CN116307534B - Engineering measurement data processing method based on cloud computing - Google Patents
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Abstract
The invention provides a cloud computing-based engineering measurement data processing method, which is characterized in that all engineering measurement devices are subjected to differentiated management through a cloud computing platform, engineering measurement data generated by the engineering measurement devices which normally execute measurement tasks are analyzed, and corresponding measurement site states are obtained; and selecting other engineering measurement equipment to replace the engineering measurement equipment which does not normally execute the measurement task, realizing continuous and stable measurement of the whole area range, improving the comprehensiveness and the persistence of the measurement data, and ensuring the early warning reliability of the engineering measurement of the whole area.
Description
Technical Field
The invention relates to the technical field of engineering data processing, in particular to an engineering measurement data processing method based on cloud computing.
Background
In engineering construction, engineering measuring equipment such as a total station or a laser range finder is used for measuring a construction area to obtain topography measuring data and the like of the construction area, so that a reliable basis is provided for engineering construction. In order to ensure smooth engineering construction, a plurality of engineering measurement devices are generally required to be distributed in a construction area, and each engineering measurement device can independently execute corresponding engineering measurement tasks. The engineering measurement equipment can inevitably fail in the working process, and the area range aimed by the engineering measurement equipment cannot be continuously and stably measured at the moment, so that the comprehensiveness and the persistence of measurement data are reduced.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides an engineering measurement data processing method based on cloud computing, which determines a data interaction mode of a cloud computing platform and engineering measurement equipment and judges whether to normally execute a measurement task based on a data stream from the engineering measurement equipment; analyzing engineering measurement data from engineering measurement equipment for normally executing the measurement tasks to obtain measurement results of the corresponding measurement tasks, and calibrating the measurement site states; executing other engineering measurement devices instead of the engineering measurement devices which do not normally execute the measurement tasks, and estimating the measurement site state of the engineering measurement devices based on the obtained measurement results; according to the states of all the measuring places, obtaining engineering quality results of the whole engineering measuring area and giving an alarm, distinguishing and managing all the engineering measuring equipment through a cloud computing platform, and analyzing engineering measuring data generated by the engineering measuring equipment which normally executes a measuring task to obtain corresponding measuring place states; and selecting other engineering measurement equipment to replace the engineering measurement equipment which does not normally execute the measurement task, realizing continuous and stable measurement of the whole area range, improving the comprehensiveness and the persistence of the measurement data, and ensuring the early warning reliability of the engineering measurement of the whole area.
The invention provides an engineering measurement data processing method based on cloud computing, which comprises the following steps:
step S1, determining a data interaction mode of a cloud computing platform and engineering measurement equipment based on the operation state of the engineering measurement equipment; judging whether the engineering measurement equipment normally executes a measurement task or not based on the data flow from the engineering measurement equipment in the current data interaction mode;
step S2, when the engineering measurement equipment normally executes a measurement task, analyzing engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain a measurement result of the corresponding measurement task; calibrating the measurement site state of the engineering measurement equipment based on the measurement result;
step S3, when the engineering measurement equipment does not normally execute the measurement task, indicating other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task through the cloud computing platform, and analyzing engineering measurement data from the other engineering measurement equipment to obtain a measurement result of the corresponding measurement task; estimating a measurement site state of the engineering measurement device based on the measurement result;
and S4, obtaining engineering quality results of the whole engineering measurement area based on the states of all measurement places, and carrying out engineering measurement early warning.
Further, in the step S1, determining a data interaction mode of the cloud computing platform and the engineering measurement device based on the operation state of the engineering measurement device includes:
sending an operation state acquisition instruction to engineering measurement equipment, and acquiring an operation log of the engineering measurement equipment;
analyzing and processing the operation log to obtain the frequency of generating engineering measurement data by the engineering measurement equipment and the average data quantity of each generation of the engineering measurement data, and taking the frequency and the average data quantity as the operation state;
based on the frequency and the data volume of generating engineering measurement data, the frequency of a data acquisition request sent to the engineering measurement equipment by a cloud computing platform and the data interaction channel bandwidth between the cloud computing platform and the engineering measurement equipment are determined.
Further, in the step S1, based on the data flow from the engineering measurement device in the current data interaction mode, determining whether the engineering measurement device normally performs the measurement task includes:
carrying out identification processing on engineering measurement data flow from the engineering measurement equipment in a current data interaction mode to obtain a data volume ratio corresponding to data of which the engineering measurement data flow contains data meeting a preset form condition;
if the data volume duty ratio is larger than or equal to a preset duty ratio threshold value, judging that the engineering measurement equipment normally executes a measurement task; otherwise, judging that the engineering measurement equipment does not normally execute the measurement task.
Further, in the step S2, when the engineering measurement device normally executes a measurement task, the cloud computing platform analyzes engineering measurement data from the engineering measurement device to obtain a measurement result of the corresponding measurement task, including:
when the engineering measurement equipment normally executes a measurement task, screening all engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain all engineering measurement data belonging to the same measurement task;
analyzing all engineering measurement data belonging to the same measurement task to obtain a geological structure measurement result of a measurement site of the corresponding measurement task; the geological structure measurement result comprises geological structure displacement amounts of the measurement site in different directions.
Further, in the step S2, calibrating the measurement site state of the engineering measurement device based on the measurement result includes:
obtaining the geological structure settlement and the geological structure inclination direction of the measurement site of the engineering measurement equipment based on the geological structure displacement of the measurement site in different directions;
and calibrating whether a measurement site of the engineering measurement equipment is in a geological safety state or not based on the geological structure settlement and the geological structure inclination direction.
Further, in the step S3, when the engineering measurement device does not normally execute the measurement task, the cloud computing platform instructs other engineering measurement devices to replace the engineering measurement device to execute the measurement task, and analyzes engineering measurement data from the other engineering measurement devices to obtain a measurement result of the corresponding measurement task, including:
when the engineering measurement equipment does not normally execute a measurement task, determining other engineering measurement equipment closest to the engineering measurement equipment through the cloud computing platform, and sending a measurement task instruction to the determined other engineering measurement equipment based on the measurement task currently executed by the engineering measurement equipment, so that the determined other engineering measurement equipment replaces the engineering measurement equipment to execute the measurement task;
analyzing all engineering measurement data from the determined other engineering measurement equipment about the measurement task instruction to obtain a geological structure measurement result of a measurement place corresponding to the determined other engineering measurement equipment; the geological structure measurement result comprises geological structure displacement amounts of measurement sites corresponding to the determined other engineering measurement equipment in different directions.
Further, in the step S3, when the engineering measurement device does not normally perform a measurement task, determining, by the cloud computing platform, another engineering measurement device closest to the engineering measurement device, and based on the measurement task currently performed by the engineering measurement device, sending a measurement task instruction to the determined other engineering measurement device, so that the determined other engineering measurement device replaces the engineering measurement device to perform the measurement task, including:
step S301, performing preliminary screening on a plurality of other engineering measurement devices according to the task amount of the measurement tasks historically executed by the plurality of other engineering measurement devices closest to the engineering measurement device and the completion condition by using the following formula (1), screening out a plurality of other engineering measurement devices with more execution tasks and higher success rate,
in the above formula (1), R (a) represents a preliminary screening control value of an a-th other engineering measurement device closest to the engineering measurement device; n (a) represents the number of measurement tasks which are totally executed by the a-th other engineering measurement equipment closest to the engineering measurement equipment up to the current moment; m (a) represents the total number of measurement tasks normally executed by the a-th other engineering measurement equipment closest to the engineering measurement equipment up to the current moment; a represents the total number of other engineering measurement devices closest to the engineering measurement device, wherein the closest distance is the other engineering measurement devices meeting a preset distance threshold;
if R (a) =1, screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
if R (a) =0, not screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
step S302, screening out the optimal other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task according to the distance between a plurality of other engineering measurement equipment with more execution tasks and higher success rate and the engineering measurement equipment and the task quantity of the measurement task currently executed by the plurality of other engineering measurement equipment with more execution tasks and higher success rate by using the following formula (2),
in the above formula (2), b 'represents that the optimal other engineering measurement device is the b' th other engineering measurement device originally screened in the step A1; s (b) represents the distance value between the b-th other engineering measurement equipment and the engineering measurement equipment which are primarily screened in the step S301; b represents the total number of other engineering measurement devices which are primarily screened in the step S301; d (b_t) represents the task amount of the measurement task currently performed by the b-th other engineering measurement device that was initially screened out in the above step S301;substituting B from a value of 1 to B into a bracket to obtain a maximum value in the bracket; />The value B is obtained when substituting B from the value 1 to the value B into the brackets to obtain the maximum value in the brackets;
step S303, utilizing the following formula (3), controlling the overhaul light state on the equipment according to the task quantity and the completion condition of the measurement task historically executed by the engineering measurement equipment which does not normally execute the measurement task,
in the above formula (3), Y represents a control value of an overhaul light state on the apparatus; m is m 0 (e) The number of the total normal execution of the measurement tasks after the engineering measurement equipment which does not normally execute the measurement tasks has historically executed the e-th measurement task is represented; n (N) 0 (e) Representing the total number of measurement tasks which are executed after the engineering measurement equipment which does not normally execute the measurement tasks historically executes the e-th measurement task; mu represents a preset threshold value of the normal execution rate, and if the normal execution rate exceeds three times and is smaller than or equal to mu, the device is requiredOverhauling; f []A function value of the judgment function is 1 if the expression in the brackets is established, and is 0 if the expression in the brackets is not established; k represents the total number of measurement tasks which are executed by the engineering measurement equipment which does not normally execute the measurement tasks until the current moment;
if Y=1, controlling the overhaul light on the equipment to be turned on, and reminding a worker of overhaul;
and if y=0, controlling the overhaul light on the equipment to be turned off, and not needing to overhaul.
Further, in the step S3, estimating a measurement site state of the engineering measurement apparatus based on the measurement result includes:
obtaining the geological structure settlement and the geological structure inclination direction of the determined measurement sites corresponding to other engineering measurement equipment based on the geological structure displacement of the determined measurement sites corresponding to other engineering measurement equipment in different directions;
estimating whether a measurement site of the engineering measurement device is in a geology safe state based on the geological structure settlement amount, the geological structure inclination direction and the relative positions between the engineering measurement device and the determined other engineering measurement devices.
Further, in the step S4, based on the states of all the measurement sites, an engineering quality result of the engineering measurement whole area is obtained, and engineering measurement early warning is performed, including:
and obtaining engineering quality problem areas of the engineering measurement whole area according to the distribution positions of all measurement sites which are not in the geological safety state, and generating engineering measurement early warning information about the area distribution range of the engineering quality problem areas.
Compared with the prior art, the engineering measurement data processing method based on cloud computing determines the data interaction mode of the cloud computing platform and engineering measurement equipment, and judges whether to normally execute a measurement task or not based on the data flow from the engineering measurement equipment; analyzing engineering measurement data from engineering measurement equipment for normally executing the measurement tasks to obtain measurement results of the corresponding measurement tasks, and calibrating the measurement site states; executing other engineering measurement devices instead of the engineering measurement devices which do not normally execute the measurement tasks, and estimating the measurement site state of the engineering measurement devices based on the obtained measurement results; according to the states of all the measuring places, obtaining engineering quality results of the whole engineering measuring area and giving an alarm, distinguishing and managing all the engineering measuring equipment through a cloud computing platform, and analyzing engineering measuring data generated by the engineering measuring equipment which normally executes a measuring task to obtain corresponding measuring place states; and selecting other engineering measurement equipment to replace the engineering measurement equipment which does not normally execute the measurement task, realizing continuous and stable measurement of the whole area range, improving the comprehensiveness and the persistence of the measurement data, and ensuring the early warning reliability of the engineering measurement of the whole area.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an engineering measurement data processing method based on cloud computing.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flow chart of a cloud computing-based engineering measurement data processing method according to an embodiment of the present invention is shown. The engineering measurement data processing method based on cloud computing comprises the following steps:
step S1, determining a data interaction mode of a cloud computing platform and engineering measurement equipment based on the operation state of the engineering measurement equipment; judging whether the engineering measurement equipment normally executes a measurement task or not based on the data flow from the engineering measurement equipment in the current data interaction mode;
step S2, when the engineering measurement equipment normally executes a measurement task, analyzing engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain a measurement result of the corresponding measurement task; calibrating the measurement site state of the engineering measurement equipment based on the measurement result;
step S3, when the engineering measurement equipment does not normally execute the measurement task, the cloud computing platform instructs other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task, and the engineering measurement data from the other engineering measurement equipment are analyzed to obtain a measurement result of the corresponding measurement task; estimating a measurement site state of the engineering measurement device based on the measurement result;
and S4, obtaining engineering quality results of the whole engineering measurement area based on the states of all measurement places, and carrying out engineering measurement early warning.
The beneficial effects of the technical scheme are as follows: the engineering measurement data processing method based on cloud computing determines a data interaction mode of a cloud computing platform and engineering measurement equipment, and judges whether to normally execute a measurement task or not based on a data stream from the engineering measurement equipment; analyzing engineering measurement data from engineering measurement equipment for normally executing the measurement tasks to obtain measurement results of the corresponding measurement tasks, and calibrating the measurement site states; executing other engineering measurement devices instead of the engineering measurement devices which do not normally execute the measurement tasks, and estimating the measurement site state of the engineering measurement devices based on the obtained measurement results; according to the states of all the measuring places, obtaining engineering quality results of the whole engineering measuring area and giving an alarm, distinguishing and managing all the engineering measuring equipment through a cloud computing platform, and analyzing engineering measuring data generated by the engineering measuring equipment which normally executes a measuring task to obtain corresponding measuring place states; and selecting other engineering measurement equipment to replace the engineering measurement equipment which does not normally execute the measurement task, realizing continuous and stable measurement of the whole area range, improving the comprehensiveness and the persistence of the measurement data, and ensuring the early warning reliability of the engineering measurement of the whole area.
Preferably, in the step S1, determining a data interaction mode of the cloud computing platform and the engineering measurement device based on the operation state of the engineering measurement device includes:
sending an operation state acquisition instruction to engineering measurement equipment, and acquiring an operation log of the engineering measurement equipment;
analyzing and processing the operation log to obtain the frequency of generating engineering measurement data by the engineering measurement equipment and the average data quantity of each generation of the engineering measurement data, and taking the frequency and the average data quantity as the operation state;
based on the frequency and the data volume of generating engineering measurement data, the frequency of sending a data acquisition request to the engineering measurement equipment by the cloud computing platform and the data interaction channel bandwidth between the cloud computing platform and the engineering measurement equipment are determined.
The beneficial effects of the technical scheme are as follows: engineering measurement equipment such as total stations or laser rangefinders synchronously generate operation logs during operation, wherein the operation logs comprise operation data generated during operation of the engineering measurement equipment, and the operation data can comprise, but are not limited to, communication record data between the engineering measurement equipment and a cloud computing platform and measurement data generated by the engineering measurement equipment executing measurement tasks. And carrying out data type and content identification processing on the running log to obtain the frequency of generating measurement data (namely the frequency of generating the measurement data in unit time) and the data bit quantity corresponding to each generation of engineering measurement data in the process of executing a measurement task by engineering measurement equipment, so that cloud computing can set the frequency of sending a data acquisition request to the engineering measurement equipment and the data interaction channel bandwidth between the engineering measurement equipment, wherein the frequency of sending the data acquisition request by a cloud computing platform is not lower than the frequency of generating the measurement data by the engineering measurement equipment, the fact that the measurement data generated by the engineering measurement equipment each time can be transmitted to the cloud computing platform is ensured, and the data interaction channel bandwidth is larger than the average data quantity of each generation of the engineering measurement data, and therefore the generated engineering measurement data can be completely and rapidly transmitted to the cloud computing platform.
Preferably, in the step S1, determining whether the engineering measurement device normally performs the measurement task based on the data flow from the engineering measurement device in the current data interaction mode includes:
carrying out identification processing on engineering measurement data flow from the engineering measurement equipment in the current data interaction mode to obtain a data volume ratio corresponding to data of which the engineering measurement data flow contains data meeting the preset form condition;
if the data volume duty ratio is larger than or equal to a preset duty ratio threshold value, judging that the engineering measurement equipment normally executes a measurement task; otherwise, judging that the engineering measurement equipment does not normally execute the measurement task.
The beneficial effects of the technical scheme are as follows: by the method, the engineering measurement data from the engineering measurement equipment is subjected to data content identification, and the data volume ratio of the data meeting the preset form condition in the engineering measurement data compared with the whole engineering measurement data is judged; wherein the data satisfying the preset form condition may be, but is not limited to, data in a specific format related to a type of equipment of the engineering measurement equipment. When the data volume duty ratio is larger than or equal to a preset duty ratio threshold value, the effective measurement data in the engineering measurement data is indicated to be the main data component, and at the moment, the engineering measurement equipment normally executes a measurement task. When the data volume duty ratio is smaller than a preset duty ratio threshold, the fact that the number of the messy code invalid data in the engineering measurement data is larger is indicated, and at the moment, the engineering measurement equipment does not normally execute the measurement task.
Preferably, in the step S2, when the engineering measurement device normally executes a measurement task, the cloud computing platform analyzes engineering measurement data from the engineering measurement device to obtain a measurement result of the corresponding measurement task, including:
when the engineering measurement equipment normally executes a measurement task, screening all engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain all engineering measurement data belonging to the same measurement task;
analyzing all engineering measurement data belonging to the same measurement task to obtain a geological structure measurement result of a measurement site of the corresponding measurement task; wherein the geologic structure measurement comprises an amount of geologic structure displacement of the measurement site occurring in different directions.
The beneficial effects of the technical scheme are as follows: by the mode, when the engineering measurement equipment normally executes the measurement task, engineering measurement data generated in the process of executing the measurement task are screened, and data frame header information corresponding to each engineering measurement data is determined, so that all engineering measurement data belonging to the same measurement task are screened. And analyzing all engineering measurement data belonging to the same measurement task, and determining the geological structure displacement change of the measurement site corresponding to the measurement task.
Preferably, in the step S2, calibrating the measurement site state of the engineering measurement device based on the measurement result includes:
obtaining the geological structure settlement and the geological structure inclination direction of the measurement site of the engineering measurement equipment based on the geological structure displacement of the measurement site in different directions;
and calibrating whether the measuring site of the engineering measuring equipment is in a geological safety state or not based on the settlement of the geological structure and the inclination direction of the geological structure.
The beneficial effects of the technical scheme are as follows: according to the method, the geological structure displacement of the measuring place in different directions is taken as a reference, and the geological structure settlement and the geological structure inclination direction of the measuring place are obtained through analysis, so that the geological structure displacement state of the measuring place can be quantitatively analyzed, and whether the measuring place is in a geological safety state or not can be accurately identified.
Preferably, in the step S3, when the engineering measurement device does not normally perform the measurement task, the cloud computing platform instructs other engineering measurement devices to replace the engineering measurement device to perform the measurement task, and analyzes engineering measurement data from the other engineering measurement devices to obtain measurement results of the corresponding measurement task, including:
when the engineering measurement equipment does not normally execute the measurement task, determining other engineering measurement equipment closest to the engineering measurement equipment through the cloud computing platform, and sending a measurement task instruction to the determined other engineering measurement equipment based on the measurement task currently executed by the engineering measurement equipment, so that the determined other engineering measurement equipment replaces the engineering measurement equipment to execute the measurement task;
analyzing all engineering measurement data of the determined other engineering measurement equipment about the measurement task instruction to obtain a geological structure measurement result of a measurement place corresponding to the determined other engineering measurement equipment; the geological structure measurement result comprises geological structure displacement amounts of measurement sites corresponding to other determined engineering measurement equipment in different directions.
The beneficial effects of the technical scheme are as follows: through the method, when the engineering measurement equipment does not normally execute the measurement task, all the engineering measurement equipment which is connected currently are screened through the cloud computing platform, and other engineering measurement equipment which is closest to the engineering measurement equipment is selected to replace the engineering measurement equipment to execute the corresponding measurement task, so that the situation of measurement missing of corresponding measurement sites is avoided, and continuous and comprehensive measurement of all the measurement sites in the whole area is ensured.
Preferably, in the step S3, when the engineering measurement device does not normally perform a measurement task, determining, by the cloud computing platform, another engineering measurement device closest to the engineering measurement device, and based on the measurement task currently performed by the engineering measurement device, sending a measurement task instruction to the determined other engineering measurement device, so that the determined other engineering measurement device performs a measurement task in place of the engineering measurement device, including:
step S301, performing preliminary screening on a plurality of other engineering measurement devices according to the task amount of the measurement tasks historically executed by the plurality of other engineering measurement devices closest to the engineering measurement device and the completion condition by using the following formula (1), screening out a plurality of other engineering measurement devices with more execution tasks and higher success rate,
in the above formula (1), R (a) represents the primary screening control value of the a-th other engineering measurement device closest to the engineering measurement device; n (a) represents the total number of measurement tasks performed by the a-th other engineering measurement device closest to the engineering measurement device up to the current moment; m (a) represents the total number of measurement tasks normally executed by the a-th other engineering measurement equipment closest to the engineering measurement equipment up to the current moment; a represents the total number of other engineering measurement devices closest to the engineering measurement device, wherein the distance is closest to the other engineering measurement devices meeting a preset distance threshold;
if R (a) =1, screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
if R (a) =0, not screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
step S302, screening out the optimal other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task according to the distance between the engineering measurement equipment and the plurality of other engineering measurement equipment with more execution tasks and higher success rate and the task quantity of the measurement task currently executed by the plurality of other engineering measurement equipment with more execution tasks and higher success rate by using the following formula (2),
in the above formula (2), b 'represents that the optimal other engineering measurement device is the b' th other engineering measurement device originally screened in the step A1; s (b) represents the distance value between the b-th other engineering measurement device and the engineering measurement device which are primarily screened in the step S301; b represents the total number of other engineering measurement devices which are primarily screened in the step S301; d (b_t) represents the task amount of the measurement task currently performed by the b-th other engineering measurement device that was initially screened out in the above step S301;substituting B from a value of 1 to B into a bracket to obtain a maximum value in the bracket; />The value B is obtained when substituting B from the value 1 to the value B into the brackets to obtain the maximum value in the brackets;
step S303, utilizing the following formula (3), controlling the overhaul light state on the equipment according to the task quantity and the completion condition of the measurement task historically executed by the engineering measurement equipment which does not normally execute the measurement task,
in the above formula (3), Y represents a control value of the overhaul light state on the apparatus; m is m 0 (e) Indicating the total number of normally executed measurement tasks after the engineering measurement equipment which does not normally execute the measurement tasks has historically executed the e-th measurement task; n (N) 0 (e) Representing the total number of measurement tasks which are executed after the engineering measurement equipment which does not normally execute the measurement tasks historically executes the e-th measurement task; mu represents a preset threshold value of the normal execution rate, if the threshold value is exceededIf the normal execution rate of the over three times is smaller than or equal to mu, the equipment needs to be overhauled; f []A function value of the judgment function is 1 if the expression in the brackets is established, and is 0 if the expression in the brackets is not established; k represents the total number of measurement tasks which are executed by the engineering measurement equipment which does not normally execute the measurement tasks until the current moment;
if Y=1, controlling the overhaul light on the equipment to be turned on, and reminding a worker of overhaul;
if y=0, the overhaul light on the equipment is controlled to be turned off, and overhaul is not needed.
The beneficial effects of the technical scheme are as follows: utilizing the formula (1), performing primary screening on a plurality of other engineering measurement devices according to the task quantity and the completion condition of the measurement tasks historically executed by the plurality of other engineering measurement devices closest to the engineering measurement device, and screening out the plurality of other engineering measurement devices with more execution tasks and higher success rate, thereby intelligently and automatically screening out the plurality of other engineering measurement devices with more execution tasks and higher success rate; then, by utilizing the formula (2), according to the distances between a plurality of other engineering measurement devices with more execution tasks and higher success rate and the engineering measurement devices and the task amounts of the measurement tasks currently executed by the plurality of other engineering measurement devices with more execution tasks and higher success rate, the optimal other engineering measurement devices are screened out to replace the engineering measurement devices to execute the measurement tasks, so that the high efficiency of the system is reflected; finally, according to the task quantity and the completion condition of the measurement task historically executed by the engineering measurement equipment which does not normally execute the measurement task, the overhaul light state on the equipment is controlled by utilizing the formula (3), so that the overhaul light is lightened for intelligent reminding when the number of times of abnormal execution is more, and the intellectualization of the system is embodied.
Preferably, in the step S3, estimating the measurement site state of the engineering measurement device based on the measurement result includes:
obtaining the geological structure settlement and the geological structure inclination direction of the measurement sites corresponding to the determined other engineering measurement equipment based on the geological structure displacement of the measurement sites corresponding to the determined other engineering measurement equipment in different directions;
based on the amount of settlement of the geological structure, the direction of inclination of the geological structure, and the relative positions between the engineering measurement device and the determined other engineering measurement devices, it is estimated whether the measurement site of the engineering measurement device is in a geology safe state.
The beneficial effects of the technical scheme are as follows: the other engineering measurement equipment replaces the original engineering measurement equipment to execute the measurement task on the measurement site, and the position difference exists between the other engineering measurement equipment and the original engineering measurement equipment, so that in order to ensure accurate judgment on whether the geological safety of the measurement site corresponding to the original engineering measurement equipment is ensured, the geological structure settlement amount, the geological structure inclination direction and the relative position between the engineering measurement equipment and the other engineering measurement equipment are obtained by combining the other engineering measurement equipment to estimate.
Preferably, in the step S4, based on all the measurement site states, an engineering quality result of an engineering measurement whole area is obtained, and engineering measurement early warning is performed, including:
and obtaining engineering quality problem areas of the engineering measurement whole area according to the distribution positions of all measurement sites which are not in the geological safety state, and generating engineering measurement early warning information about the area distribution range of the engineering quality problem areas.
The beneficial effects of the technical scheme are as follows: by the method, the distribution positions of the measurement sites which are not in the geological safety state are used as the accuracy, the engineering quality problem areas (such as areas with geological collapse risks) are defined in the engineering measurement whole area, and corresponding engineering measurement early warning messages are generated according to the respective positions of the area boundaries of the engineering quality problem areas, so that the safety risks of the engineering are accurately reminded.
As can be seen from the foregoing embodiments, the cloud computing-based engineering measurement data processing method determines a data interaction mode between a cloud computing platform and engineering measurement equipment, and determines whether to normally execute a measurement task based on a data stream from the engineering measurement equipment; analyzing engineering measurement data from engineering measurement equipment for normally executing the measurement tasks to obtain measurement results of the corresponding measurement tasks, and calibrating the measurement site states; executing other engineering measurement devices instead of the engineering measurement devices which do not normally execute the measurement tasks, and estimating the measurement site state of the engineering measurement devices based on the obtained measurement results; according to the states of all the measuring places, obtaining engineering quality results of the whole engineering measuring area and giving an alarm, distinguishing and managing all the engineering measuring equipment through a cloud computing platform, and analyzing engineering measuring data generated by the engineering measuring equipment which normally executes a measuring task to obtain corresponding measuring place states; and selecting other engineering measurement equipment to replace the engineering measurement equipment which does not normally execute the measurement task, realizing continuous and stable measurement of the whole area range, improving the comprehensiveness and the persistence of the measurement data, and ensuring the early warning reliability of the engineering measurement of the whole area.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (1)
1. The engineering measurement data processing method based on cloud computing is characterized by comprising the following steps of:
step S1, determining a data interaction mode of a cloud computing platform and engineering measurement equipment based on the operation state of the engineering measurement equipment; judging whether the engineering measurement equipment normally executes a measurement task or not based on the data flow from the engineering measurement equipment in the current data interaction mode;
step S2, when the engineering measurement equipment normally executes a measurement task, analyzing engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain a measurement result of the corresponding measurement task; calibrating the measurement site state of the engineering measurement equipment based on the measurement result;
step S3, when the engineering measurement equipment does not normally execute the measurement task, indicating other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task through the cloud computing platform, and analyzing engineering measurement data from the other engineering measurement equipment to obtain a measurement result of the corresponding measurement task; estimating a measurement site state of the engineering measurement device based on the measurement result;
step S4, obtaining engineering quality results of the whole engineering measurement area based on the states of all measurement places, and carrying out engineering measurement early warning;
in the step S1, determining a data interaction mode of the cloud computing platform and the engineering measurement device based on the operation state of the engineering measurement device includes:
sending an operation state acquisition instruction to engineering measurement equipment, and acquiring an operation log of the engineering measurement equipment;
analyzing and processing the operation log to obtain the frequency of generating engineering measurement data by the engineering measurement equipment and the average data quantity of each generation of the engineering measurement data, and taking the frequency and the average data quantity as the operation state;
based on the frequency and the data volume for generating engineering measurement data, determining the frequency of a data acquisition request sent to the engineering measurement equipment by a cloud computing platform and the bandwidth of a data interaction channel between the cloud computing platform and the engineering measurement equipment;
in the step S1, based on the data flow from the engineering measurement device in the current data interaction mode, determining whether the engineering measurement device normally executes a measurement task includes:
carrying out identification processing on engineering measurement data flow from the engineering measurement equipment in a current data interaction mode to obtain a data volume ratio corresponding to data of which the engineering measurement data flow contains data meeting a preset form condition;
if the data volume duty ratio is larger than or equal to a preset duty ratio threshold value, judging that the engineering measurement equipment normally executes a measurement task; otherwise, judging that the engineering measurement equipment does not normally execute a measurement task;
in the step S2, when the engineering measurement device normally executes a measurement task, the cloud computing platform analyzes engineering measurement data from the engineering measurement device to obtain a measurement result of the corresponding measurement task, including:
when the engineering measurement equipment normally executes a measurement task, screening all engineering measurement data from the engineering measurement equipment through the cloud computing platform to obtain all engineering measurement data belonging to the same measurement task;
analyzing all engineering measurement data belonging to the same measurement task to obtain a geological structure measurement result of a measurement site of the corresponding measurement task; the geological structure measurement result comprises geological structure displacement amounts of the measurement site in different directions;
in the step S2, calibrating the measurement site state of the engineering measurement device based on the measurement result includes:
obtaining the geological structure settlement and the geological structure inclination direction of the measurement site of the engineering measurement equipment based on the geological structure displacement of the measurement site in different directions;
calibrating whether a measurement site of the engineering measurement equipment is in a geological safety state or not based on the geological structure settlement and the geological structure inclination direction;
in the step S3, when the engineering measurement device does not normally execute the measurement task, the cloud computing platform instructs other engineering measurement devices to replace the engineering measurement device to execute the measurement task, and analyzes engineering measurement data from the other engineering measurement devices to obtain a measurement result of the corresponding measurement task, including:
when the engineering measurement equipment does not normally execute a measurement task, determining other engineering measurement equipment closest to the engineering measurement equipment through the cloud computing platform, and sending a measurement task instruction to the determined other engineering measurement equipment based on the measurement task currently executed by the engineering measurement equipment, so that the determined other engineering measurement equipment replaces the engineering measurement equipment to execute the measurement task;
analyzing all engineering measurement data from the determined other engineering measurement equipment about the measurement task instruction to obtain a geological structure measurement result of a measurement place corresponding to the determined other engineering measurement equipment; the geological structure measurement result comprises geological structure displacement amounts of measurement sites corresponding to the determined other engineering measurement equipment in different directions;
in the step S3, when the engineering measurement device does not normally execute a measurement task, determining, by the cloud computing platform, another engineering measurement device closest to the engineering measurement device, and based on the measurement task currently executed by the engineering measurement device, sending a measurement task instruction to the determined other engineering measurement device, so that the determined other engineering measurement device replaces the engineering measurement device to execute the measurement task, including:
step S301, performing preliminary screening on a plurality of other engineering measurement devices according to the task amount of the measurement tasks historically executed by the plurality of other engineering measurement devices closest to the engineering measurement device and the completion condition by using the following formula (1), screening out a plurality of other engineering measurement devices with more execution tasks and higher success rate,
in the above formula (1), R (a) represents a preliminary screening control value of an a-th other engineering measurement device closest to the engineering measurement device; n (a) represents the number of measurement tasks which are totally executed by the a-th other engineering measurement equipment closest to the engineering measurement equipment up to the current moment; m (a) represents the total number of measurement tasks normally executed by the a-th other engineering measurement equipment closest to the engineering measurement equipment up to the current moment; a represents the total number of other engineering measurement devices closest to the engineering measurement device, wherein the closest distance is the other engineering measurement devices meeting a preset distance threshold;
if R (a) =1, screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
if R (a) =0, not screening out the a-th other engineering measurement equipment closest to the engineering measurement equipment;
step S302, screening out the optimal other engineering measurement equipment to replace the engineering measurement equipment to execute the measurement task according to the distance between a plurality of other engineering measurement equipment with more execution tasks and higher success rate and the engineering measurement equipment and the task quantity of the measurement task currently executed by the plurality of other engineering measurement equipment with more execution tasks and higher success rate by using the following formula (2),
in the above formula (2), b 'represents that the optimal other engineering measurement device is the b' th other engineering measurement device originally screened in the step A1; s (b) represents the distance value between the b-th other engineering measurement equipment and the engineering measurement equipment which are primarily screened in the step S301; b represents the total number of other engineering measurement devices which are primarily screened in the step S301; d (b_t) represents the task amount of the measurement task currently performed by the b-th other engineering measurement device that was initially screened out in the above step S301;substituting B from a value of 1 to B into a bracket to obtain a maximum value in the bracket; />The value B is obtained when substituting B from the value 1 to the value B into the brackets to obtain the maximum value in the brackets;
step S303, utilizing the following formula (3), controlling the overhaul light state on the equipment according to the task quantity and the completion condition of the measurement task historically executed by the engineering measurement equipment which does not normally execute the measurement task,
in the above formula (3), Y represents a control value of an overhaul light state on the apparatus; m is m 0 (e) The number of the total normal execution of the measurement tasks after the engineering measurement equipment which does not normally execute the measurement tasks has historically executed the e-th measurement task is represented; n (N) 0 (e) Representing the total number of measurement tasks which are executed after the engineering measurement equipment which does not normally execute the measurement tasks historically executes the e-th measurement task; μ represents a preset threshold of normal execution rate, and if the normal execution rate exceeding three times is smaller than or equal to μ, the equipment needs to be overhauled; f []A function value of the judgment function is 1 if the expression in the brackets is established, and is 0 if the expression in the brackets is not established; k represents the total number of measurement tasks which are executed by the engineering measurement equipment which does not normally execute the measurement tasks until the current moment;
if Y=1, controlling the overhaul light on the equipment to be turned on, and reminding a worker of overhaul;
if Y=0, controlling the overhaul light on the equipment to be turned off, and not needing to overhaul;
in the step S3, estimating a measurement site state of the engineering measurement device based on the measurement result, including:
obtaining the geological structure settlement and the geological structure inclination direction of the determined measurement sites corresponding to other engineering measurement equipment based on the geological structure displacement of the determined measurement sites corresponding to other engineering measurement equipment in different directions; estimating whether a measurement site of the engineering measurement device is in a geology safe state based on the geological structure settlement amount, the geological structure inclination direction and the relative positions between the engineering measurement device and the determined other engineering measurement devices; in the step S4, based on the states of all the measurement sites, the engineering quality result of the whole engineering measurement area is obtained, and engineering measurement early warning is performed, including:
and obtaining engineering quality problem areas of the engineering measurement whole area according to the distribution positions of all measurement sites which are not in the geological safety state, and generating engineering measurement early warning information about the area distribution range of the engineering quality problem areas.
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