CN114298174A - Water supply abnormity identification method, system, electronic equipment and medium - Google Patents
Water supply abnormity identification method, system, electronic equipment and medium Download PDFInfo
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Abstract
The invention is suitable for the technical field of water supply identification and provides a water supply abnormity identification method, a system, electronic equipment and a medium, wherein the method comprises the following steps: acquiring position information of a water supply pipe, and setting a pressure threshold value according to the position information of the water supply pipe; acquiring first pressure data of a water supply pipe, and classifying the first pressure data according to a pressure threshold to acquire a classification result; if the classification result is the first water leakage abnormity, acquiring a sequence standard deviation of the first pressure data, and comparing the sequence standard deviation of the first pressure data with a preset standard deviation to acquire a first identification result; if the classification result is the second water leakage abnormity, acquiring a sequence average value of the first pressure data, and comparing the sequence average value of the first pressure data with a preset average value to acquire a second identification result; the problem of can't carry out qualitative and quantitative analysis to fire control water supply abnormity among the prior art is solved.
Description
Technical Field
The invention relates to the technical field of water supply identification, in particular to a water supply abnormity identification method, a water supply abnormity identification system, electronic equipment and a medium.
Background
The building fire water supply system is the most core fire fighting infrastructure and is an indispensable life line project for fire emergency rescue. With the acceleration of the new urbanization construction process, the functions of various buildings become more complex. The number of high-rise, underground, large-span, large-space buildings and large commercial complexes is increasing, and the fire-fighting water supply systems of the buildings tend to be complicated. However, fire supervisors and maintenance personnel usually detect the operation condition of the fire water supply system of a building according to experience, and judge the problems of pipe network leakage, under/over pressure, water drainage, blockage, mistaken opening/closing of a gate valve, equipment failure and the like completely depend on manpower. The traditional fault diagnosis mode depends heavily on the technical level and experience accumulation of supervisors/maintenance personnel, on one hand, the technical threshold is higher, on the other hand, the traditional fault diagnosis mode can be effective on a simple fire-fighting water supply system, but for the fire-fighting water supply system with the increasingly complex current structure, the traditional fault diagnosis mode is not only low in efficiency, but also low in accuracy.
At present, the urban fire-fighting remote monitoring system realizes remote real-time monitoring and alarming on a building fire-fighting water supply system, and promotes daily management of the fire-fighting water supply system to a certain extent. However, the urban fire-fighting remote monitoring system is used for providing water pressure, water level and alarm data of monitoring point locations, sensing data of a large number of internet of things devices are not timely and effectively processed and applied, faults of a fire-fighting water supply system cannot be qualitatively and quantitatively analyzed, and data resources are wasted.
Disclosure of Invention
The invention provides a water supply abnormity identification method, a system, electronic equipment and a medium, which are used for solving the problem that qualitative and quantitative analysis on fire water supply abnormity cannot be carried out in the prior art.
The invention provides a water supply abnormity identification method, which comprises the following steps: acquiring position information of a water supply pipe, and setting a first pressure threshold value and a second pressure threshold value according to the position information of the water supply pipe, wherein the second pressure threshold value is larger than the first pressure threshold value;
acquiring first pressure data of the water supply pipe, and classifying the first pressure data according to the first pressure threshold and the second pressure threshold to acquire a classification result, wherein the classification result comprises normal, first water leakage abnormity and second water leakage abnormity;
if the classification result is first water leakage abnormity, acquiring a sequence standard deviation of the first pressure data, and comparing the sequence standard deviation of the first pressure data with a preset standard deviation to acquire a first identification result, wherein the first identification result comprises slight water leakage;
and if the classification result is the second water leakage abnormity, acquiring a sequence average value of the first pressure data, and comparing the sequence average value of the first pressure data with a preset average value to acquire a second identification result, wherein the second identification result comprises severe water leakage.
Optionally, the classifying the first pressure data according to the first pressure threshold and the second pressure threshold, and obtaining a classification result includes:
comparing the first pressure data with the first pressure threshold, wherein if the first pressure data is less than or equal to the first pressure threshold, the classification result is normal;
if the first pressure data is larger than the first pressure threshold, comparing the first pressure data with the second pressure threshold;
if the first pressure data is smaller than or equal to the second pressure threshold, the classification result is a first water leakage abnormity;
and if the first pressure data is larger than the second pressure threshold, the classification result is a second water leakage abnormity.
Optionally, the acquiring first pressure data of the water supply pipe comprises: acquiring pressure data of the water supply pipe and the generation time of the pressure data, and performing time sequencing processing on the pressure data according to the generation time of the pressure data to acquire time sequence pressure data;
and preprocessing the time sequence pressure data to obtain first pressure data of the water supply pipe, wherein the preprocessing comprises intercepting the time sequence pressure data by adopting a preset first sliding window.
Optionally, after obtaining the first recognition result, the method further includes: if the first identification result is slight water leakage, intercepting the time sequence pressure data by adopting a preset second sliding window to obtain a plurality of second pressure data;
and acquiring sequence standard deviations of the plurality of second pressure data, comparing the sequence standard deviations of the second pressure data with the preset standard deviations to acquire a first standard deviation comparison result, wherein the first standard deviation comparison result comprises a first abnormity and a first abnormity probability, and acquiring a first target identification result according to the first abnormity probability.
Optionally, after the obtaining the second recognition result, the method further includes: if the second identification result is that the water is heavily leaked, intercepting the time sequence pressure data by adopting a preset third sliding window to obtain a plurality of third pressure data;
and acquiring a sequence average value of the plurality of third pressure data, comparing the sequence average value of the third pressure data with the preset average value to acquire an average value comparison result, wherein the average value comparison result comprises a second abnormity and a second abnormity probability, and acquiring a second target identification result according to the second abnormity probability.
Optionally, after the obtaining the second recognition result, the method further includes: if the probability of the second anomaly is smaller than a preset probability threshold, obtaining sequence standard deviations of the plurality of third pressure data, comparing the sequence standard deviations of the third pressure data with the preset standard deviations to obtain a second standard deviation comparison result, wherein the second standard deviation comparison result comprises the third anomaly and the probability of the third anomaly, and obtaining a third target identification result according to the probability of the third anomaly.
The invention also provides a water supply abnormity identification system, which comprises: the device comprises a threshold value setting module, a first pressure threshold value setting module and a second pressure threshold value setting module, wherein the threshold value setting module is used for acquiring the position information of a water supply pipe and setting a first pressure threshold value and a second pressure threshold value according to the position information of the water supply pipe, and the second pressure threshold value is larger than the first pressure threshold value;
the classification module is used for acquiring first pressure data of the water supply pipe, classifying the first pressure data according to the first pressure threshold and the second pressure threshold, and acquiring a classification result, wherein the classification result comprises normal, first water leakage abnormity and second water leakage abnormity;
the first identification module is used for acquiring a sequence standard deviation of the first pressure data if the classification result is the first water leakage abnormity, comparing the sequence standard deviation of the first pressure data with a preset standard deviation, and acquiring a first identification result, wherein the first identification result comprises slight water leakage;
the second identification module is configured to obtain a sequence average value of the first pressure data if the classification result is the second water leakage abnormality, compare the sequence average value of the first pressure data with a preset average value, and obtain a second identification result, where the second identification result includes heavy water leakage, and the threshold setting module, the classification module, the first identification module, and the second identification module are connected.
Optionally, the water supply abnormality recognition system further includes: and the sensor configuration module is used for configuring the position information of the pressure sensors and the number of the pressure sensors of the water supply pipe according to the position information of the water supply pipe and acquiring the pressure data of the water supply pipe based on the pressure sensors.
The present invention also provides an electronic device comprising: a processor and a memory;
the memory is used for storing computer programs, and the processor is used for executing the computer programs stored by the memory so as to enable the electronic equipment to execute the water supply abnormity identification method.
The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the water supply abnormality identification method as described above.
The invention has the beneficial effects that: according to the water supply abnormity identification method, a first pressure threshold value and a second pressure threshold value are set according to the position information of the water supply pipe, the first pressure data of the water supply pipe is classified through the first pressure threshold value and the second pressure threshold value, the classification result of the water supply pipe is obtained, and therefore the preliminary judgment of the water leakage state of the water supply pipe is achieved; and then carrying out abnormity analysis on the pressure data of the water supply pipe according to the classification result, when the classification result is the first water leakage abnormity, analyzing the water leakage state of the water supply pipe by adopting the sequence standard deviation of the first pressure data, and when the classification result is the second water leakage abnormity, analyzing the water leakage state of the water supply pipe by adopting the sequence average value of the first pressure data, thereby realizing accurate identification of the water leakage condition of the water supply pipe and solving the problem that qualitative and quantitative analysis cannot be carried out on the fire water supply abnormity in the prior art.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic flow chart of a water supply abnormality identification method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first method for obtaining pressure data according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating a method for classifying first pressure data according to an embodiment of the present invention;
FIG. 4 is a graph of pressure data for a water supply line with a slight water leak in an embodiment of the present invention;
FIG. 5 is a graph of pressure data for a heavily leaking water supply in an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a water supply abnormality recognition system according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
The building fire-fighting water supply system is used as a core facility of the building fire-fighting system and is widely installed and used in a large number of buildings, and a large number of fire cases show that the intact and effective fire-fighting water supply system plays an important role in the aspects of reducing fire loss to the maximum extent, realizing self-defense and self-rescue of building fire and the like. The water supply pipe is an important component of the fire-fighting water supply system, so that the intact water supply pipe can ensure that the building fire-fighting water supply system can timely control and extinguish fire in the initial stage of a fire. The water supply pipe can be damaged due to aging, corrosion and the like in the using process, so that the water leakage phenomenon of the water supply pipe is caused; however, the water leakage state of the water supply pipe cannot be accurately identified at present. Therefore, the water supply pipe is provided with the pressure sensor, the pressure data collected by the pressure sensor are classified to obtain the classification result, and the water supply pipe is subjected to water leakage abnormity analysis according to the classification result, so that the damage condition of the water supply pipe is obtained.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
First embodiment
Fig. 1 is a schematic flow chart of a water supply abnormality identification method according to an embodiment of the present invention.
As shown in fig. 1, the above-mentioned water supply abnormality identification method includes steps S110 to S140:
s110, acquiring position information of a water supply pipe, and setting a first pressure threshold value and a second pressure threshold value according to the position information of the water supply pipe;
s120, acquiring first pressure data of the water supply pipe, and classifying the first pressure data according to the first pressure threshold and the second pressure threshold to acquire a classification result;
s130, if the classification result is the first water leakage abnormity, acquiring a sequence standard deviation of the first pressure data, and comparing the sequence standard deviation of the first pressure data with a preset standard deviation to acquire a first identification result;
and S140, if the classification result is the second water leakage abnormity, acquiring a sequence average value of the first pressure data, and comparing the sequence average value of the first pressure data with a preset average value to acquire a second identification result.
In step 110 of this embodiment, the position information of the water supply pipe includes height information of the water supply pipe, wherein the height information of the water supply pipe can be based on the water supply pump. After the position information of the water supply pipe is obtained, in order to better identify the water leakage condition of the water supply pipe, the position information of a pressure sensor of the water supply pipe and the number of the pressure sensors need to be configured according to the position information of the water supply pipe; specifically, the number of the pressure sensors is obtained according to the ratio of the height of the water supply pipe to the preset height, and the pressure sensors are uniformly arranged on the water supply pipe. Wherein, predetermine the height and set for according to the material and the pipe diameter of feed pipe, the material of feed pipe damages the degree of difficulty and is higher then predetermine the height big more, and the feed pipe diameter is big more, predetermines the height little. The concrete implementation method for setting the first pressure threshold and the second pressure threshold according to the position information of the water supply pipe comprises the following steps: acquiring the position information of a pressure sensor arranged on a water supply pipe according to the position information of the water supply pipe to obtain the target position information of the water supply pipe; the method comprises the steps of obtaining the material of the water supply pipe and the pipe diameter of the water supply pipe, setting a first pressure threshold value and a second pressure threshold value according to target position information of the water supply pipe, the material of the water supply pipe and the pipe diameter of the water supply pipe, wherein the first pressure threshold value is the lowest pressure of slight damage of the water supply pipe, and the second pressure threshold value is the lowest pressure of severe damage of the water supply pipe.
In step S120 of the present embodiment, please refer to fig. 2 for a specific implementation method of obtaining the first pressure data, and fig. 2 is a flowchart illustrating a method of obtaining the first pressure data according to an embodiment of the present invention.
As shown in fig. 2, the first pressure data acquiring method may include the following steps S210 to S220:
s210, acquiring pressure data of the water supply pipe and the generation time of the pressure data, and performing time sequencing processing on the pressure data according to the generation time of the pressure data to acquire time sequence pressure data;
s220, preprocessing the time sequence pressure data to obtain first pressure data of the water supply pipe, wherein the preprocessing comprises intercepting the time sequence pressure data by adopting a preset first sliding window.
Referring to fig. 3, a specific implementation method for classifying the first pressure data after the first pressure data is acquired and classifying the first pressure data according to the first pressure threshold and the second pressure threshold is shown, where fig. 3 is a schematic flow chart of a classification method for the first pressure data in an embodiment of the present invention.
As shown in fig. 3, the classification method of the first pressure data may include the following steps S310 to S340:
s310, comparing the first pressure data with the first pressure threshold, wherein if the first pressure data is smaller than or equal to the first pressure threshold, the classification result is normal;
s320, if the first pressure data is larger than the first pressure threshold, comparing the first pressure data with the second pressure threshold;
s330, if the first pressure data is smaller than or equal to the second pressure threshold, the classification result is a first water leakage abnormity;
s340, if the first pressure data is greater than the second pressure threshold, the classification result is a second water leakage anomaly.
In one embodiment, the period of the preset first sliding window is set according to the data volume of the time sequence pressure data and the data processing capacity of the abnormal water supply system. The first pressure data is a plurality of pressure data, and when the first pressure data is compared with the first pressure threshold and the second pressure threshold, the average value of the first pressure data is compared with the first pressure threshold and the second pressure threshold. In the actual water supply process of a building fire-fighting system, the pressure acquired when the water supply pipes at the same position of the same water supply pipe are slightly damaged is greater than the pressure acquired when the water supply pipes are normal, and the pressure acquired when the water supply pipes are severely damaged is greater than the pressure acquired when the water supply pipes are slightly damaged; therefore, the first pressure data are classified through the first pressure threshold and the second pressure threshold, and therefore preliminary screening of the first pressure data of the water supply pipe is achieved.
Referring to fig. 4, fig. 4 is a pressure data diagram of a water supply pipe with slight water leakage according to an embodiment of the present invention; in the actual water supply process of building fire extinguishing system, when the flow of leaking of feed pipe is less, pressure variation can present and vibrate the ripples shape, and this is mainly because leak and lead to pressure to diminish, and water supply system's real-time pressure (gas pitcher or pond moisturizing) can be not enough with pressure in the short time, consequently can present the constantly changing condition that vibrates of pressure. Referring to fig. 5, fig. 5 is a pressure data diagram of a water supply pipe with heavy water leakage according to an embodiment of the present invention; when the water leakage flow of the water supply pipe is large, the pressure stabilizing pump pressure supplementing system cannot supplement pressure in time, and the pressure can be continuously reduced. When the pressure drops below a certain threshold value, the pressure compensating pump is triggered to start to compensate the pressure, the pressure can be stabilized at a fixed value, and after water leakage is finished, the pressure can return to a normal value due to the fact that the pressure stabilizing pump is controlled left and right. The pressure thus exhibits a decreasing waveform. In order to realize more accurate identification of water leakage of the water supply pipe, after primary identification is carried out on first pressure data of the water supply pipe (classification processing is carried out on the first pressure data according to a first pressure threshold and a second pressure threshold), different classification results are identified in different modes according to that pressure vibrates continuously during slight water leakage and pressure is reduced to a fixed range during severe water leakage.
In step S130 of this embodiment, if the classification result is a first water leakage anomaly, obtaining a sequence standard deviation of the first pressure data, comparing the sequence standard deviation of the first pressure data with a preset standard deviation, obtaining a first identification result, if the sequence standard deviation of the first pressure data is smaller than the preset standard deviation, the first identification result is a slight water leakage, and when the first identification result is a slight water leakage, generating an early warning message to remind a corresponding responsible object to handle the slight water leakage phenomenon of the water supply pipe, so that the building fire-fighting water supply system can normally operate; and if the sequence standard deviation of the first pressure data is greater than or equal to the preset standard deviation, the first identification result is normal, and if the first identification result is normal, the water supply pipe is not damaged. In order to ensure the accuracy of the acquired working state of the water supply pipe, when the first identification result is slight water leakage, the specific implementation method for further confirming the first identification result comprises the following steps: if the first identification result is slight water leakage, intercepting the time sequence pressure data by adopting a preset second sliding window to obtain a plurality of second pressure data; and acquiring sequence standard deviations of the plurality of second pressure data, comparing the sequence standard deviations of the second pressure data with the preset standard deviations to acquire a first standard deviation comparison result, wherein the first standard deviation comparison result comprises a first abnormity and a first abnormity probability, and acquiring a first target identification result according to the first abnormity probability. And when the probability of the first abnormity is greater than or equal to a preset probability threshold value, the first target identification result is that the water supply pipe is slightly damaged. And intercepting the time sequence pressure data through the period of a preset second sliding window to obtain second pressure data, performing sequence standard deviation calculation on the second pressure data according to a first recognition result, obtaining a first standard deviation comparison result, obtaining a first abnormal probability, and comparing the first abnormal probability with a preset probability threshold value, so that the damage degree of the water supply pipe is obtained, and the accurate recognition of the state of the water supply pipe is realized.
In step S140 of this embodiment, if the classification result is the second water leakage abnormality, the sequence average value of the first pressure data is obtained, the sequence average value of the first pressure data is compared with the preset average value, a second identification result is obtained, if the sequence average value of the first pressure data is smaller than the preset average value, the second identification result is heavy water leakage, and when the second identification result is heavy water leakage, the warning information may be generated to remind the corresponding responsible object to handle the heavy water leakage phenomenon of the water supply pipe, so that the building fire-fighting water supply system can normally operate. In order to ensure the accuracy of the acquired working state of the water supply pipe, when the second identification result is heavy water leakage, the specific implementation method for further confirming the second identification result comprises the following steps: if the second identification result is that the water is heavily leaked, intercepting the time sequence pressure data by adopting a preset third sliding window to obtain a plurality of third pressure data; and acquiring a sequence average value of the plurality of third pressure data, comparing the sequence average value of the third pressure data with the preset average value to acquire an average value comparison result, wherein the average value comparison result comprises a second abnormity and a second abnormity probability, and acquiring a second target identification result according to the second abnormity probability. And when the probability of the second abnormity is greater than or equal to a preset probability threshold value, the second target identification result is that the water supply pipe is severely damaged. In order to ensure the accuracy of the acquired working state of the water supply pipe, when the second identification result is heavy water leakage, the specific implementation method for further confirming the second identification result further comprises the following steps: if the probability of the second anomaly is smaller than a preset probability threshold, obtaining sequence standard deviations of the plurality of third pressure data, comparing the sequence standard deviations of the third pressure data with the preset standard deviations to obtain a second standard deviation comparison result, wherein the second standard deviation comparison result comprises the third anomaly and the probability of the third anomaly, and obtaining a third target identification result according to the probability of the third anomaly. And when the sequence standard deviation of the third pressure data is greater than or equal to a preset standard deviation, the second standard deviation comparison result is a third anomaly, and when the probability of the third anomaly is greater than or equal to a preset probability threshold, the third target identification result is that the water supply pipe is slightly damaged. And intercepting the time sequence pressure data to obtain second pressure data after a preset third sliding window period, calculating the sequence standard deviation and the sequence average deviation of the second pressure data according to a second identification result, obtaining an average value second standard deviation comparison result, obtaining the probability of second abnormity and the probability of third abnormity, comparing the probability of the second abnormity with a preset probability threshold value, and comparing the probability of the third abnormity with a preset probability threshold value, thereby obtaining the damage degree of the water supply pipe and realizing accurate identification of the state of the water supply pipe.
According to the embodiment, a first pressure threshold value and a second pressure threshold value are set according to the position information of the water supply pipe, the first pressure data of the water supply pipe are classified through the first pressure threshold value and the second pressure threshold value, the classification result of the water supply pipe is obtained, and therefore the preliminary judgment of the water leakage state of the water supply pipe is achieved; and then carrying out abnormity analysis on the pressure data of the water supply pipe according to the classification result, when the classification result is the first water leakage abnormity, analyzing the water leakage state of the water supply pipe by adopting the sequence standard deviation of the first pressure data, and when the classification result is the second water leakage abnormity, analyzing the water leakage state of the water supply pipe by adopting the sequence average value of the first pressure data, thereby realizing accurate identification of the water leakage condition of the water supply pipe and solving the problem that qualitative and quantitative analysis cannot be carried out on the fire water supply abnormity in the prior art.
Second embodiment
Based on the same inventive concept as the method in the first embodiment, correspondingly, the embodiment also provides a water supply abnormality identification system.
Fig. 6 is a schematic flow chart of a water supply abnormality recognition system according to the present invention.
As shown in fig. 6, the water supply abnormality recognition system includes: 61 threshold setting module, 62 classification module, 63 first identification module and 64 second identification module.
The system comprises a threshold setting module, a first pressure threshold setting module and a second pressure threshold setting module, wherein the threshold setting module is used for acquiring position information of a water supply pipe, and setting a first pressure threshold and a second pressure threshold according to the position information of the water supply pipe, and the second pressure threshold is larger than the first pressure threshold;
the classification module is used for acquiring first pressure data of the water supply pipe, classifying the first pressure data according to the first pressure threshold and the second pressure threshold, and acquiring a classification result, wherein the classification result comprises normal, first water leakage abnormity and second water leakage abnormity;
the first identification module is used for acquiring a sequence standard deviation of the first pressure data if the classification result is the first water leakage abnormity, comparing the sequence standard deviation of the first pressure data with a preset standard deviation, and acquiring a first identification result, wherein the first identification result comprises slight water leakage;
the second identification module is configured to obtain a sequence average value of the first pressure data if the classification result is the second water leakage abnormality, compare the sequence average value of the first pressure data with a preset average value, and obtain a second identification result, where the second identification result includes heavy water leakage, and the threshold setting module, the classification module, the first identification module, and the second identification module are connected.
In some exemplary embodiments, the feedwater abnormality identification system further includes:
and the sensor configuration module is used for configuring the position information of the pressure sensors and the number of the pressure sensors of the water supply pipe according to the position information of the water supply pipe and acquiring the pressure data of the water supply pipe based on the pressure sensors.
In some exemplary embodiments, the classification module comprises:
the classification unit is used for comparing the first pressure data with the first pressure threshold, and if the first pressure data is smaller than or equal to the first pressure threshold, the classification result is normal;
if the first pressure data is larger than the first pressure threshold, comparing the first pressure data with the second pressure threshold;
if the first pressure data is smaller than or equal to the second pressure threshold, the classification result is a first water leakage abnormity;
and if the first pressure data is larger than the second pressure threshold, the classification result is a second water leakage abnormity.
In some exemplary embodiments, the classification module further comprises:
the preprocessing unit is used for acquiring pressure data of the water supply pipe and the generation time of the pressure data, and performing time sequencing processing on the pressure data according to the generation time of the pressure data to acquire time sequence pressure data;
and preprocessing the time sequence pressure data to obtain first pressure data of the water supply pipe, wherein the preprocessing comprises intercepting the time sequence pressure data by adopting a preset first sliding window.
In some exemplary embodiments, the first identification module comprises:
the first target identification unit is used for intercepting the time sequence pressure data by adopting a preset second sliding window to obtain a plurality of second pressure data if the first identification result is slight water leakage;
and acquiring sequence standard deviations of the plurality of second pressure data, comparing the sequence standard deviations of the second pressure data with the preset standard deviations to acquire a first standard deviation comparison result, wherein the first standard deviation comparison result comprises a first abnormity and a first abnormity probability, and acquiring a first target identification result according to the first abnormity probability.
In some exemplary embodiments, the second identification module comprises:
the second target identification unit is used for intercepting the time sequence pressure data by adopting a preset third sliding window to obtain a plurality of third pressure data if the second identification result is that the water is heavily leaked;
and acquiring a sequence average value of the plurality of third pressure data, comparing the sequence average value of the third pressure data with the preset average value to acquire an average value comparison result, wherein the average value comparison result comprises a second abnormity and a second abnormity probability, and acquiring a second target identification result according to the second abnormity probability.
In some exemplary embodiments, the second identification module comprises:
and the third target identification unit is used for acquiring sequence standard deviations of the plurality of third pressure data if the probability of the second abnormality is smaller than a preset probability threshold, comparing the sequence standard deviations of the third pressure data with the preset standard deviations to acquire a second standard deviation comparison result, comparing the second standard deviation comparison result with the third abnormality and the probability of the third abnormality, and acquiring a third target identification result according to the probability of the third abnormality.
The present embodiment also provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor implements any of the methods in the present embodiments.
In an embodiment, referring to fig. 7, the embodiment further provides an electronic device 700, which includes a memory 701, a processor 702, and a computer program stored on the memory and capable of running on the processor, and when the processor 702 executes the computer program, the steps of the method according to any of the above embodiments are implemented.
The computer-readable storage medium in the present embodiment can be understood by those skilled in the art as follows: all or part of the steps for implementing the above method embodiments may be performed by hardware associated with a computer program. The aforementioned computer program may be stored in a computer readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The electronic device provided by the embodiment comprises a processor, a memory, a transceiver and a communication interface, wherein the memory and the communication interface are connected with the processor and the transceiver and are used for realizing mutual communication, the memory is used for storing a computer program, the communication interface is used for carrying out communication, and the processor and the transceiver are used for operating the computer program to enable the electronic device to execute the steps of the method.
In this embodiment, the Memory may include a Random Access Memory (RAM), and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In the above-described embodiments, references in the specification to "the present embodiment," "an embodiment," "another embodiment," "in some exemplary embodiments," or "other embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments. The various appearances of the phrase "the present embodiment," "one embodiment," or "another embodiment" are not necessarily all referring to the same embodiment.
In the embodiments described above, although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory structures (e.g., dynamic ram (dram)) may use the discussed embodiments. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The foregoing embodiments are merely illustrative of the principles of the present invention and its efficacy, and are not to be construed as limiting the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A feedwater abnormality recognition method characterized by comprising:
acquiring position information of a water supply pipe, and setting a first pressure threshold value and a second pressure threshold value according to the position information of the water supply pipe, wherein the second pressure threshold value is larger than the first pressure threshold value;
acquiring first pressure data of the water supply pipe, and classifying the first pressure data according to the first pressure threshold and the second pressure threshold to acquire a classification result, wherein the classification result comprises normal, first water leakage abnormity and second water leakage abnormity;
if the classification result is first water leakage abnormity, acquiring a sequence standard deviation of the first pressure data, and comparing the sequence standard deviation of the first pressure data with a preset standard deviation to acquire a first identification result, wherein the first identification result comprises slight water leakage;
and if the classification result is the second water leakage abnormity, acquiring a sequence average value of the first pressure data, and comparing the sequence average value of the first pressure data with a preset average value to acquire a second identification result, wherein the second identification result comprises severe water leakage.
2. The method for identifying the water supply abnormality according to claim 1, wherein the classifying the first pressure data according to the first pressure threshold and the second pressure threshold and obtaining a classification result includes:
comparing the first pressure data with the first pressure threshold, wherein if the first pressure data is less than or equal to the first pressure threshold, the classification result is normal;
if the first pressure data is larger than the first pressure threshold, comparing the first pressure data with the second pressure threshold;
if the first pressure data is smaller than or equal to the second pressure threshold, the classification result is a first water leakage abnormity;
and if the first pressure data is larger than the second pressure threshold, the classification result is a second water leakage abnormity.
3. The feedwater abnormality recognition method of claim 2, wherein the acquiring first pressure data of the feedwater pipe comprises:
acquiring pressure data of the water supply pipe and the generation time of the pressure data, and performing time sequencing processing on the pressure data according to the generation time of the pressure data to acquire time sequence pressure data;
and preprocessing the time sequence pressure data to obtain first pressure data of the water supply pipe, wherein the preprocessing comprises intercepting the time sequence pressure data by adopting a preset first sliding window.
4. The water supply abnormality recognition method according to claim 3, further comprising, after the acquiring the first recognition result:
if the first identification result is slight water leakage, intercepting the time sequence pressure data by adopting a preset second sliding window to obtain a plurality of second pressure data;
and acquiring sequence standard deviations of the plurality of second pressure data, comparing the sequence standard deviations of the second pressure data with the preset standard deviations to acquire a first standard deviation comparison result, wherein the first standard deviation comparison result comprises a first abnormity and a first abnormity probability, and acquiring a first target identification result according to the first abnormity probability.
5. The water supply abnormality recognition method according to claim 3, further comprising, after the obtaining of the second recognition result:
if the second identification result is that the water is heavily leaked, intercepting the time sequence pressure data by adopting a preset third sliding window to obtain a plurality of third pressure data;
and acquiring a sequence average value of the plurality of third pressure data, comparing the sequence average value of the third pressure data with the preset average value to acquire an average value comparison result, wherein the average value comparison result comprises a second abnormity and a second abnormity probability, and acquiring a second target identification result according to the second abnormity probability.
6. The water supply abnormality recognition method according to claim 5, further comprising, after the obtaining of the second recognition result:
if the probability of the second anomaly is smaller than a preset probability threshold, obtaining sequence standard deviations of the plurality of third pressure data, comparing the sequence standard deviations of the third pressure data with the preset standard deviations to obtain a second standard deviation comparison result, wherein the second standard deviation comparison result comprises the third anomaly and the probability of the third anomaly, and obtaining a third target identification result according to the probability of the third anomaly.
7. A feedwater abnormality identification system, comprising:
the device comprises a threshold value setting module, a first pressure threshold value setting module and a second pressure threshold value setting module, wherein the threshold value setting module is used for acquiring the position information of a water supply pipe and setting a first pressure threshold value and a second pressure threshold value according to the position information of the water supply pipe, and the second pressure threshold value is larger than the first pressure threshold value;
the classification module is used for acquiring first pressure data of the water supply pipe, classifying the first pressure data according to the first pressure threshold and the second pressure threshold, and acquiring a classification result, wherein the classification result comprises normal, first water leakage abnormity and second water leakage abnormity;
the first identification module is used for acquiring a sequence standard deviation of the first pressure data if the classification result is the first water leakage abnormity, comparing the sequence standard deviation of the first pressure data with a preset standard deviation, and acquiring a first identification result, wherein the first identification result comprises slight water leakage;
the second identification module is configured to obtain a sequence average value of the first pressure data if the classification result is the second water leakage abnormality, compare the sequence average value of the first pressure data with a preset average value, and obtain a second identification result, where the second identification result includes heavy water leakage, and the threshold setting module, the classification module, the first identification module, and the second identification module are connected.
8. The water supply abnormality recognition system according to claim 7, further comprising:
and the sensor configuration module is used for configuring the position information of the pressure sensors and the number of the pressure sensors of the water supply pipe according to the position information of the water supply pipe and acquiring the pressure data of the water supply pipe based on the pressure sensors.
9. An electronic device comprising a processor, a memory, and a communication bus;
the communication bus is used for connecting the processor and the memory;
the processor is configured to execute a computer program stored in the memory to implement the method of any one of claims 1-6.
10. A computer-readable storage medium, having stored thereon a computer program for causing a computer to perform the method of any one of claims 1-6.
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