtained through the repair history data and the repair difficulty assessment index of each device is calculated. The repair difficulty assessment index of each device is multiplied by the impact weight of the category to which the corresponding device belongs, and the calculation result is used as the device score.

[0020] In a preferred embodiment, in step S4, the abnormal situation is classified using a hierarchical classification method according to the device combination and the device score, and the specific steps are as follows:

[0021] Set the assessment level: set three levels, namely, level 1 abnormality, level 2 abnormality and level 3 abnormality. Level 1 abnormality represents severe abnormality, level 2 abnormality represents moderate abnormality, and level 3 abnormality represents mild abnormality;

[0022] Formulate assessment rules:

[0023] Rule 1: When there are two or more abnormal device categories in the device combination, the abnormal situation is determined as a level 1 abnormality;

[0024] Rule 2: When there is only one abnormal device category in the device combination, set a device score threshold. If the device score of the abnormal device in the device combination exceeds the device score threshold, the abnormal situation is determined as a level 2 abnormality; otherwise, the abnormal situation is determined as a level 3 abnormality.

[0025] The device score threshold is the average of all device scores.

[0026] A secondary water supply system fault early warning system based on data analysis, which is used to implement the above-mentioned secondary water supply system fault early warning method based on data analysis, includes an abnormality confirmation module, an equipment division module, a combination determination module and an alarm response module;

[0027] The abnormal confirmation module is used to detect the water supply operation status, determine whether the water supply is abnormal and screen out the abnormal parts;

[0028] The equipment classification module is used to classify all equipment in the water supply system, classify different equipment and determine the impact caused by damage to different equipment;

[0029] The combination determination module is used to classify the screened abnormal parts and record the type combination of the abnormal parts when the water supply is abnormal;

[0030] The alarm response module is used to receive the type combination of abnormal parts and make corresponding alarm responses according to the received type combination.

[0031] Technical effects and advantages of the secondary water supply system fault early warning method and system based on data analysis of the present invention:

[0032] The present invention first detects the water supply operation status, analyzes the abnormal situation in the water supply program and screens out the abnormal parts, classifies and divides the equipment in the water supply system, determines the repair time and repair cost required when the divided equipment is abnormal, divides the equipment according to the comprehensive repair time and repair cost, and evaluates the repair difficulty of each divided equipment, uses the repair time and repair cost to digitize the equipment repair difficulty for subsequent analysis of the abnormal situation level to provide data, classifies the screened abnormal parts into equipment to determine the abnormal equipment combination, grades the abnormal situation according to the repair difficulty of the equipment combination, and finally uses the abnormal situation level to make different alarm responses, and records the response behavior, and stores the abnormal equipment combination information and the abnormal situation level of the corresponding equipment combination for subsequent water supply system abnormalities as auxiliary decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of a secondary water supply system fault early warning method based on data analysis of the present invention,

[0034] Figure 2 This is a flow chart of the secondary water supply system fault warning system based on data analysis of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] The present invention first detects the water supply operation status, analyzes the abnormal conditions in the water supply program and screens out the abnormal parts, classifies and divides the equipment in the water supply system, determines the repair time and repair cost required when the divided equipment is abnormal, divides the equipment based on the comprehensive repair time and repair cost and evaluates the repair difficulty of each divided equipment, classifies the screened abnormal parts into equipment to determine the abnormal equipment combination, grades the abnormal conditions according to the repair difficulty of the equipment combination, and finally makes different alarm responses using the abnormal condition level, records the response behavior, and stores the abnormal equipment combination information and the abnormal condition level of the corresponding equipment combination.

[0037] Example 1, a secondary water supply system fault early warning method based on data analysis, such as Figure 1 As shown, the following steps are included:

[0038] Step S1: Detect the water supply operation to obtain the water quality and transportation status of the secondary water supply, and compare the preset standard threshold to analyze whether there is any abnormality in the secondary water supply;

[0039] Step S2: Filter out abnormal parts according to abnormal conditions, classify the equipment in the water supply system into categories, compare the repair history data, calculate the repair time and repair cost of each category of equipment, and calculate the impact coefficient of each category and the repair difficulty assessment index of each equipment based on the repair time and repair cost;

[0040] Step S3: using the influence coefficient of each category to determine the influence weight of each category using the priority diagram method, combining the repair difficulty index of each device and the influence weight of its category to calculate the device score, matching each abnormal part with each category of equipment and determining the abnormal equipment combination;

[0041] Step S4: The abnormal situation is graded according to the device combination and the device score. The system makes different alarm responses according to the abnormal situation level, records the response behavior, and stores the abnormal device combination information and the abnormal situation level of the corresponding device combination.

[0042] The specific implementation is as follows:

[0043] In step S1, the secondary water supply operation includes two aspects: on the one hand, detecting whether the water quality meets the standard during the secondary water supply; on the other hand, detecting the water supply situation during the secondary water supply. The standard threshold is the prescribed threshold of the corresponding water quality index and the set standard water pressure threshold.

[0044] To detect whether the water quality meets the standard during the secondary water supply, random sampling can be performed before the water supply is transmitted to detect whether the corresponding water quality indicators in the water meet the specified thresholds. By detecting the pollutants in the water in the sampled samples and comparing their standards and specified thresholds, if any one of the conditions does not meet the specified thresholds or the condition exceeds the preset number of times during the monitoring period, the water quality is judged to be abnormal. Taking the detection of E. coli content and residual chlorine in water as an example, if the E. coli standard is set to not be detected in every 100 ml, then the online water quality instrument is used to select water samples from the water body for detection multiple times. If E. coli is detected, the water quality is judged to be abnormal; if the residual chlorine standard is that the free chlorine in the water is above 0.05 mg / L, the online water quality instrument is used to extract water samples from the water body multiple times (according to the warning requirements) for detection. When the free chlorine in the water is not more than 0.05 mg / L after multiple detections, the water quality is judged to be abnormal.

[0045] When detecting the water supply situation during secondary water supply, the water supply and transportation situation can be preliminarily analyzed by detecting the water pressure at the receiving end. When the water pressure at the receiving end is within the set standard water pressure threshold range, the secondary water supply and transportation situation is judged to be normal. When the water pressure at the receiving end exceeds the set standard water pressure threshold for multiple times (set according to the early warning requirements), the secondary water supply and transportation situation is judged to be abnormal.

[0046] The number of water quality or water pressure tests and the number of times the corresponding thresholds are exceeded can be set according to the warning needs. By testing both water quality and transportation during water supply operation, the stability of secondary water supply and transportation is improved while ensuring the quality of water. This also provides a data basis for setting alarm thresholds for subsequent classified water supply systems.

[0047] It should be noted that the prescribed threshold and standard water pressure threshold can be adjusted according to industry standards, secondary water supply project design calculations, actual water usage in the community, and operation and maintenance experience. When the system determines through detection that the water quality or transportation situation is abnormal, it will be treated as an abnormal situation in the secondary water supply and treated accordingly.

[0048] In step S2, the water supply system equipment is divided into three parts, namely, the host computer, the data channel and the lower computer part. It should be explained that the host computer is a high-level device in the water supply control system, which is responsible for issuing commands to the lower computer to perform various operations. The lower computer is a low-level device in the water supply control system, which is responsible for receiving commands and performing specific operations. The data channel is a channel for data exchange between the host computer and the lower computer. For example, the water supply controller sends a command to detect the water flow rate, and the command to detect the water flow rate is transmitted to the flow meter through the command channel. The flow meter receives the command to detect the water flow rate and transmits the detection result to the result transmission channel for the water supply controller to receive it. Among them, the water supply controller is the host computer, the flow meter is the lower computer, and the command channel and the result transmission channel are the data channel. It should be explained that problems with the host computer and the data channel will cause large-scale paralysis of the water supply system, and it is more difficult to repair. There are many types of lower computers. For the command issued by the host computer, it specifies the lower computer to start working. When there is a problem with the lower computer, it is easier to repair.

[0049] When the system determines that the water quality is abnormal, it will test the upper computer, data channel and lower computer in turn. When the system tests the upper computer, it will check whether the displayed data of the upper computer is consistent with the actual situation, and whether an alarm is issued when the data reaches the corresponding alarm threshold. If the displayed data does not conform to the actual situation or the data reaches the corresponding alarm threshold but no alarm is issued, the upper computer is judged to be abnormal.

[0050] When the system detects the data channel, it compares whether the data at both ends of the upper computer and the lower computer are consistent, that is, it compares the data sent by the upper computer and the data received by the lower computer or the data received by the upper computer and the data sent by the lower computer. If the data at both ends of the upper computer and the lower computer are inconsistent or exceed the deviation range, the data channel is judged to be abnormal.

[0051] When the system detects the lower computer, it checks whether the lower computer makes a corresponding response after receiving the command, and whether the data collected by the lower computer is consistent with the actual situation. If the lower computer does not make a corresponding response after receiving the command or the collected data does not conform to the actual situation, the lower computer is judged to be abnormal.

[0052] When checking whether the data displayed by the upper computer is consistent with the actual situation or detecting the data collected by the lower computer, the data can be tested by pre-calibrated equipment and compared with the test results when the upper computer displayed the data or the lower computer collected the data, and the deviation range can be set. If it is outside the deviation range, it is judged that the upper computer or the lower computer is abnormal.

[0053] The system classifies all the equipment in the water supply system according to the equipment classification, and classifies all the equipment into the upper computer, data channel and lower computer categories in turn. It accesses the repair history database to obtain the repair history data. The repair history data records the repair time and repair cost of each device. The repair cost can be expressed as the amount spent on the repair. The repair time and repair cost of the equipment classified in the same category are merged into the repair time data set and the repair cost data set respectively. The data in the repair time data set and the repair cost data set are normalized to calculate the category impact index.

[0054] When normalizing the data in the repair time dataset and the repair cost dataset, the Z-score normalization formula can be used: nore =x-μ / σ, where x is the data in the repair time dataset or the repair cost dataset, nore is the normalized result of the corresponding data in the repair time dataset or the repair cost dataset, μ is the mean value of the data in the repair time dataset or the repair cost dataset, and σ is the standard deviation of the data in the repair time dataset or the repair cost dataset.

[0055] The specific steps for the system to calculate the category impact index are as follows:

[0056] After normalizing the data in each data set, the repair difficulty assessment index of each device is calculated. The normalized results of the repair time and the normalized results of the repair cost of each device can be summed up to obtain the index. After classifying each device according to the device classification, the median of the repair difficulty assessment index calculated for each category of equipment is selected as the category influence coefficient.

[0057] The category impact coefficient digitizes the repair difficulty of the upper computer, data channel and lower computer. The category impact coefficient can be used to analyze the impact of different categories of equipment damage on the entire water supply system, so as to subsequently set different alarm thresholds in different levels.

[0058] It should be noted that the normalization formula involved in the above steps is not unique and can be replaced or adjusted according to actual conditions. In this example, the data set is divided in advance, and the repair difficulty assessment index of each category of equipment is calculated to obtain the category influence coefficient. In fact, the order of operations can be reversed. For example, the repair difficulty assessment index of each device is calculated first, and then the category of the repair difficulty assessment index is determined according to the equipment division to obtain the category influence coefficient. I will not go into details here.

[0059] In step S3, before matching each abnormal part with each type of equipment, the system analyzes the impact degree of damage to different types of equipment and sets the impact weight. The system uses the priority diagram method to set the impact weight according to the category impact coefficient. The specific steps are shown in Table 1:

[0060] Table 1

[0061] Category A Category B Category C TTL indicator Impact Weight Category A Importance 0.5 1 1 2.5 0.5556 Category B Importance 0 0.5 1 1.5 0.3333 C Category Importance 0 0 0.5 0.5 0.1111

[0062] It should be noted that Category A, Category B and Category C in Table 1 correspond to the three classification categories in this example respectively. The three classification categories are arranged from large to small according to their respective calculated category influence coefficients and then correspond to Category A, Category B and Category C in sequence.

[0063] When an abnormality occurs in the water supply system, the system will detect and screen out the abnormal part and determine the category of the abnormal part. The repair time and repair cost of each device are obtained through the repair history data, and the repair difficulty assessment index of each device is calculated. The repair difficulty assessment index of each device is multiplied by the influence weight of the category of the corresponding device, and the calculation result is used as the equipment score.

[0064] After the system conducts an overall inspection of the water supply system, it records all detected abnormal parts and analyzes the categories of the abnormal parts respectively, so as to determine the abnormal equipment combination. For example, if there are two categories of equipment, upper computer and lower computer, among all the detected abnormal parts, then the abnormal equipment combination is upper computer and lower computer; if there are only equipment classified as data channel among all the detected abnormal parts, then the abnormal equipment combination is only data channel, etc.

[0065] Since chain reactions will occur when abnormalities occur in some water supply systems, the system divides the abnormal parts and classifies them, thereby determining the category combination of all abnormal parts when abnormalities occur in the water supply system, and calculating the equipment scores in different categories. This provides data support for the subsequent grading of abnormal situations from both overall and local aspects, and improves the accuracy of the alarm threshold classification setting.

[0066] In step S4, the system determines the abnormal detection of the water supply system and obtains the equipment combination, and then uses the hierarchical classification method to grade the abnormal water supply situation in combination with the equipment score of the abnormal equipment. Taking the three categories in this example as an example, the specific steps of the grade assessment are as follows:

[0067] Set the assessment level: set three levels, namely, level 1 abnormality, level 2 abnormality and level 3 abnormality. Level 1 abnormality represents severe abnormality, level 2 abnormality represents moderate abnormality, and level 3 abnormality represents mild abnormality;

[0068] Formulate assessment rules:

[0069] Rule 1: When there are two or more abnormal device categories in the device combination, the abnormal situation is determined as a level 1 abnormality;

[0070] Rule 2: When there is only one abnormal device category in the device combination, set the device score threshold. If the device score of the abnormal device in the device combination exceeds the device score threshold, the abnormal situation is determined as a level 2 abnormality; otherwise, the abnormal situation is determined as a level 3 abnormality.

[0071] The system makes different responses after determining the abnormal situation. When the abnormal situation is determined to be a level one abnormality, the system sends a prompt message for immediate processing to the administrator interface, and provides the detected abnormal combination and detailed information on the equipment with abnormalities in the abnormal combination, as well as the repair time, repair cost and solution in the repair history data; when the abnormal situation is determined to be a level two abnormality, the system sends the abnormal problem and abnormal equipment information to the administrator interface, and provides the solution in the repair history data; when the abnormal situation is determined to be a level three abnormality, the system only sends the abnormal equipment information and abnormal prompts to the administrator interface. The system records the responses after making different responses so that it can be used as an auxiliary decision for subsequent water supply system abnormalities.

[0072] Example 2, a secondary water supply system fault warning system based on data analysis, such as Figure 2 As shown, the method for realizing the above-mentioned secondary water supply system fault early warning method based on data analysis includes an abnormality confirmation module, an equipment division module, a combination determination module and an alarm response module;

[0073] The abnormal confirmation module is used to detect the water supply operation status, determine whether the water supply is abnormal and screen out the abnormal parts;

[0074] The equipment classification module is used to classify all equipment in the water supply system, classify different equipment and determine the impact caused by damage to different equipment;

[0075] The combination determination module is used to classify the screened abnormal parts and record the type combination of the abnormal parts when the water supply is abnormal;

[0076] The alarm response module is used to receive the type combination of abnormal parts and make corresponding alarm responses according to the received type combination.

[0077] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0078] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0079] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0080] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0081] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A secondary water supply system fault early warning method based on data analysis, characterized in that: The following steps are included: Step S1: Detect and obtain the secondary water supply operation status, and compare the preset standard threshold to analyze whether the secondary water supply is abnormal; Step S2: Filter out abnormal parts according to abnormal conditions, classify the equipment in the water supply system into categories, compare the repair history data, calculate the repair time and repair cost of each category of equipment, and calculate the impact coefficient of each category and the repair difficulty assessment index of each equipment based on the repair time and repair cost; Step S3: using the influence coefficient of each category to determine the influence weight of each category using the priority diagram method, combining the repair difficulty index of each device and the influence weight of its category to calculate the device score, matching each abnormal part with each category of equipment and determining the abnormal equipment combination; Step S4: The abnormal situation is graded according to the device combination and the device score. The system makes different alarm responses according to the abnormal situation level, records the response behavior, and stores the abnormal device combination information and the abnormal situation level of the corresponding device combination.

2. The secondary water supply system fault early warning method based on data analysis according to claim 1 is characterized in that: In step S1, the secondary water supply operation includes two aspects: on the one hand, detecting whether the water quality of the secondary water supply meets the standard; on the other hand, detecting the water supply condition during the secondary water supply. The standard threshold is the prescribed threshold of the corresponding water quality index and the set standard water pressure threshold.

3. The secondary water supply system fault early warning method based on data analysis according to claim 2 is characterized in that: In step S1, it is detected whether the water quality meets the standard during the secondary water supply. By detecting whether the corresponding water quality index in the water meets the specified threshold during the water supply transmission, the pollutants in the water are detected and compared with the specified threshold of the corresponding water quality index. If any one of them does not meet the specified threshold, it is judged that the water quality is abnormal; When detecting the secondary water supply and transportation situation, the water pressure at the receiving end is detected. When the water pressure at the receiving end is within the set standard water pressure threshold range, the secondary water supply and transportation situation is judged to be normal. When the water pressure at the receiving end exceeds the set standard water pressure threshold for multiple times, the secondary water supply and transportation situation is judged to be abnormal. The number of water quality or water pressure tests and the number of evaluations exceeding the corresponding thresholds can be set according to early warning needs.

4. The secondary water supply system fault early warning method based on data analysis according to claim 1 is characterized in that: In step S2, the water supply system equipment is divided into three parts, namely the host computer, data channel and slave computer. After the system determines that the water quality is abnormal, the host computer, data channel and slave computer in the abnormal part are detected in turn to determine the abnormal equipment and its type.

5. The secondary water supply system fault early warning method based on data analysis according to claim 1 is characterized in that: In step S2, the repair time and cost of each category of equipment are counted by comparing the repair history data, and the repair time and repair cost of each device are normalized and summed to obtain the equipment's repair difficulty assessment index. According to the equipment category, the median of the repair difficulty assessment index of the same category of equipment is taken as the category influence coefficient.

6. The secondary water supply system fault early warning method based on data analysis according to claim 5 is characterized in that: In step S3, the priority diagram method is used to determine the impact weight of each category. The specific steps are as follows: Construct a priority chart, arrange each category from large to small according to the category influence coefficient, compare the category influence coefficients pairwise, mark the category with a large category influence coefficient as 1, mark the categories with the same category influence coefficient as 0.5, and mark the category with a small category influence coefficient as 0. Count the sum of the number of marks for different categories and divide it by the sum of the number of marks for all categories as the influence weight of the corresponding category.

7. The secondary water supply system fault early warning method based on data analysis according to claim 6 is characterized in that: In step S3, the repair time and repair cost of each device are obtained through the repair history data and the repair difficulty assessment index of each device is calculated. The repair difficulty assessment index of each device is multiplied by the impact weight of the category to which the corresponding device belongs, and the calculation result is used as the device score.

8. The secondary water supply system fault early warning method based on data analysis according to claim 1 is characterized in that: In step S4, the abnormal situation is classified using a hierarchical classification method according to the device combination and the device score. The specific steps are as follows: Set the assessment level: set three levels, namely, level 1 abnormality, level 2 abnormality and level 3 abnormality. Level 1 abnormality represents severe abnormality, level 2 abnormality represents moderate abnormality, and level 3 abnormality represents mild abnormality; Formulate assessment rules: Rule 1: When there are two or more abnormal device categories in the device combination, the abnormal situation is determined as a level 1 abnormality; Rule 2: When there is only one abnormal device category in the device combination, set a device score threshold. If the device score of the abnormal device in the device combination exceeds the device score threshold, the abnormal situation is determined as a level 2 abnormality; otherwise, the abnormal situation is determined as a level 3 abnormality. The device score threshold is the average of all device scores.

9. A secondary water supply system fault early warning system based on data analysis, based on the secondary water supply system fault early warning method based on data analysis according to any one of claims 1 to 8, characterized in that: It includes an abnormality confirmation module, an equipment division module, a combination determination module and an alarm response module; The abnormal confirmation module is used to detect the water supply operation status, determine whether the water supply is abnormal and screen out the abnormal parts; The equipment classification module is used to classify all equipment in the water supply system, classify different equipment and determine the impact caused by damage to different equipment; The combination determination module is used to classify the screened abnormal parts and record the type combination of the abnormal parts when the water supply is abnormal; The alarm response module is used to receive the type combination of abnormal parts and make corresponding alarm responses according to the received type combination.

Images