CN113790822B - Method and device for detecting abnormity of ground measured temperature data and readable storage medium - Google Patents

Abstract

The invention relates to the technical field of abnormal value detection, and provides a method, device, computer-readable storage medium and electronic equipment for abnormal detection of ground measurement temperature data. ; wherein, the water profile temperature data includes the respective temperature values of multiple depth layers; obtain multiple temperature value differences; wherein, multiple temperature value differences include the bottom or top two depth layers of each waypoint of multiple waypoints The difference between the temperature values or the difference between the temperature values of the multiple waypoints corresponding to the same two adjacent depth layers; based on the multiple temperature value differences, determine the abnormal difference among the multiple temperature value differences; The abnormal temperature value is determined according to the temperature value of the target waypoint corresponding to the abnormal difference value. Through the technical solutions of the embodiments of the present invention, the accuracy and objectivity of the temperature data for on-site monitoring can be improved, and accurate and effective data support is provided for water body thermal pollution management and water environment supervision.

Description

Method, device and readable storage medium for abnormal detection of ground measurement temperature data

technical field

The present invention relates to the technical field of abnormal value detection, and in particular, to a method, device and readable storage medium for abnormal detection of ground measurement temperature data.

Background technique

With the increasing demand for electricity in my country, the development of power plants in coastal areas has gradually attracted public attention, and the thermal pollution of water bodies caused by power plants in the process of work inevitably becomes one of the hot spots. Temperature is a basic indicator and an important characterization of seawater quality. Thermal pollution of water bodies will lead to a sharp rise in water temperature in local waters, a decrease in dissolved oxygen in water, and a decrease in water density and viscosity, thus affecting the species, quantity and community structure of aquatic organisms in the sea area. It will harm the biodiversity and ecological balance of the sea area near the power plant. Therefore, regular and accurate investigation of thermal pollution in water bodies is of great significance to the protection of water quality and ecological environment in sea areas.

At present, the commonly used water temperature and thermal pollution monitoring methods are: ground measurement monitoring. Among them, ground measurement monitoring is the most direct and intuitive means of thermal pollution monitoring, mainly using manual measurement to conduct on-the-spot investigation of water areas. This method can directly obtain objective and real sea surface temperature and sea temperature-depth profile and other related data. CTD (Conductivity-Temperature-Depth) or TD (Temperature-Depth) is an important tool for measuring the physical properties of the ocean and can be used to measure precise parameters such as seawater temperature and salinity at different depths. However, due to the influence of various factors such as sunlight, human disturbance, environmental changes, and sea depths, abnormal values are easily generated in the monitoring data, which leads to the deterioration of the quality of the monitoring data, questioning the authenticity and objectivity of the data, and affecting the accuracy of subsequent analysis results. Spend. Therefore, the identification and elimination of outliers has important application value and practical significance for effectively improving data quality, objectively reflecting water temperature, and accurately guiding ecological environmental protection.

Therefore, how to identify outliers in ground-measured temperature data is an urgent problem to be solved.

SUMMARY OF THE INVENTION

The invention provides an abnormal detection method, device, computer-readable storage medium and electronic equipment of ground measurement temperature data, which can improve the accuracy and objectivity of field monitoring temperature data, and provide accurate water body thermal pollution management and water environment supervision. Effective data support.

In a first aspect, the present invention provides a method for detecting anomalies in ground-measured temperature data, including:

Acquire respective water profile temperature data of multiple waypoints in the target water body area; wherein, the water profile temperature data includes respective temperature values of multiple depth layers, and the multiple depth layers are based on the measurement of the corresponding waypoints by the layered water depths The water depth is stratified to obtain;

Obtain multiple temperature value differences; wherein, the multiple temperature value differences include the difference between the temperature values of the bottom two depth layers of each of the multiple waypoints, and the temperature value of each of the multiple waypoints. The difference between the temperature values of the two depth layers on the top layer of the point, or the difference between the temperature values of multiple target waypoints corresponding to the same two adjacent depth layers, where the target waypoint is the multiple destination waypoints. There are waypoints with temperature values corresponding to the two adjacent depth layers in the points;

determining an abnormal difference in the plurality of temperature value differences based on the plurality of temperature value differences;

The abnormal temperature value is determined according to the temperature value of the waypoint corresponding to the abnormal difference value.

In a second aspect, the present invention provides an abnormality detection device for ground measurement temperature data, including:

The temperature data acquisition module is used to acquire the water profile temperature data of each of the multiple waypoints in the target water body area; wherein, the water profile temperature data includes the respective temperature values of the multi-layer depth layers, and the multi-layer depth layers are based on the hierarchical The water depth is obtained by layering the measured water depth of the corresponding waypoint;

A difference value acquisition module, configured to acquire a plurality of temperature value differences; wherein, the plurality of temperature value differences include the difference between the temperature values of the two depth layers at the bottom of each waypoint of the plurality of waypoints, the The difference between the temperature values of the two depth layers at the top of each of the multiple waypoints, or the difference between the temperature values of the two adjacent depth layers corresponding to the multiple target waypoints, the target navigation The point is a waypoint with temperature values corresponding to the two adjacent depth layers in the plurality of waypoints;

an abnormal value detection module, configured to determine an abnormal difference value among the plurality of temperature value differences based on the plurality of temperature value differences;

The abnormal value determination module is configured to determine the abnormal temperature value according to the temperature value of the waypoint corresponding to the abnormal difference value.

In a third aspect, the present invention provides a computer-readable storage medium, comprising execution instructions, when a processor of an electronic device executes the execution instructions, the processor executes the method according to any one of the first aspects.

In a fourth aspect, the present invention provides an electronic device, including a processor and a memory storing execution instructions. When the processor executes the execution instructions stored in the memory, the processor executes the first aspect. any of the methods described above.

The present invention provides a method, a device, a computer-readable storage medium and an electronic device for detecting abnormality of ground measurement temperature data. The method obtains the respective water profile temperature data of multiple waypoints in a target water body area; wherein, the water profile temperature data Including the respective temperature values of the multi-layer depth layers, the multi-layer depth layers are obtained by dividing the measured water depths of the corresponding waypoints based on the layered water depth; multiple temperature value differences are obtained; wherein, the multiple temperature value differences include multiple waypoints The difference between the temperature values of the two depth layers at the bottom of the point, or the difference between the temperature values of the two adjacent depth layers corresponding to multiple target waypoints, and the target waypoint exists in multiple waypoints. Waypoints of temperature values corresponding to two adjacent depth layers; based on multiple temperature value differences, determine the abnormal difference among the multiple temperature value differences; determine the abnormal temperature according to the temperature value of the target waypoint corresponding to the abnormal difference value. To sum up, through the technical solution of the present invention, the accuracy and objectivity of the temperature data of on-site monitoring can be improved, and accurate and effective data support can be provided for water body thermal pollution management and water environment supervision.

Further effects of the above-mentioned non-conventional preferred mode will be described below in conjunction with specific embodiments.

Description of drawings

In order to illustrate the embodiments of the present invention or the existing technical solutions more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the existing technology. Obviously, the accompanying drawings in the following description are only the For some embodiments described in the invention, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

1 is a schematic diagram of temperature measurement data provided by an embodiment of the present invention;

2 is a schematic diagram of temperature gradient data of adjacent depth layers provided by an embodiment of the present invention;

3 is a schematic diagram of an abnormal temperature value provided by an embodiment of the present invention;

4 is a schematic flowchart of a method for detecting anomalies in ground measurement temperature data provided by an embodiment of the present invention;

5 is a schematic structural diagram of a device for detecting abnormality in ground measurement temperature data provided by an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

First, the practical application of the method provided by the embodiment of the present invention is described.

(1) Experiment design and seawater temperature data collection

First, select the study area (the sea area near the power plant); secondly, design test waypoints within the study area, and the design waypoints are gradually distributed from dense to sparse outward from the center of the nuclear power plant, and it is necessary to avoid land and islands, so as not to interfere with them. The measured temperature value has an impact; finally, a temperature acquisition instrument, such as a temperature and salt depth instrument CTD (Conductivity-Temperature-Depth) or a temperature and depth instrument TD (Temperature-Depth), is used to collect seawater temperature data.

(2) Time series temperature processing

Since the instrument goes into the water first and then out of the water during the measurement process, the depth data at each waypoint presents a periodic phenomenon from shallow to deep and then from deep to shallow. As shown in Figure 1, during the measurement process, the temperature and depth change with time in 5 cycles, corresponding to the 5 waypoints measured, so the depth increases from 0.02m and then returns to 0.02m again, which is the cycle for the instrument to measure a waypoint. The corresponding temperature value in each cycle is the measured temperature sequence at the corresponding waypoint.

Through the analysis of the rules in the figure, the measurement depth of the instrument just entering the water and just exiting the water is the sea level height. The recorded value of the instrument is 0.02m, and the real value should be 0m. Here, 0.02m is caused by the difference between the actual atmospheric pressure and the standard atmospheric pressure. This error is corrected to obtain the true depth of water penetration of the instrument.

The water entry depth is corrected by the following formula (1):

h _ar = h _br -h _sea (1)

In the formula, h _ar represents the water entry depth of the instrument after calibration, h _br represents the water entry depth before the instrument is calibrated, and h _sea represents the depth value recorded when the instrument is placed at sea level.

Further, set the layered water depth to 0.5, that is, set a depth layer every 0.5m, and extract and calculate the temperature value of the depth layer of each waypoint. Specifically, the temperature value of the depth layer h _i of the waypoint can be calculated by the following formula (2):

表示深度层h_i的温度值；h_i(i＝0.5，1.0，1.5，…)表示深度层，如h_0.5代表0-0.5m分层水深，h₁代表0.5-1.0m分层水深；

表示位于深度层h_i的第j个温度测量值；n表示位于深度层h_i的温度测量值的数量。in,

Indicates the temperature value of the depth layer hi; _hi ( _i =0.5, 1.0, 1.5, ...) represents the depth layer, such as h _0.5 represents 0-0.5m layered water depth, h ₁ represents 0.5-1.0m layered water depth;

represents the _jth temperature measurement at the depth layer hi; _n represents the number of temperature measurements at the depth layer hi.

The respective temperature values of the multi-layer depth layers of the waypoint are used as the water profile temperature data.

Secondly, calculate the difference between the temperature values of two adjacent depth layers, and obtain the temperature gradient map of adjacent depth layers as shown in Figure 2 (corresponding to 4 waypoints, so each adjacent depth layer has 4 points , each point corresponds to a waypoint). Specifically, the difference between the temperature values can be calculated by the following formula (3):

ΔT _{(i, i+0.5)} =T _h(i+0.5) -T _hi (3)

Among them, ΔT _{(i, i+0.5)} represents the temperature value difference between two adjacent depth layers; T _h(i+0.5) represents the temperature value of the next depth layer, that is, the temperature value of the depth layer h _i+0.5 ; T _hi represents the temperature value of the previous depth layer, that is, the temperature value of the depth layer _hi .

Select the representative water temperature profile data, take the layered water depth as the vertical axis and the temperature as the horizontal axis to make a vertical temperature profile, as shown in Figure 2, and analyze the changes in the water temperature profile data based on the calculated temperature difference between adjacent depth layers. feature, which summarizes abnormal data values into two types, namely:

Type 1: The data on the top layer is abnormal. The instrument is exposed to the sun, so the temperature of the top layer measured by the instrument when it enters the water is too high, which is abnormal;

Type 2: The underlying data is abnormal, and the underlying data measured by the instrument is too high due to the bottom of the instrument, and an abnormality occurs.

(2) The difference between the temperature values of the top layer and the bottom layer is calculated separately

Calculates the average value of the temperature difference between the two depth layers at the top of each of the multiple waypoints

Among them, m represents the number of waypoints; ΔT _ai represents the temperature value difference between the two depth layers of the top layer of the ith waypoint (i=1, 2, 3..., m).

Calculate the standard deviation T _aσ of the temperature value difference between the two depth layers at the top of each of the multiple waypoints:

Calculate the average value of the temperature value difference between the two depth layers of the respective bottom layers of multiple waypoints

Among them, m represents the number of waypoints; ΔT _i represents the temperature value difference between the two depth layers at the bottom of the i-th waypoint (i=1, 2, 3..., m).

Calculate the standard deviation T _bσ of the temperature value difference between the bottom two depth layers of each of the multiple waypoints:

Suppose the waypoint has a total of _y depth layers, h ₁ , h ₂ , , , hy _-1 , hy . Then h ₁ and h ₂ are the two depth layers of the top layer; h _y-1 and _hy are the two depth layers of the bottom layer.

(3) Identification and elimination of temperature outliers at the top and bottom layers

Calculate the Grubbs statistic g _ai of the temperature value difference ΔT _i of the top layer:

Calculate the Grubbs statistic g _{bi of the underlying temperature value difference ΔT bi :}

Then look up the Grubbs table to get the critical value G _(1-α) (m). Among them, α is the probability of causing a test error, and 1-α is the confidence probability P. It should be noted that the critical value G _(1-α) (m) is related to two parameters: α and the number of measurements m. For α: if the requirements are strict, α can be set smaller, for example, α=0.01, then the confidence probability P is 0.99; if the requirements are not strict, α can be set larger, for example, α=0.10, that is, the confidence probability P is 0.90; in the embodiment of the present invention, α=0.01, and P is 0.99. The critical value obtained by the Chagrubs table: according to the selected confidence probability P (here is 0.99) and the number of measurements m (determined in combination with the actual demand), the Chagrubs table, the horizontal and vertical intersections obtain the critical value G _(1-α) (m).

Outlier judgment:

When g _ai ≥ G _(1-α) (m), ΔT _ai is an abnormal value, in other words, the temperature value T _h1 of the depth layer of the top layer is an abnormal temperature value.

When g _bi ≥ G _(1-α) (m), ΔT _bi is an abnormal value, in other words, the temperature value T _hy of the depth layer of the bottom layer is an abnormal temperature value.

The gray circles in Figure 2 are the temperature differences between adjacent layers in the ground test, the white triangle points are the extracted abnormal differences in the top layer, and the black triangle points are the abnormal differences in the bottom layer. Abnormal temperature values can be extracted. The white triangle point is the abnormal temperature of the top layer caused by the exposure of the instrument, and the black triangle point is the abnormal temperature of the bottom layer caused by the bottom of the instrument.

It should be understood that for other two adjacent depth layers, abnormal temperature value identification can also be performed in the above manner. Considering that the water depths of different waypoints are different, therefore, not every waypoint will have the same temperature values of two adjacent depth layers. In practical applications, only waypoints with temperature values will be considered.

As shown in FIG. 4 , a method for detecting abnormality of ground measurement temperature data provided by an embodiment of the present invention is provided. The method provided by the embodiment of the present invention can be applied to an electronic device, and specifically can be applied to a server or a general computer, and the electronic device is used as the execution body for description below. In this embodiment, the method specifically includes the following steps:

As shown in FIG. 4 , an embodiment of the present invention provides a method for detecting anomalies in ground-measured temperature data, including the following steps:

Step 401: Acquire the respective water profile temperature data of multiple waypoints in the target water body area; wherein, the water profile temperature data includes the respective temperature values of the multi-layer depth layers, and the multi-layer depth layers are based on the measured water depths of the corresponding waypoints based on the layered water depths. Obtained by layering.

As a feasible implementation method, select a target water body area, for example, the sea area near the above-mentioned power plant, and design waypoints in the target water body area. The designed waypoints need to avoid land and islands, so as not to affect the temperature measurement. In one example, the designed waypoints are gradually distributed from dense to sparse outward from the center point of the target water area. In an example, the target water area includes a nuclear power plant, and the designed waypoints are gradually distributed from dense to sparse outward from the nuclear power plant as the center.

As a feasible implementation, the water profile temperature data of the waypoint includes the respective temperature values of multiple depth layers. Specifically, the water profile temperature data of the waypoint can be determined by the following implementation methods:

Obtain the water temperature measurement data obtained by measuring the water body temperature at the waypoint, and the water temperature measurement data includes the temperature measurement values corresponding to each of the multiple water entry depth values, wherein the multiple water entry depth values are all corrected water entry depth values, and a plurality of The maximum value of the water entry depth value is the measured water depth; the measured water depth is layered based on the preset layered water depth to determine the multi-layer depth layer; for each layer in the multi-layer depth layer, the multi-layer water depth values belonging to the depth layer are determined. The respective temperature measurements are weighted and averaged to determine the depth layer temperature value.

First, for each waypoint among the multiple waypoints, the temperature acquisition instrument is used to collect the temperature data of the water body profile of the waypoint, so as to determine the original water body temperature measurement data collected by the instrument. Wherein, the original water body temperature measurement data includes respective temperature measurement values of a plurality of water entry depth values.

In practical applications, the user inputs the original water profile temperature data to the electronic device, so that the electronic device obtains the original water profile temperature data of the waypoint.

The electronic device corrects the water entry depth value. The water entry depth value is corrected by the above formula (1).

Then, the electronic device acquires the set layered water depth, for example, 0.5m, which is described below by taking 0.5m as an example. It should be understood that 0.5m is only used as an example, and does not constitute a specific limitation.

For each of the multiple waypoints, the electronic device divides the measured water depth of the waypoint (the maximum value among the corrected water entry depths of the waypoint) based on the layered water depth to obtain multiple depth layers. For example, the layered water depth is 0.5, that is, every 0.5m is set as one depth layer. Based on the measured depth of the waypoint, that is, the corrected maximum water entry depth measured by the instrument, multiple depth layers are set, and the depth of each layer is extracted and calculated. The temperature value of the layer. Specifically, the temperature value of the depth layer hi is calculated by the above formula (2). For example, if the maximum water entry depth is an integer multiple of 0.5, such as 5 meters, the depth layer is 0.5, 1, 1.5, ..., 5; if the maximum water entry depth is not an integer multiple of 0.5, the depth layer is the maximum water entry depth. The depth layer is the end. For example, if the maximum water entry depth is 4.2, the depth layer is 0.5, 1, 1.5, ..., 4.5.

It should be understood that the layered water depths of the multiple depth layers of the same waypoint are the same, and the layered water depths of the depth layers of different waypoints are also the same.

Step 402: Obtain a plurality of temperature value differences; wherein, the plurality of temperature value differences include the difference between the temperature values of the bottom two depth layers of each of the multiple waypoints, and the top layer of each of the multiple waypoints. The difference between the temperature values of the two depth layers, or the difference between the temperature values of multiple target waypoints corresponding to the same two adjacent depth layers, the target waypoint is that there are two adjacent layers in the multiple waypoints. The waypoint for the temperature value corresponding to the depth layer.

In one example, the plurality of temperature value differences consists of the difference between the temperature values of the two depth layers of the respective top layers of all the waypoints. Correspondingly, the electronic device acquires the difference between the temperature values of the two depth layers on the top layer of all the waypoints, so as to obtain a plurality of temperature value differences. For example, each waypoint corresponds to a temperature value difference.

In one example, the plurality of temperature value differences consists of the difference values of the temperature values of the respective bottom two depth layers of all the waypoints. Correspondingly, the electronic device obtains the difference between the temperature values of the bottom two depth layers of all the waypoints, so as to obtain a plurality of temperature value differences. For example, each waypoint corresponds to a temperature value difference.

In one example, the plurality of temperature value differences include differences between the temperature values of the plurality of target waypoints corresponding to the same two adjacent depth layers. Wherein, the multiple depth layers of the target waypoint include the two adjacent depth layers. Correspondingly, the electronic device obtains the difference between the temperature values of the same two adjacent depth layers corresponding to each target waypoint, so as to obtain a plurality of temperature value differences. It should be understood that two adjacent depth layers may be [T _h(i-Δh) , T _hi ]. Among them, Δh represents the layered water depth corresponding to the depth layer, and the layered water depth corresponding to each depth layer is the same, for example, Δh can be 0.5 meters. It should be noted that, since the water depth of each waypoint may be different, not all the waypoints are target waypoints, in other words, the number of target waypoints in different adjacent two depth layers may be different. In some possible cases, the layered water depths of the multiple depth layers of the same waypoint are the same, and the layered water depths of the depth layers of different waypoints are also the same, so the two adjacent depth layers can be the two depth layers of the top layer.

Step 403 , based on the plurality of temperature value differences, determine an abnormal difference among the plurality of temperature value differences.

The electronic device calculates an average value and a standard deviation of the plurality of temperature value differences; then, for each value of the plurality of temperature value differences, based on the average value of the plurality of temperature value differences, the standard deviation of the plurality of temperature value differences, The temperature value difference is determined as the Grubbs number of the temperature value difference; when the Grubbs number is greater than the Grubbs critical value, the temperature value difference is regarded as an abnormal difference. The Grubbs critical value is determined based on the number of differences between multiple temperature values and the confidence probability P Chagrubs table. For details, see the above, and I won't go into details this time.

Step 404: Determine the abnormal temperature value according to the temperature value of the target waypoint corresponding to the abnormal difference value.

In one example, the abnormal difference value is not the temperature value difference between the bottom two depth layers of the corresponding waypoint. The temperature value is taken as the abnormal temperature value. For example, if two adjacent depth layers are [T _h(i-Δh) , T _hi ], the temperature value corresponding to _Th(i-Δh) is abnormal.

It should be noted that the abnormal difference value is the temperature value difference between the two depth layers on the top layer of the corresponding waypoint, and the electronic device takes the temperature value of the depth layer on the top layer of the waypoint corresponding to the abnormal difference value as the abnormal temperature value. It should be understood that the abnormal temperature value is due to the exposure of the temperature acquisition instrument to the sun, which causes the temperature of the top layer measured by the instrument to be high when it enters the water, and an abnormality occurs. The top layer here is the top layer.

In one example, the abnormal difference value is the temperature value difference between the bottom two depth layers of the corresponding waypoint, and the electronic device takes the abnormal difference value as the temperature value of the bottom depth layer of the corresponding waypoint as the abnormal temperature value. It should be noted that the abnormal temperature value is the reason that the temperature acquisition instrument bottomed out, resulting in the measured bottom layer data being high and abnormal. The bottom layer here is the bottom layer.

Further, the abnormal temperature values in the water profile temperature data are deleted.

In practical applications, the abnormal temperature difference between the two depth layers of the top layer and the two depth layers of the bottom layer is usually detected, and the corresponding abnormal temperature value (data caused by exposure or bottoming of the measuring instrument) is found. Then, based on the deletion of the abnormal temperature value (data abnormality caused by the exposure of the measuring instrument or bottoming) of the respective water profile temperature data of the multiple waypoints, it is determined that the multiple target waypoints correspond to the same adjacent two. The difference in temperature values for the layer depth layer. Therefore, for any target waypoint, when two adjacent depth layers are the bottom two depth layers of the target waypoint, the temperature value difference corresponding to the target waypoint is not the difference between the temperature values of the bottom two depth layers. outliers in .

It can be known from the above technical solutions that the beneficial effects of the present embodiment are:

By considering the difference between multiple temperature values at the same two adjacent depth layers at different waypoints, abnormal data can be identified more accurately, and the accuracy and objectivity of the temperature data monitored on the spot can be improved. Provide accurate and effective data support for environmental supervision.

Based on the same concept as the method embodiment of the present invention, please refer to FIG. 5 , the embodiment of the present invention further provides an abnormal detection device for ground measurement temperature data, including:

The temperature data acquisition module 501 is used to acquire the water profile temperature data of each of the multiple waypoints in the target water body area; wherein, the water profile temperature data includes the respective temperature values of the multi-layer depth layers, and the multi-layer depth layers are based on the The layer water depth is obtained by layering the measured water depth of the corresponding waypoint;

A difference value obtaining module 502, configured to obtain a plurality of temperature value differences; wherein, the plurality of temperature value differences include the difference between the temperature values of the two depth layers at the bottom of each waypoint of the plurality of waypoints, The difference between the temperature values of the two depth layers on the top layer of each of the multiple waypoints, or the difference between the temperature values of the two adjacent depth layers corresponding to the multiple target waypoints, the target The waypoint is a waypoint in which there are temperature values corresponding to the two adjacent depth layers among the plurality of waypoints;

An abnormal value detection module 503, configured to determine an abnormal difference value among the plurality of temperature value differences based on the plurality of temperature value differences;

The abnormal value determination module 504 is configured to determine the abnormal temperature value according to the temperature value of the waypoint corresponding to the abnormal difference value.

As a feasible implementation manner, the abnormal value detection module 503 includes: a calculation unit and an abnormality detection unit; wherein,

the calculation unit, configured to calculate the average value of the plurality of temperature value differences, and calculate the standard deviation of the plurality of temperature value differences according to the average value of the plurality of temperature value differences;

The abnormality detection unit for each value of the plurality of temperature value differences based on the average value of the plurality of temperature value differences, the standard deviation of the plurality of temperature value differences, the temperature value The difference value is used to determine the Grubbs number; when the Grubbs number is greater than the critical value of Grubbs, the temperature value difference is regarded as an abnormal difference.

As a feasible implementation manner, the Grubbs critical value is determined based on the number of the plurality of temperature value differences and a confidence check Grubbs table.

As a feasible implementation manner, the plurality of temperature value differences include a difference between temperature values of two depth layers on the top layer of each of the plurality of waypoints, and the abnormal temperature value is the abnormal difference The value corresponds to the temperature value of the top-level depth layer of the waypoint.

As a feasible implementation manner, the plurality of temperature value differences include a difference value between the temperature values of two depth layers at the bottom of each of the plurality of waypoints, and the abnormal temperature value is the abnormal difference The value corresponds to the temperature value of the underlying depth layer of the waypoint.

As a feasible implementation manner, the multiple temperature value differences include the difference between the temperature values of multiple target waypoints corresponding to the same two adjacent depth layers; for any one of the target waypoints, when The same two adjacent depth layers are the bottom two depth layers of the target waypoint, and the difference between the temperature values of the target waypoint corresponding to the same two adjacent depth layers is not the multiple The abnormal difference in the difference between the temperature values of the two depth layers at the bottom of each waypoint.

FIG. 6 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. At the hardware level, the electronic device includes a processor 601 and a memory 602 storing execution instructions, and optionally an internal bus 603 and a network interface 604 . Wherein, the memory 602 may include a memory 6021, such as a high-speed random-access memory (Random-Access Memory, RAM), and may also include a non-volatile memory 6022 (non-volatile memory), such as at least one disk memory, etc.; the processor 601, the network interface 604 and the memory 602 can be connected to each other through an internal bus 603, and the internal bus 603 can be an ISA (Industry Standard Architecture, industry standard architecture) bus, a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or EISA (Extended Industry Standard Architecture, Extended Industry Standard Architecture) bus, etc.; the internal bus 603 can be divided into address bus, data bus, control bus, etc. For convenience, only one bidirectional arrow is used in FIG. 6, but it does not mean that there is only one Root bus or a type of bus. Of course, the electronic equipment may also include hardware required for other services. When the processor 601 executes the execution instructions stored in the memory 602, the processor 601 executes the method in any one of the embodiments of the present invention, and is at least configured to execute the method shown in FIG. 4 .

In a possible implementation manner, the processor reads the corresponding execution instructions from the non-volatile memory into the memory and then executes them, and also obtains the corresponding execution instructions from other devices, so as to form a logic level Anomaly detection device for ground measurement temperature data. The processor executes the execution instructions stored in the memory, so as to implement a method for detecting abnormality in ground measurement temperature data provided in any embodiment of the present invention through the executed execution instructions.

A processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above-mentioned method can be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software. The above-mentioned processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; it may also be a digital signal processor (Digital Signal Processor, DSP), dedicated integrated Circuit (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Various methods, steps, and logical block diagrams disclosed in the embodiments of the present invention can be implemented or executed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Embodiments of the present invention further provide a computer-readable storage medium, including execution instructions. When a processor of an electronic device executes the execution instructions, the processor executes the method provided in any one of the embodiments of the present invention. Specifically, the electronic device may be the electronic device shown in FIG. 6 ; the execution instruction is a computer program corresponding to a device for detecting abnormality of ground measurement temperature data.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method or a computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware.

Each embodiment of the present invention is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and reference may be made to some descriptions of the method embodiments for related parts.

It should also be noted that the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device comprising a series of elements includes not only those elements, but also Other elements not expressly listed, or which are inherent to such a process, method, article of manufacture, or apparatus are also included. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article of manufacture, or device that includes the element.

The above descriptions are merely embodiments of the present invention, and are not intended to limit the present invention. Various modifications and variations of the present invention are possible for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims (9)

1. a ground measurement temperature data abnormal detection method, is characterized in that, comprises: Obtain the water profile temperature data of multiple waypoints gradually distributed outward from the center of the target water body area from dense to sparse; wherein, the water profile temperature data includes the respective temperature values of the multi-layer depth layers, and the temperature values are determined by the multi-layer The depth layer is extracted and calculated, and the multi-layer depth layer is obtained by layering the measured water depth of the corresponding waypoint based on the layered water depth after the water entry depth correction; Obtain a plurality of temperature values and perform difference calculation to obtain a temperature value difference; wherein, the plurality of temperature value differences include the difference between the temperature values of the two depth layers at the bottom of each waypoint of the plurality of waypoints, the The difference between the temperature values of the two depth layers at the top of each of the multiple waypoints, or the difference between the temperature values of the two adjacent depth layers corresponding to the multiple target waypoints, the target navigation The point is a waypoint with temperature values corresponding to the two adjacent depth layers in the plurality of waypoints; Based on the plurality of temperature value differences, calculating a Grubbs statistic and a Grubbs critical value to determine an abnormal difference in the plurality of temperature value differences; The abnormal temperature value is determined according to the temperature value of the waypoint corresponding to the abnormal difference value. 2 . The method according to claim 1 , wherein the determining an abnormal difference among the plurality of temperature value differences based on the plurality of temperature value differences comprises: 2 . calculating the average value of the plurality of temperature value differences, and calculating the standard deviation of the plurality of temperature value differences according to the average value of the plurality of temperature value differences; For each of the plurality of temperature value differences, a Grubbs number is determined based on the average value of the plurality of temperature value differences, the standard deviation of the plurality of temperature value differences, and the temperature value difference ; When the Grubbs number is greater than the Grubbs critical value, the temperature value difference is regarded as an abnormal difference. 3 . The method of claim 2 , wherein the Grubbs critical value is determined based on the number of the plurality of temperature value differences and a confidence check Grubbs table. 4 . 4 . The method according to claim 1 , wherein the plurality of temperature value differences comprise the difference values of the temperature values of two depth layers on the top layer of each of the plurality of waypoints, and the abnormality The temperature value is the temperature value of the depth layer of the top layer of the waypoint corresponding to the abnormal difference value. 5 . The method according to claim 1 , wherein the plurality of temperature value difference values comprise the difference value between the temperature values of two depth layers at the bottom of each waypoint of the plurality of waypoints, and the abnormality The temperature value is the temperature value of the depth layer of the bottom layer of the waypoint corresponding to the abnormal difference value. 6. The method according to claim 1, wherein the plurality of temperature value differences comprises a plurality of target waypoints respectively corresponding to the difference between the temperature values of the same two adjacent depth layers; For any one of the target waypoints, when the same two adjacent depth layers are the bottom two depth layers of the target waypoint, the target waypoint corresponds to the same two adjacent depth layers. The difference of the temperature values is not an abnormal difference among the differences of the temperature values of the bottom two depth layers of each of the multiple waypoints. 7. An abnormality detection device for ground measurement temperature data, characterized in that, comprising: The temperature data acquisition module is used to acquire the respective water profile temperature data of a plurality of waypoints gradually distributed outward from the center of the target water body area from dense to sparse; wherein, the water profile temperature data includes the respective temperature values of the multi-layer depth layers, The temperature value is extracted and calculated from the multi-layer depth layer, and the multi-layer depth layer is obtained by layering the measured water depth of the corresponding waypoint based on the layered water depth after the water entry depth correction; A difference value acquisition module, which calculates the difference value of the obtained temperature value to obtain a temperature value difference value; wherein, the plurality of temperature value difference values include the temperature values of the bottom two depth layers of each waypoint of the plurality of waypoints The difference between the multiple waypoints, the difference between the temperature values of the two depth layers on the top layer of each of the multiple waypoints, or the difference between the temperature values of the multiple target waypoints corresponding to the same two adjacent depth layers , the target waypoint is a waypoint in which there are temperature values corresponding to the two adjacent depth layers in the plurality of waypoints; an abnormal value detection module, configured to calculate a Grubbs statistic and a Grubbs critical value based on the plurality of temperature value differences to determine an abnormal difference among the plurality of temperature value differences; The abnormal value determination module is configured to determine the abnormal temperature value according to the temperature value of the waypoint corresponding to the abnormal difference value. 8. A computer-readable storage medium comprising executable instructions that, when executed by a processor of an electronic device, cause the processor to perform the method of any one of claims 1 to 6. 9. An electronic device comprising a processor and a memory storing execution instructions, when the processor executes the execution instructions stored in the memory, the processor executes any one of claims 1 to 6. method described.

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