CN111898094B - Method and device for processing foundation pit monitoring data, electronic equipment and storage medium - Google Patents

Method and device for processing foundation pit monitoring data, electronic equipment and storage medium Download PDF

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CN111898094B
CN111898094B CN202010642035.0A CN202010642035A CN111898094B CN 111898094 B CN111898094 B CN 111898094B CN 202010642035 A CN202010642035 A CN 202010642035A CN 111898094 B CN111898094 B CN 111898094B
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黄文德
彭炎华
李彬
赵成铭
王鹏
黄利军
谭懿行
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Guangzhou Geohwa Survey Corp ltd
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Abstract

The invention discloses a method and a device for processing foundation pit monitoring data, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data; calculating a mean difference value of the first mean value and the second mean value; if the mean difference is larger than a first threshold value, respectively acquiring a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length; calculating a first difference value between the first historical mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value; and if the first difference and the second difference are both larger than a second threshold value, triggering an alarm. The embodiment of the application can improve the accuracy of alarming and reduce the false alarm rate.

Description

Method and device for processing foundation pit monitoring data, electronic equipment and storage medium
Technical Field
The embodiments of the present invention relate to a survey technology, and in particular, to a method and an apparatus for processing monitoring data, an electronic device, and a storage medium.
Background
The foundation pit is a soil pit excavated at the design position of the foundation according to the elevation of the foundation and the plane size of the foundation. In order to ensure the safety of the foundation pit, more and more sensors are applied to the safety monitoring of the foundation pit. The sensors can be collected continuously for 24 hours. However, false alarm caused by data fluctuation due to the influence of external conditions often occurs to the sensor, the alarm accuracy is low, and the false alarm rate is high.
Disclosure of Invention
The invention provides a method and a device for processing foundation pit monitoring data, electronic equipment and a storage medium, which are used for improving the alarm accuracy of a foundation pit sensor and reducing the false alarm rate.
In a first aspect, an embodiment of the present invention provides a method for processing foundation pit monitoring data, including:
determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data;
calculating a mean difference value of the first mean value and the second mean value;
if the mean difference is larger than a first threshold value, respectively acquiring a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length;
calculating a first difference value between the first historical mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value;
and if the first difference and the second difference are both larger than a second threshold value, triggering an alarm.
In a second aspect, an embodiment of the present invention further provides a device for processing foundation pit monitoring data, including:
the mean value calculation module is used for determining a first mean value according to the length of the first window and the measurement data and determining a second mean value according to the length of the second window and the measurement data;
the difference value calculating module is used for calculating the difference value of the first mean value and the second mean value;
the historical mean value obtaining module is used for respectively obtaining a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length if the mean value difference value is larger than a first threshold value;
the history difference value calculating module is used for calculating a first difference value between the first history mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value;
and the alarm triggering module is used for triggering alarm if the first difference value and the second difference value are both greater than a second threshold value.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the method for processing the pit monitoring data according to the embodiment of the present application.
In a fourth aspect, the present invention further provides a storage medium containing computer executable instructions, which when executed by a computer processor, are configured to perform the method for processing foundation pit monitoring data according to the embodiment of the present application.
According to the method for processing the foundation pit monitoring data, the first window length and the second window length can be used for respectively obtaining the first average value and the second average value corresponding to the current measurement data; and when the difference value between the first mean value and the second mean value is greater than a first threshold value, respectively calculating a first difference value between the first mean value and the first historical mean value and a second difference value between the second mean value and the second historical mean value, and when the first difference value and the second difference value are both greater than a second threshold value, triggering an alarm. Compared with the prior art, the alarm is given out as long as the sensor detects the measurement data larger than the preset threshold value, and the alarm accuracy is low. In the embodiment of the application, the alarm is triggered only when the difference value between the first average value and the second average value is greater than the first threshold value and the first difference value and the second difference value are both greater than the second threshold value. The difference value between the first mean value and the second mean value is larger than the first threshold value, which indicates that the mean values measured by using different window lengths in the current measurement period have difference, and the difference value between the first difference value and the second difference value is larger than the second threshold value, which indicates that the data difference exists in comparison with the previous measurement period.
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Fig. 1 is an architecture diagram of a processing system for pit monitoring data according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for processing foundation pit monitoring data according to a first embodiment of the present invention;
fig. 3 is a flowchart of a method for processing foundation pit monitoring data according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a processing apparatus for foundation pit monitoring data according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
At present, the application of the foundation pit safety monitoring sensor is more and more extensive, and the automatic monitoring is more and more in mainstream application of the industry. The sensors can realize uninterrupted acquisition for 24 hours. The sensor has large data fluctuation due to the influence of the self precision and external conditions, the change rate of parameters such as horizontal displacement, vertical displacement, deep horizontal displacement, vertical displacement of a stand column, vertical displacement of the earth surface and the like on the top of a surrounding wall (side slope) is normal at the speed of 2-5 mm/d according to the technical standard for monitoring foundation pit engineering GB 50497 2019, and early warning is given when the change rate exceeds the value, so that false warning is often caused due to the data fluctuation caused by the influence of the external conditions. Taking the distance measuring instrument as an example, when the sensor is used in summer from 6 points to 18 points, the fluctuation of the measured data is +/-9 mm, and when the fluctuation of the measured data from 18 points to 6 points is +/-1.5 mm, the data changes periodically. The sensor is greatly influenced by the natural environment such as temperature, illumination intensity, rain fog, humidity, wind speed and the like, so that a method for processing foundation pit monitoring data is urgently needed to ensure the accuracy of alarming.
Fig. 1 is an architecture diagram of a processing system for foundation pit monitoring data according to an embodiment of the present application, where the system includes a sensor 1 and a server 2, and the sensor 1 may be a water level meter, an anchor cable meter, a static level, a laser range finder, or the like. The sensor 1 monitors the foundation pit site in real time and sends the measured data measured in real time to the server 2. A plurality of sensors 1 may be provided, and the plurality of sensors 1 respectively transmit measurement data to the server 2. The server 2 processes the measurement data transmitted by each sensor 1 in parallel processes.
Alternatively, the server 2 may be replaced by a mobile terminal having processing capability to perform the methods provided by the embodiments of the present application. At this time, the sensor 1 may transmit the measurement data to the mobile terminal through a wireless network, bluetooth, or the like. The following description will be given taking the server 2 device as an example. The server 2 determines a first average value according to the first window length and the measurement data, and determines a second average value according to the second window length and the measurement data; calculating a mean difference value of the first mean value and the second mean value; if the mean difference is larger than a first threshold value, respectively acquiring a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length; calculating a first difference value between the first historical mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value; and if the first difference and the second difference are both larger than a second threshold value, triggering an alarm. The alarm can be that the server 2 sends an alarm instruction to the sensor 1, and the sensor 1 performs alarm operation after receiving the alarm instruction. The alarm may also be that the server 2 sends alarm information to the user terminal, and the user terminal performs alarm feedback after receiving the alarm information, for example, playing an alarm sound, pushing the alarm information for the user, and the like. The following describes a processing scheme of the pit monitoring data executed by the server.
Example one
Fig. 2 is a flowchart of a method for processing foundation pit monitoring data according to an embodiment of the present application, where the method is applicable to a case where foundation pit measurement data is processed, and the method may be executed by a server, and the method includes:
step 110, determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data.
The first window length and the second window length are given values. The setting can be manually set by a programmer or can be determined according to historical measurement data of the foundation pit currently measured. The specific manner of determining the current measurement data of the foundation pit according to the historical measurement data is specifically described in the following embodiment two.
Before determining the first mean value according to the first window length and the measurement data in step 110, the method further includes: and receiving measurement data sent by the sensor, wherein the measurement data is the internal distance data of the foundation pit, which is acquired by the sensor according to the preset frequency.
And if the execution main body is a server, receiving the measurement data uploaded by the sensor through a wireless network. The measurement data is real-time measurement data of the sensor.
The measurement data may be represented by: { (t1, y1), (t2, y2), …, (ti, yi), …, (tn, yn) }, wherein i ═ 1,2, …, n, i denote the measurement period, and n is the measurement data corresponding to the current measurement period. Each measurement cycle is measured to obtain a group (ti, yi), where ti represents the time corresponding to the measurement cycle i, and yi represents the value of the measurement data measured in the measurement cycle i.
Optionally, taking an average value of the measurement data corresponding to the first window length of the current period as a first average value; and taking the average value of the measurement data corresponding to the second window length of the current period as a second average value.
The unit lengths of the first window length and the second window length correspond to one measurement period. For example, if the first window length is 3, the measurement data acquired in the current period and the average value of the measurement data acquired in the first two measurement periods of the current period are taken as the first average value. Thus, each time the measurement period is refreshed, the server receives new measurement data (tn, yn).
The first mean value calculation method may be: and starting from the measurement data acquired in the current period, acquiring a plurality of historical measurement data forwards, wherein the acquired historical measurement data is obtained by subtracting one from the length of the first window. And taking the arithmetic mean value of a plurality of historical measurement data obtained at the beginning of the measurement data obtained in the current period and the obtained data as a first mean value. Further, if the number of the historical measurement data before the current measurement period is smaller than the length of the first window minus one, the historical measurement data of all the measurement periods before the current period are obtained, and the arithmetic mean value of the measurement data of the current period and the obtained historical measurement data is used as a first mean value. A second average value may be obtained in the same way.
Further, the first window length and the second window length are odd;
correspondingly, the average value of the measurement data corresponding to the first window length of the current period is taken as a first average value, and the method comprises the following steps: taking a central point corresponding to the first window length of the current period as first reference measurement data; respectively acquiring a preset number of first measurement data before the first reference measurement data and a preset number of second measurement data after the first reference measurement data, wherein the preset number is an integer half of the length of the first window; and taking the mean value of the reference measurement data, the first measurement data and the second measurement data as a first mean value.
When the first window length is odd, the first reference measurement data may be determined among the plurality of measurement data for one window length. The first reference measurement data is measurement data corresponding to a middle point of the first window length. Assuming that the first window length is 5, the first reference measurement length is the third measurement data.
For example, taking m measurement data of the first window length in succession may be regarded as a circular queue. The length of the queue is fixed to m, and after a new measurement data (measurement data of the current period) is sampled each time, the new measurement data is put into the tail of the queue, and a data at the head of the original queue is thrown away (first-in first-out principle). For example, after receiving new measurement data every measurement period, the new measurement data is inserted into the circular queue, and the average value of the circular queue is taken as the first average value.
Assuming that the first window length m is odd, the first mean value is YiRepresenting a first mean value, y, corresponding to the measurement period iiRepresenting the measurement data measured in the measurement period i, a first average value corresponding to each first window length can be calculated by the following formula:
Figure BDA0002571504020000071
wherein the content of the first and second substances,
Figure BDA0002571504020000072
illustratively, m-5, i-4
Figure BDA0002571504020000073
Figure BDA0002571504020000074
Wherein the predetermined number is an integer of one-half of the length of the first window, e.g.
Figure BDA0002571504020000075
The first measurement data is y2、y3The second measurement data is y5、y6。
The data after fitting by using the fitting function has better continuity, and the influence of local fluctuation on the whole trend is avoided. In addition, the fitted data in different time periods are subjected to trend comparison, and data with the same trend and data with obviously different trends can be found out.
It should be noted that, in the above embodiment, the output first average value is output based on the first reference measurement data, and the first reference measurement data is the historical measurement data corresponding to the middle point of the first window length. The alarm issued on the basis of the first mean value has a certain lag compared to the data measured for the current measurement period, and does not hinder real-time performance since the lag is only in the measurement period of priority. Meanwhile, whether the first reference measurement data is a surge measurement value or not can be judged more accurately by using the preset number of second measurement data after the first reference measurement data.
Correspondingly, the average value of the measurement data corresponding to the second window length of the current period is used as a second average value, and the method includes: taking a central point corresponding to the length of a second window of the current period as second reference measurement data; respectively acquiring a preset number of third measurement data before the second reference measurement data and a preset number of fourth measurement data after the second reference measurement data, wherein the preset number is an integer half of the length of the second window; and taking the mean value of the reference measurement data, the third measurement data and the fourth measurement data as a second mean value.
The calculation process of the second average value is the same as that of the first average value, except for the second window length used, and the second reference measurement data, the third measurement data and the fourth measurement data corresponding to the second window length. The calculation process of the first average value may be used, in which the first window length is replaced by the second window length, the first reference measurement data is replaced by the second reference measurement data, the first measurement data is replaced by the third measurement data, and the second measurement data is replaced by the fourth measurement data.
And step 120, calculating a mean difference value of the first mean value and the second mean value.
And calculating the difference value of the first average value and the second average value, and taking the difference value as the average value difference value.
Step 130, if the difference value of the mean values is greater than the first threshold, respectively obtaining a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length.
And storing the key value pair of the mean value and the response window length into a mean value sequence corresponding to the window length every time a mean value is obtained by calculation. For example, { (m)1,Y11)，(m1,Y21)，...,(m1,Yi1)，...,(m1,Yn1) Denotes the mean sequence for the first window length m 1. Where Y11 represents a first average of the first measurement cycle using the first window length m 1. The first historical mean value can be accurately inquired according to the mean value sequence. The second historical mean value can be obtained in the same way.
Step 140, calculating a first difference value between the first historical average value and the first average value; a second difference between the second historical average and the second average is calculated.
A first difference and a second difference are calculated, respectively. And taking the difference value of the first historical mean value and the first mean value as a first difference value. And taking the difference value of the second historical average value and the second average value as a second difference value.
And 150, if the first difference value and the second difference value are both larger than a second threshold value, triggering an alarm.
And if the absolute value of the first difference is larger than the second threshold value and the absolute value of the second difference is larger than the second threshold value, triggering an alarm.
The smaller the average difference value is, the closer the average value Y under different window length m values is to the real-time measurement data Y, and the data error of the distance meter sensor caused by natural conditions can be filtered. Two different window lengths m avoid data distortion and data timeliness caused by the fact that one m value is in fact in the early warning condition of the distance meter. Taking two different window lengths m, on the other hand, for comparison of subsequent measurement data, when the mean difference value of the two window lengths m becomes large, the range finder data starts to generate real early warning. And when the difference value of the mean difference values is higher than a first threshold value, recording the mean Y value of the next two windows with the length m. And subtracting the corresponding Yi value in the previous period from the two Yi values, and alarming the data when the corresponding Yi value exceeds a second threshold value specified under the building foundation pit engineering monitoring technical standard.
According to the method for processing the foundation pit monitoring data, the first window length and the second window length can be used for respectively obtaining the first average value and the second average value corresponding to the current measurement data; and when the difference value between the first mean value and the second mean value is greater than a first threshold value, respectively calculating a first difference value between the first mean value and the first historical mean value and a second difference value between the second mean value and the second historical mean value, and when the first difference value and the second difference value are both greater than a second threshold value, triggering an alarm. Compared with the prior art, the alarm is given out as long as the sensor detects the measurement data larger than the preset threshold value, and the alarm accuracy is low. In the embodiment of the application, the alarm is triggered only when the difference value between the first average value and the second average value is greater than the first threshold value and the first difference value and the second difference value are both greater than the second threshold value. The difference value between the first mean value and the second mean value is larger than the first threshold value, which indicates that the mean values measured by using different window lengths in the current measurement period have difference, and the difference value between the first difference value and the second difference value is larger than the second threshold value, which indicates that the data difference exists in comparison with the previous measurement period.
Example two
Fig. 3 is a flowchart of a method for processing foundation pit monitoring data according to a second embodiment of the present application, as a further description of the foregoing embodiment, in step 110, before determining a first average value according to a first window length and measurement data, the method further includes:
step 210, obtaining historical measurement data.
The historical data may be all measured data within a preset time period. For example, 7 days of continuous measurement data are used as the historical measurement data.
Step 220, determining a plurality of mean value sequences corresponding to the lengths of the windows to be measured according to the lengths of the windows to be measured and historical measurement data.
And setting the lengths of a plurality of windows to be tested. And respectively obtaining corresponding measurement data in the historical measurement data by using the length of each window to be measured to obtain an average value sequence. And obtaining a mean value sequence for each length of the window to be measured. The mean value may be calculated in the same manner as described above with respect to the first mean value. Since each measurement cycle results in a mean value, the number of mean values included in the plurality of mean value sequences is the same.
A reference sequence and a plurality of other sequences are determined 230 based on the plurality of mean sequences.
One sequence is randomly selected from the plurality of mean sequences as a reference sequence. The sequences of the plurality of mean sequences other than the reference sequence are other sequences.
And step 240, obtaining a plurality of difference value sequences corresponding to other sequences according to the reference sequence and the other sequences.
The means in the other sequences are subtracted from the means in the reference sequence, respectively. And during subtraction, subtracting one energy according to each measurement period to obtain a difference value sequence. Each measurement period in the difference sequence corresponds to a difference, and the difference is the difference of the mean values corresponding to the periods in the other sequences and the reference sequence. Optionally, the difference sequence is a sequence of absolute differences. Since there may be negative numbers in the subtraction process, in order to accurately represent the difference, the absolute value of the difference is taken and written into the difference sequence.
Step 250, respectively calculating the sum of the difference values in each difference value sequence.
The sum of the differences in each difference sequence is calculated separately.
And step 260, acquiring two difference value sequences with the minimum sum of the difference values.
And after counting the sum of the differences of the difference sequences, determining two difference sequences with the minimum sum of the differences.
And 270, determining the lengths of the windows to be measured corresponding to the two difference sequences as a first window length and a second window length.
In some implementations, the two difference sequences with the smallest sum of differences correspond to two window lengths that are numerically adjacent. At this time, the lengths of the two windows are too similar, and the disadvantage of similar test using one window length is easy to occur. Therefore, further, after obtaining the two difference sequences with the minimum sum of the differences at step 260, the method further includes: and judging whether the lengths of the windows to be detected corresponding to the two difference value sequences are adjacent integers or not.
Step 270, determining the lengths of the windows to be measured corresponding to the two difference sequences as a first window length and a second window length, including: and if the difference value sequences are not adjacent integers, determining the lengths of the windows to be measured corresponding to the two difference value sequences as a first window length and a second window length.
And if the first window length and the second window length are not adjacent integers, determining the lengths of the windows to be measured corresponding to the two difference sequences as the first window length and the second window length.
According to the method for processing the foundation pit monitoring data, the first window length and the second window length can be selected to be proper for the foundation pit by analyzing the historical measurement data of the foundation pit. The problem of inaccurate setting when manual setting is carried out according to experience is avoided, and the alarm accuracy is further improved.
EXAMPLE III
Fig. 4 is a schematic structural diagram of a device for processing foundation pit monitoring data according to an embodiment of the present application, where the device is suitable for a situation where foundation pit measurement data is processed, and the device may be executed by a server, and includes: a mean value calculation module 41, a difference value calculation module 42, a historical mean value acquisition module 43, a historical difference value calculation module 44, and an alarm triggering module 45.
A mean value calculating module 41, configured to determine a first mean value according to the first window length and the measurement data, and determine a second mean value according to the second window length and the measurement data;
a difference calculation module 42, configured to calculate a difference between the first average and the second average;
a historical mean value obtaining module 43, configured to obtain a first historical mean value of a previous cycle corresponding to the first window length and a second historical mean value of a previous cycle corresponding to the second window length, respectively, if the mean value difference value is greater than the first threshold;
a history difference calculation module 44, configured to calculate a first difference between the first history mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value;
and an alarm triggering module 45, configured to trigger an alarm if both the first difference and the second difference are greater than a second threshold.
Further, the mean calculation module 41 is configured to:
taking the average value of the measurement data corresponding to the first window length of the current period as a first average value;
and taking the average value of the measurement data corresponding to the second window length of the current period as a second average value.
Further, the first window length and the second window length are odd; the mean calculation module 41 is used for
Taking a central point corresponding to the first window length of the current period as first reference measurement data; respectively acquiring a preset number of first measurement data before the first reference measurement data and a preset number of second measurement data after the first reference measurement data, wherein the preset number is an integer half of the length of the first window;
taking the mean value of the reference measurement data, the first measurement data and the second measurement data as a first mean value;
taking a central point corresponding to the length of a second window of the current period as second reference measurement data; respectively acquiring a preset number of third measurement data before the second reference measurement data and a preset number of fourth measurement data after the second reference measurement data, wherein the preset number is an integer half of the length of the second window;
and taking the mean value of the reference measurement data, the third measurement data and the fourth measurement data as a second mean value.
Further, the system further comprises a window length determining module, configured to:
acquiring historical measurement data;
determining a plurality of mean value sequences corresponding to the lengths of the windows to be measured according to the lengths of the windows to be measured and historical measurement data;
determining a reference sequence and a plurality of other sequences according to the plurality of mean sequences;
obtaining difference value sequences corresponding to a plurality of other sequences according to the reference sequence and the other sequences;
respectively calculating the sum of the difference values in each difference value sequence;
obtaining two difference value sequences with the minimum sum of the difference values;
and determining the lengths of the windows to be detected corresponding to the two difference sequences as a first window length and a second window length.
Further, the difference sequence is a sequence of absolute differences.
Further, the window length determination module is configured to:
judging whether the lengths of the windows to be detected corresponding to the two difference sequences are adjacent integers or not;
and if the difference value sequences are not adjacent integers, determining the lengths of the windows to be measured corresponding to the two difference value sequences as a first window length and a second window length.
The system further comprises a receiving module for receiving the measurement data sent by the sensor, wherein the measurement data is the internal distance data of the foundation pit, which is obtained by the sensor according to the preset frequency.
The processing device for the foundation pit monitoring data provided by the embodiment of the application can respectively obtain a first average value and a second average value corresponding to the current measurement data by using the first window length and the second window length; and when the difference value between the first mean value and the second mean value is greater than a first threshold value, respectively calculating a first difference value between the first mean value and the first historical mean value and a second difference value between the second mean value and the second historical mean value, and when the first difference value and the second difference value are both greater than a second threshold value, triggering an alarm. Compared with the prior art, the alarm is given out as long as the sensor detects the measurement data larger than the preset threshold value, and the alarm accuracy is low. In the embodiment of the application, the alarm is triggered only when the difference value between the first average value and the second average value is greater than the first threshold value and the first difference value and the second difference value are both greater than the second threshold value. The difference value between the first mean value and the second mean value is larger than the first threshold value, which indicates that the mean values measured by using different window lengths in the current measurement period have difference, and the difference value between the first difference value and the second difference value is larger than the second threshold value, which indicates that the data difference exists in comparison with the previous measurement period.
The processing device for the foundation pit monitoring data provided by the embodiment of the invention can execute the processing method for the foundation pit monitoring data provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention, as shown in fig. 5, the electronic device includes a processor 50, a memory 51, an input device 52, and an output device 53; the number of the processors 50 in the electronic device may be one or more, and one processor 50 is taken as an example in fig. 5; the processor 50, the memory 51, the input device 52 and the output device 53 in the electronic apparatus may be connected by a bus or other means, and the bus connection is exemplified in fig. 5.
The memory 51 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the processing method of the pit monitoring data in the embodiment of the present invention (for example, the mean value calculating module 41, the difference value calculating module 42, the historical mean value acquiring module 43, the historical difference value calculating module 44, and the alarm triggering module 45 in the processing device of the pit monitoring data). The processor 50 executes various functional applications and data processing of the electronic device by running software programs, instructions and modules stored in the memory 51, that is, the processing method of the pit monitoring data is realized.
The memory 51 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 51 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 51 may further include memory located remotely from the processor 50, which may be connected to the electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 52 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function controls of the electronic apparatus. The output device 53 may include a display device such as a display screen.
EXAMPLE six
The sixth embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the computer-executable instructions are executed by a computer processor to perform a processing method for monitoring data of a foundation pit, and the method includes:
determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data;
calculating a mean difference value of the first mean value and the second mean value;
if the mean difference is larger than a first threshold value, respectively acquiring a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length;
calculating a first difference value between the first historical mean value and the first mean value; calculating a second difference value between the second historical mean value and the second mean value;
and if the first difference and the second difference are both larger than a second threshold value, triggering an alarm.
Further, determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data includes:
taking the average value of the measurement data corresponding to the first window length of the current period as a first average value;
and taking the average value of the measurement data corresponding to the second window length of the current period as a second average value.
Further, the first window length and the second window length are odd;
correspondingly, the average value of the measurement data corresponding to the first window length of the current period is taken as a first average value, and the method comprises the following steps:
taking a central point corresponding to the first window length of the current period as first reference measurement data; respectively acquiring a preset number of first measurement data before the first reference measurement data and a preset number of second measurement data after the first reference measurement data, wherein the preset number is an integer half of the length of the first window;
taking the mean value of the reference measurement data, the first measurement data and the second measurement data as a first mean value;
correspondingly, the average value of the measurement data corresponding to the second window length of the current period is used as a second average value, and the method includes:
taking a central point corresponding to the length of a second window of the current period as second reference measurement data; respectively acquiring a preset number of third measurement data before the second reference measurement data and a preset number of fourth measurement data after the second reference measurement data, wherein the preset number is an integer half of the length of the second window;
and taking the mean value of the reference measurement data, the third measurement data and the fourth measurement data as a second mean value.
Further, before determining a first mean value according to the first window length and the measurement data, and determining a second mean value according to the second window length and the measurement data, the method further includes:
acquiring historical measurement data;
determining a plurality of mean value sequences corresponding to the lengths of the windows to be measured according to the lengths of the windows to be measured and historical measurement data;
determining a reference sequence and a plurality of other sequences according to the plurality of mean sequences;
obtaining difference value sequences corresponding to a plurality of other sequences according to the reference sequence and the other sequences;
respectively calculating the sum of the difference values in each difference value sequence;
obtaining two difference value sequences with the minimum sum of the difference values;
and determining the lengths of the windows to be detected corresponding to the two difference sequences as a first window length and a second window length.
Further, the difference sequence is a sequence of absolute differences.
Further, after obtaining the two difference sequences with the minimum sum of the differences, the method further includes:
judging whether the lengths of the windows to be detected corresponding to the two difference sequences are adjacent integers or not;
determining the lengths of the windows to be detected corresponding to the two difference sequences as a first window length and a second window length, including:
and if the difference value sequences are not adjacent integers, determining the lengths of the windows to be measured corresponding to the two difference value sequences as a first window length and a second window length.
Further, before determining the first mean value according to the first window length and the measurement data, the method further includes:
and receiving measurement data sent by the sensor, wherein the measurement data is the internal distance data of the foundation pit, which is acquired by the sensor according to the preset frequency.
Of course, the storage medium provided by the embodiment of the present invention includes computer-executable instructions, and the computer-executable instructions are not limited to the above method operations, and may also perform related operations in the method for processing the pit monitoring data provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the above search apparatus, each included unit and module are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (8)

1. A processing method of foundation pit monitoring data is characterized by comprising the following steps:
receiving measurement data sent by a sensor, wherein the measurement data are internal distance data of a foundation pit, which are acquired by the sensor according to a preset frequency;
taking the average value of the measurement data corresponding to the first window length of the current period as a first average value;
taking the average value of the measurement data corresponding to the second window length of the current period as a second average value;
calculating a mean difference value of the first mean value and the second mean value;
if the mean difference is larger than a first threshold, respectively acquiring a first historical mean value of a previous period corresponding to the first window length and a second historical mean value of a previous period corresponding to the second window length;
calculating a first difference value between the first historical mean value and the first mean value; calculating a second difference between the second historical mean and the second mean;
if the first difference value and the second difference value are both larger than a second threshold value, triggering an alarm;
the taking an average value of the measurement data corresponding to the first window length of the current period as a first average value includes:
inserting new measurement data received in the current period into a cyclic queue with the length of a first window, and taking the average value of the cyclic queue with the length of the first window as a first average value;
the taking an average value of the measurement data corresponding to the second window length of the current period as a second average value includes:
inserting new measurement data received in the current period into a cyclic queue with the length of a second window, and taking the average value of the cyclic queue with the length of the second window as a second average value;
the respectively obtaining a first historical average value of a previous period corresponding to the first window length and a second historical average value of a previous period corresponding to the second window length includes:
storing the first average value and the key value pair of the first window length into an average value sequence corresponding to the first window length, and inquiring a first historical average value according to the average value sequence corresponding to the first window length;
and storing the key value pairs of the second average value and the second window length into an average value sequence corresponding to the second window length, and inquiring a second historical average value according to the average value sequence corresponding to the second window length.
2. The method for processing the foundation pit monitoring data according to claim 1, wherein the first window length and the second window length are odd numbers;
correspondingly, the taking the average value of the measurement data corresponding to the first window length of the current period as the first average value includes:
taking a central point corresponding to the first window length of the current period as first reference measurement data; respectively acquiring a preset number of first measurement data before the first reference measurement data and a preset number of second measurement data after the first reference measurement data, wherein the preset number is an integer half of the length of the first window;
taking a mean value of the first reference measurement data, the first measurement data and the second measurement data as a first mean value;
correspondingly, the taking the average value of the measurement data corresponding to the second window length of the current period as the second average value includes:
taking a central point corresponding to the length of a second window of the current period as second reference measurement data; respectively acquiring a preset number of third measurement data before the second reference measurement data and a preset number of fourth measurement data after the second reference measurement data, wherein the preset number is an integer half of the length of the second window;
and taking the mean value of the second reference measurement data, the third measurement data and the fourth measurement data as a second mean value.
3. The method for processing the pit monitoring data according to claim 1, wherein before determining the first mean value according to the first window length and the measurement data, and before determining the second mean value according to the second window length and the measurement data, the method further comprises:
acquiring historical measurement data;
determining a plurality of mean value sequences corresponding to the lengths of the windows to be measured according to the lengths of the windows to be measured and the historical measurement data;
determining a reference sequence and a plurality of other sequences according to the plurality of mean sequences;
obtaining difference value sequences corresponding to the other sequences according to the reference sequence and the other sequences;
respectively calculating the sum of the difference values in each difference value sequence;
obtaining two difference value sequences with the minimum sum of the difference values;
and determining the lengths of the windows to be detected corresponding to the two difference sequences as a first window length and a second window length.
4. The method for processing the pit monitoring data according to claim 3, wherein the difference sequence is a sequence of absolute differences.
5. The method for processing the foundation pit monitoring data according to claim 3, wherein after obtaining the two difference sequences with the minimum sum of the differences, the method further comprises:
judging whether the lengths of the windows to be detected corresponding to the two difference sequences are adjacent integers or not;
determining the lengths of the windows to be detected corresponding to the two difference sequences as a first window length and a second window length, including:
and if the difference value sequences are not adjacent integers, determining the lengths of the windows to be measured corresponding to the two difference value sequences as a first window length and a second window length.
6. A processing apparatus of foundation ditch monitoring data, characterized by includes:
the receiving module is used for receiving measurement data sent by the sensor, and the measurement data is the internal distance data of the foundation pit, which is acquired by the sensor according to the preset frequency;
the average value calculation module is used for taking the average value of the measurement data corresponding to the first window length of the current period as a first average value; taking the average value of the measurement data corresponding to the second window length of the current period as a second average value;
a difference value calculating module, configured to calculate a difference value between the first average value and the second average value;
a historical mean value obtaining module, configured to respectively obtain a first historical mean value of a previous cycle corresponding to the first window length and a second historical mean value of a previous cycle corresponding to the second window length if the mean value difference value is greater than a first threshold;
a history difference value calculating module, configured to calculate a first difference value between the first history mean value and the first mean value; calculating a second difference between the second historical mean and the second mean;
the alarm triggering module is used for triggering an alarm if the first difference value and the second difference value are both greater than a second threshold value;
the mean value calculation module is also used for inserting new measurement data received in the current period into a circular queue with the length of a first window, and taking the mean value of the circular queue with the length of the first window as a first mean value; inserting new measurement data received in the current period into a cyclic queue with the length of a second window, and taking the average value of the cyclic queue with the length of the second window as a second average value;
the historical mean value obtaining module is further used for storing the first mean value and the key value pair of the first window length into a mean value sequence corresponding to the first window length, and inquiring a first historical mean value according to the mean value sequence corresponding to the first window length; and storing the key value pairs of the second average value and the second window length into an average value sequence corresponding to the second window length, and inquiring a second historical average value according to the average value sequence corresponding to the second window length.
7. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of processing pit monitoring data according to any one of claims 1-5.
8. A storage medium containing computer executable instructions for performing the method of processing pit monitoring data according to any one of claims 1-5 when executed by a computer processor.
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