CN118095934A - Engineering supervision method and device for high-rise building and electronic equipment - Google Patents
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Abstract
The application provides a method, a device and electronic equipment for engineering supervision of a high-rise building, which relate to the technical field of building supervision, and the method comprises the following steps: acquiring vibration data acquired by each vibration sensor; preprocessing a plurality of vibration data to obtain a plurality of processed data; comparing the difference values of the plurality of processing data of the same time node to determine abnormal data in the plurality of processing data; determining an abnormal sensor corresponding to abnormal data in the plurality of vibration sensors; and outputting an early warning prompt to prompt a prisoner that the abnormal sensor needs to be calibrated. The method and the device can find out the abnormal data generated by the sensor abnormality in the supervision process of the high-rise building.
Description
Technical Field
The application relates to the technical field of building supervision, in particular to a method and a device for managing engineering of a high-rise building and electronic equipment.
Background
The engineering supervision refers to a supervision unit with relevant qualification, and represents a specialized service activity for monitoring the engineering construction of the second party by the first party according to relevant laws, regulations, technical standards, relevant contracts, files and the like. The project supervision aims to ensure the project construction quality and safety, improve the project construction level and fully exert the investment benefit. The work content of engineering supervision mainly comprises construction process supervision, quality inspection, safety supervision, progress management, site coordination and the like.
The high-rise building is a residential building having a building height greater than a prescribed standard height. High-rise buildings are generally more susceptible to wind, vibration, temperature, etc., than low-rise buildings, thereby affecting the stability and durability of the project. At present, vibration conditions of high-rise buildings are monitored in real time by installing sensors and monitoring systems. Real-time high-rise building vibration data can be obtained by a supervisor, so that problems can be found early and preventive or repair measures can be taken, and the safety and stability of a high-rise building are ensured.
When vibration conditions of a high-rise building are monitored in real time through a sensor and a monitoring system, abnormal data may be generated due to sensor faults rather than building structure problems. Without identifying and excluding these abnormal data, false alarms may result, wasting time and resources. Therefore, a method is needed to find out abnormal data generated by abnormal sensors in the process of monitoring high-rise buildings.
Disclosure of Invention
The application provides an engineering supervision method and device for a high-rise building and electronic equipment, which can be used for searching abnormal data generated by sensor abnormality in the supervision process of the high-rise building.
In a first aspect of the application, there is provided a method of engineering supervision of a high-rise building, the method comprising:
Acquiring vibration data acquired by each vibration sensor;
preprocessing a plurality of vibration data to obtain a plurality of processed data;
Comparing the difference values of a plurality of processing data of the same time node, and determining abnormal data in the plurality of processing data;
determining an abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors;
And outputting an early warning prompt to prompt a prisoner that the abnormal sensor needs to be calibrated.
By adopting the technical scheme, the vibration data of the building is acquired through the vibration sensor. Through preprocessing, operations such as filtering, denoising and the like can be performed on the vibration data, so that the accuracy and reliability of the data are improved, and subsequent data analysis is facilitated. And then, comparing the difference values of the plurality of processing data of the same time node, so that abnormal data in the processing data can be found. Because vibrations generated by a tall building are typically transmitted to different vibration sensors, the differences are typically within an acceptable range, i.e., the differences in the plurality of vibration data are within a range, although there is a difference in the magnitude. If there is a large difference, the corresponding anomaly data may be due to vibration sensor failure, signal interference, or other anomalies. Further, by tracking the source of the abnormal data, it is possible to determine which vibration sensor has a problem in acquiring the data. And outputting an early warning prompt to inform a supervisor that the abnormal sensor needs to be calibrated. Thereby, in the supervision process of the high-rise building, abnormal data generated by abnormal sensors are searched.
Optionally, the comparing the difference value of the plurality of processing data of the same time node to determine abnormal data in the plurality of processing data specifically includes:
According to first data acquired by each vibration sensor at a first time node and second data acquired by a second time node, determining fluctuation difference values of the first data and the second data, wherein the first time node and the second time node are any two adjacent time nodes in a plurality of times;
Determining a first difference value which is smaller than or equal to a preset difference value in the fluctuation difference values;
determining a fluctuation range according to a plurality of first sub-data, wherein the first sub-data is second data corresponding to the first difference value in a plurality of second data;
Determining a second difference value larger than the preset difference value in the fluctuation difference values;
Judging whether second sub-data is in the fluctuation range or not, wherein the second sub-data is second data corresponding to a second difference value in a plurality of second data;
And if the second sub-data is not in the fluctuation range, determining that the second sub-data is abnormal data.
By adopting the technical scheme, under the condition that the vibration sensor is normal, the fluctuation difference value of the vibration data collected by the adjacent time nodes is not too large, namely the data fluctuation is smaller and smaller than or equal to the preset difference value. When the fluctuation of the vibration data collected by a certain vibration sensor is small, the vibration sensor and the vibration data are normal, and then the vibration data are used for calculating the fluctuation range, namely a normal range in which the normal vibration data are supposed to be. And finally, screening out abnormal data which deviate from a normal range obviously by comparing whether the vibration data with larger fluctuation difference value is in a fluctuation range or not.
Optionally, after the acquiring the vibration data acquired by each vibration sensor, the method further includes:
acquiring physical addresses of the vibration sensors based on a preset positioning rule;
Establishing a mapping relation between a first physical address and first vibration data, wherein the first physical address is a physical address corresponding to a first sensor, the first vibration data is vibration data acquired by the first sensor, and the first sensor is any one of a plurality of vibration sensors.
By adopting the technical scheme, after the vibration data acquired by each vibration sensor are acquired, the mapping relation between the physical address and the vibration data is established by acquiring the physical address of each vibration sensor under the preset positioning rule. This mapping can correlate the physical location of each vibration sensor with the vibration data it collects, providing more detailed and accurate information for use in subsequent data processing and analysis.
Optionally, the determining the abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors specifically further includes:
Determining a second physical address corresponding to the abnormal data according to the mapping relation, wherein the second physical address is any one physical address of a plurality of physical addresses;
and determining an abnormal sensor in the plurality of vibration sensors according to the second physical address.
By adopting the technical scheme, the physical address corresponding to the abnormal data is determined through the mapping relation, and the corresponding sensor is found, so that the abnormal sensor can be determined more quickly, and more accurate information is provided for subsequent calibration operation.
Optionally, after the outputting the early warning prompt, the method further includes:
acquiring a judgment result of the supervision personnel on the abnormal data;
If the judgment result is that the abnormal sensor is abnormal in calibration, acquiring calibration parameters which are input by the supervision personnel and aim at the abnormal sensor;
And sending the calibration parameters to the anomaly sensor.
By adopting the technical scheme, after the early warning prompt is output, whether the abnormal sensor and the abnormal data are determined correctly or not is further determined by acquiring the judgment result of the supervision personnel on the abnormal data. And according to the judgment result, the calibration parameters input by the supervision personnel aiming at the abnormal sensor are obtained, and then the calibration parameters are sent to the abnormal sensor, so that the calibration operation of the abnormal sensor is realized.
Optionally, the preprocessing the vibration data to obtain a plurality of processing data specifically includes:
Cleaning the vibration data to remove noise values and obtain first vibration data;
performing standardization processing on the plurality of first vibration data to obtain a plurality of second vibration data in the same form;
And carrying out interpolation processing on the plurality of first vibration data to obtain a plurality of processing data.
By adopting the technical scheme, the cleaning treatment can help to remove the noise value in the original vibration data, reduce the influence of interference signals on data analysis and improve the purity of the data. The normalization process may convert the plurality of first vibration data into the same form of second vibration data, resulting in better comparability and analyzability between different data. The interpolation processing can supplement and perfect the missing or insufficient part in the first vibration data, improve the continuity and the integrity of the data, and is beneficial to finding and extracting more comprehensive information. Invalid or low-quality vibration data can be filtered through preprocessing, the workload and the computational complexity of subsequent data analysis are reduced, and the data processing efficiency is improved.
Optionally, the outputting the early warning prompt specifically includes:
Acquiring a BIM model of a high-rise building;
determining a model position of the anomaly sensor in the BIM model according to the second physical address;
And according to the model position, displaying the abnormal sensor in the BIM model.
By adopting the technical scheme, the abnormal sensor is displayed in the BIM model, so that the visual display and positioning of the abnormal sensor are realized. The abnormal sensor is displayed in the BIM model, so that the position and state of the abnormal sensor can be intuitively displayed, and clearer and accurate perception information is provided for the supervision personnel. Meanwhile, the problem can be rapidly positioned, and the exception handling and maintenance operations can be conveniently and timely carried out by the supervision personnel.
In a second aspect of the present application, an engineering supervision apparatus for a high-rise building is provided, including an acquisition module, a processing module, a comparison module, a sensor positioning module, and an output module, where:
the acquisition module is used for acquiring vibration data acquired by each vibration sensor.
The processing module is used for preprocessing a plurality of vibration data to obtain a plurality of processing data.
The comparison module is used for comparing the difference values of the plurality of processing data of the same time node and determining abnormal data in the plurality of processing data.
The sensor positioning module is used for determining an abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors.
And the output module is used for outputting an early warning prompt to prompt a prisoner that the abnormal sensor needs to be calibrated.
Optionally, the comparison module is configured to determine, according to first data collected by each vibration sensor at a first time node and second data collected by a second time node, a fluctuation difference value between the first data and the second data, where the first time node and the second time node are any two adjacent time nodes in a plurality of times.
The comparison module is used for determining a first difference value smaller than or equal to a preset difference value among the fluctuation difference values.
The processing module is used for determining a fluctuation range according to a plurality of first sub-data, wherein the first sub-data is second data corresponding to the first difference value in the plurality of second data.
The comparison module is used for determining a second difference value which is larger than the preset difference value in the fluctuation difference values.
The comparison module is used for judging whether second sub-data is in the fluctuation range, wherein the second sub-data is second data corresponding to the second difference value in a plurality of second data.
And the processing module is used for determining the second sub-data as abnormal data if the second sub-data is not in the fluctuation range.
Optionally, the sensor positioning module is configured to obtain a physical address of each vibration sensor based on a preset positioning rule.
The comparison module is used for establishing a mapping relation between a first physical address and first vibration data, the first physical address is a physical address corresponding to a first sensor, the first vibration data are vibration data acquired by the first sensor, and the first sensor is any one of a plurality of vibration sensors.
Optionally, the comparison module is configured to determine, according to the mapping relationship, a second physical address corresponding to the abnormal data, where the second physical address is any one physical address of the plurality of physical addresses.
The sensor positioning module is used for determining abnormal sensors in the vibration sensors according to the second physical address.
Optionally, the acquiring module is configured to acquire a result of the judging of the abnormal data by the prison.
The acquisition module is used for acquiring the calibration parameters which are input by the supervision personnel and aimed at the abnormal sensor if the judgment result is that the abnormal sensor is abnormal in calibration.
The output module is used for sending the calibration parameters to the abnormal sensor.
Optionally, the processing module is configured to perform cleaning processing on the plurality of vibration data, and remove a noise value to obtain a plurality of first vibration data.
And the processing module is used for carrying out standardization processing on the plurality of first vibration data to obtain a plurality of second vibration data in the same form.
And the processing module is used for carrying out interpolation processing on the plurality of first vibration data to obtain a plurality of processing data.
Optionally, the acquiring module is configured to acquire a BIM model of the high-rise building.
The sensor positioning module is used for determining the model position of the abnormal sensor in the BIM according to the second physical address.
And the output module is used for displaying the abnormal sensor in the BIM according to the model position.
In a third aspect the application provides an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface, both for communicating with other devices, the processor being for executing instructions stored in the memory to cause the electronic device to perform a method as claimed in any one of the preceding claims.
In a fourth aspect of the application there is provided a computer readable storage medium storing instructions which, when executed, perform a method as claimed in any one of the preceding claims.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. Firstly, vibration data of a building are obtained through a vibration sensor. Through preprocessing, operations such as filtering, denoising and the like can be performed on the vibration data, so that the accuracy and reliability of the data are improved, and subsequent data analysis is facilitated. And then, comparing the difference values of the plurality of processing data of the same time node, so that abnormal data in the processing data can be found. Because vibrations generated by a tall building are typically transmitted to different vibration sensors, the differences are typically within an acceptable range, i.e., the differences in the plurality of vibration data are within a range, although there is a difference in the magnitude. If there is a large difference, the corresponding anomaly data may be due to vibration sensor failure, signal interference, or other anomalies. Further, by tracking the source of the abnormal data, it is possible to determine which vibration sensor has a problem in acquiring the data. And outputting an early warning prompt to inform a supervisor that the abnormal sensor needs to be calibrated. Thereby, in the supervision process of the high-rise building, abnormal data generated by abnormal sensors are searched.
2. Under the condition that the vibration sensor is normal, the fluctuation difference value of vibration data collected by adjacent time nodes is not too large, namely the data fluctuation is smaller and smaller than or equal to the preset difference value. When the fluctuation of the vibration data collected by a certain vibration sensor is small, the vibration sensor and the vibration data are normal, and then the vibration data are used for calculating the fluctuation range, namely a normal range in which the normal vibration data are supposed to be. And finally, screening out abnormal data which deviate from a normal range obviously by comparing whether the vibration data with larger fluctuation difference value is in a fluctuation range or not.
Drawings
FIG. 1 is a schematic flow chart of a method for engineering supervision of a high-rise building according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an engineering supervision device for a high-rise building according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 201. an acquisition module; 202. a processing module; 203. comparison module; 204. a sensor positioning module; 205. an output module; 301. a processor; 302. a communication bus; 303. a user interface; 304. a network interface; 305. a memory.
Detailed Description
In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.
In describing embodiments of the present application, words such as "for example" or "for example" are used to mean serving as examples, illustrations, or descriptions. Any embodiment or design described herein as "such as" or "for example" in embodiments of the application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of embodiments of the application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
The engineering supervision refers to a supervision unit with relevant qualification, and represents a specialized service activity for monitoring the engineering construction of the second party by the first party according to relevant laws, regulations, technical standards, relevant contracts, files and the like. The project supervision aims to ensure the project construction quality and safety, improve the project construction level and fully exert the investment benefit. The work content of engineering supervision mainly comprises construction process supervision, quality inspection, safety supervision, progress management, site coordination and the like.
The high-rise building is a residential building having a building height greater than a prescribed standard height. High-rise buildings are generally more susceptible to wind, vibration, temperature, etc., than low-rise buildings, thereby affecting the stability and durability of the project. At present, vibration conditions of high-rise buildings are monitored in real time by installing sensors and monitoring systems. Real-time high-rise building vibration data can be obtained by a supervisor, so that problems can be found early and preventive or repair measures can be taken, and the safety and stability of a high-rise building are ensured.
When vibration conditions of a high-rise building are monitored in real time through a sensor and a monitoring system, abnormal data may be generated due to sensor faults rather than building structure problems. Without identifying and excluding these abnormal data, false alarms may result, wasting time and resources. Therefore, a method is needed to realize abnormal data generated due to abnormal sensors in the process of supervision of high-rise buildings.
The embodiment discloses an engineering supervision method for a high-rise building, referring to fig. 1, comprising the following steps:
S110, vibration data acquired by each vibration sensor are acquired.
The engineering supervision method for the high-rise building disclosed by the embodiment of the application is applied to a server, wherein the server comprises but is not limited to electronic equipment such as a mobile phone, a tablet personal computer, wearable equipment, a PC (Personal Computer ) and the like, and can also be a background server for running the engineering supervision method for the high-rise building. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
Before acquiring vibration data collected by a plurality of vibration sensors, it is necessary to install the vibration sensors on a high-rise building. First, the monitored targets and demands are clarified, such as monitoring the vibration response of the building structure, assessing the health of the structure, predicting the safety of the structure, etc. An appropriate vibration sensor, such as an acceleration sensor, a speed sensor or a displacement sensor, is then selected according to the monitoring purpose and requirements. And selecting a proper installation position according to the structural characteristics and monitoring requirements of the high-rise building. It is often desirable to install sensors at strategic locations and representative locations of a building, such as structural support points, floor nodes, etc. of the building. After the installation position is determined, an installation base is prepared. Depending on the size and weight of the sensor, the appropriate mounting materials and manner are selected. And then the selected vibration sensor is installed according to the installation requirement. It is often necessary to secure the sensor to the mounting base and to ensure that the sensor is tightly coupled to the building structure to avoid errors. And the output signal of each vibration sensor is connected to the server, so that stable and reliable connection is ensured, and signal interference or distortion is avoided. Suitable data acquisition parameters, such as sampling frequency, sampling time, etc., are set according to the monitoring purpose and requirements. And finally, starting the server and the vibration sensor, and starting to collect vibration data.
In order to facilitate the subsequent quick search of the vibration sensor corresponding to the abnormal data according to the abnormal data in the vibration data, a mapping relationship between the vibration data of the vibration sensor and the physical address of the vibration sensor needs to be established, so that the vibration sensor can be found according to the physical address corresponding to the vibration data. The preset positioning rule is a positioning rule which is preset in advance according to the structure and design of a high-rise building and is used for determining the physical position of each vibration sensor in the building. The rules may be formulated based on factors such as architectural features, key locations, floor nodes, etc.
The physical address of each vibration sensor is obtained, and in general, when the vibration sensor is installed, the physical address is required to be compared with the data such as the design drawing, the structural diagram and the like of the building, and the accurate position of each sensor in the building is determined. The physical address may be at a certain floor at a certain stairway or at a certain support column connection of a certain floor.
After the physical addresses of the individual vibration sensors are acquired, these addresses need to be correlated and mapped with the vibration data collected by the sensors. Specifically, the position information of each sensor is corresponding to the acquired vibration data, and a mapping relation between the position information and the acquired vibration data is established. Therefore, the physical address of the sensor can be associated with corresponding vibration data, and subsequent data processing and analysis are convenient.
After the vibration data acquired by each vibration sensor are acquired, the mapping relation between the physical address and the vibration data is established by acquiring the physical address of each vibration sensor under the preset positioning rule. This mapping can correlate the physical location of each vibration sensor with the vibration data it collects, providing more detailed and accurate information for use in subsequent data processing and analysis.
S120, preprocessing the vibration data to obtain processed data.
Vibration data may contain noise and inaccurate measurements, thus requiring a cleaning process. The cleaning process may be performed in a variety of ways, such as using filters, statistical methods, or threshold-based filtering techniques to identify and remove noise values. After the cleaning process, a plurality of first vibration data will be obtained, which have been freed from noise and inaccurate measurements, more closely approaching the real vibration situation.
And carrying out standardization processing on the plurality of first vibration data to obtain a plurality of second vibration data in the same form. The normalization process is a process of converting data into a standard form, such as normalizing or normalizing the data to a specific range or standard deviation. By means of standardization processing, data of different sources and forms can be made to be comparable, and subsequent data analysis and processing are facilitated. In the technical scheme, after the plurality of first vibration data are subjected to standardization processing, a plurality of second vibration data in the same form are obtained. These data are of the same standard form and can be more conveniently compared and analyzed.
And carrying out interpolation processing on the plurality of first vibration data to obtain a plurality of processing data. Interpolation is a mathematical method for estimating the unknown value between given data points. In vibration data analysis, interpolation processing may be used to fill in missing measurements, smooth data, or improve the resolution of the data. In this technical scheme, after interpolation processing is performed on the plurality of first vibration data, a plurality of processing data will be obtained. These data may have a higher accuracy and smoother curve shape, which is more convenient for subsequent data analysis and application.
The cleaning process can help to remove noise values in the original vibration data, reduce the influence of interference signals on data analysis, and improve the purity of the data. The normalization process may convert the plurality of first vibration data into the same form of second vibration data, resulting in better comparability and analyzability between different data. The interpolation processing can supplement and perfect the missing or insufficient part in the first vibration data, improve the continuity and the integrity of the data, and is beneficial to finding and extracting more comprehensive information. Invalid or low-quality vibration data can be filtered through preprocessing, the workload and the computational complexity of subsequent data analysis are reduced, and the data processing efficiency is improved. It should be noted that the specific implementation of the above technical solution may be different according to the application scenario, the data type and the analysis requirement. In actual operation, adjustment and optimization are required according to specific situations.
S130, comparing the plurality of processing data of the same time node, and determining abnormal data in the plurality of processing data.
Specifically, firstly, according to first data collected by each vibration sensor at a first time node and second data collected by each vibration sensor at a second time node, a fluctuation difference value of the first data and the second data is determined. Here, "first time node" and "second time node" refer to any two adjacent time nodes among a plurality of time nodes. For example, if the frequency of how the vibration sensor is configured to collect data is such that data is collected once every second, then the "first time node" may be 2 seconds, the "second time node" may be 3 seconds, and so on.
The fluctuation difference is the difference between the data acquired by a pointer to a certain vibration sensor at two adjacent time nodes. This difference may be obtained by calculating the difference between the two data, the relative error, the absolute error, etc. The fluctuation difference can be reflected between two time nodes, and the data change condition of the vibration sensor is reflected.
And then the server judges the magnitude relation between each fluctuation difference value and a preset difference value, wherein the preset difference value is a preset standard for judging whether the fluctuation of the data is within an acceptable range. The setting of the preset difference value can be determined according to the actual application scene and the data analysis requirement. The server determines a first difference value among the plurality of fluctuation difference values that is less than or equal to a preset difference value. And then determining first sub-data corresponding to each first difference value, wherein the first sub-data is second data corresponding to the first difference value in the plurality of second data.
A fluctuation range is then determined from the plurality of first sub-data, the fluctuation range referring to an acceptable fluctuation range of the data determined from the first sub-data. The fluctuation range can be calculated by a variety of methods, including standard deviation, which is a common method for measuring the degree of dispersion in the values in the data set. It calculates the difference between each data point and the mean of the dataset and sums the squares of these differences, finally taking the square root of the mean. The larger the standard deviation, the wider the fluctuation range of the data. There is also a percentile method, which is a method of segmenting a dataset that can help identify a particular distribution of data. For example, the difference between the 25 th percentile and the 75 th percentile may be used to determine the fluctuation range of the data.
And determining a second difference value larger than the preset difference value in the fluctuation difference values. The second difference refers to second data that have a fluctuation difference greater than a preset difference at adjacent time nodes. These data are of interest and analysis because they may fluctuate beyond a preset range. And then determining whether the second sub-data is within the fluctuation range. The second sub data is second data corresponding to the second difference value among the plurality of second data. In other words, the second sub-data are those having a fluctuation difference greater than a preset difference at adjacent time nodes. If the second sub-data is within the fluctuation range, it may not be an abnormal data; otherwise, it is regarded as an abnormal data.
Under the condition that the vibration sensor is normal, the fluctuation difference value of vibration data collected by adjacent time nodes is not too large, namely the data fluctuation is smaller and smaller than or equal to the preset difference value. When the fluctuation of the vibration data collected by a certain vibration sensor is small, the vibration sensor and the vibration data are normal, and then the vibration data are used for calculating the fluctuation range, namely a normal range in which the normal vibration data are supposed to be. And finally, screening out abnormal data which deviate from a normal range obviously by comparing whether the vibration data with larger fluctuation difference value is in a fluctuation range or not.
S140, determining an abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors.
According to the mapping relationship between the vibration data and the vibration sensor obtained in step S110, the server may associate the abnormal data with a specific physical address according to the mapping relationship. After the abnormal data is determined, the server directly determines a second physical address corresponding to the abnormal data according to the mapping relation, wherein the second physical address is any one physical address of a plurality of physical addresses. The server further determines an anomaly sensor of the plurality of vibration sensors based on the physical address. The physical address corresponding to the abnormal data is determined through the mapping relation, and the corresponding sensor is found, so that the abnormal sensor can be determined more quickly, and more accurate information is provided for subsequent calibration operation.
S150, outputting an early warning prompt.
Further, if the vibration data collected by the plurality of vibration sensors are abnormal, in order to facilitate the supervisor to rapidly analyze the cause, the positions of the sensors corresponding to the abnormal data need to be intuitively displayed through the BIM model of the high-rise building.
First, the server obtains a BIM model of the high-rise building, which is typically created, edited, and shared by the designer during the building design phase using existing BIM software or tools, such as AutoDesk Revit, archicad, etc. After the second physical address corresponding to the abnormal data is present, the position of the abnormal sensor in the model may be further determined. This may be accomplished by querying or searching the BIM model to find a model location corresponding to the second physical address. Once the model location of the anomaly sensor is determined, it can be revealed in the BIM model. This may be viewed directly in a 3D view or may be presented in a cross-sectional, sectional or detail view. It may be marked and presented in the BIM model using marks, colors, or special symbols, etc.
And displaying the abnormal sensor in the BIM model, so that visual display and positioning of the abnormal sensor are realized. The abnormal sensor is displayed in the BIM model, so that the position and state of the abnormal sensor can be intuitively displayed, and clearer and accurate perception information is provided for the supervision personnel. Meanwhile, the problem can be rapidly positioned, and the exception handling and maintenance operations can be conveniently and timely carried out by the supervision personnel.
Further, after the abnormal sensor of the prison is prompted to be calibrated through the early warning prompt, the server needs to acquire the judgment result of the prison on the abnormal data. These determination results may include analysis of the cause of the abnormality, confirmation of the sensor failure, and the like. If the supervisor determines that the abnormal data is due to an abnormal sensor calibration, then corresponding calibration parameters need to be obtained to calibrate the sensor. The "calibration parameters" include various physical quantities for adjusting and calibrating the sensor, such as acceleration, signal strength, frequency, etc. These parameters may be measured and entered by a supervisor or other professional through a specialized calibration device or tool. The calibration parameters are obtained at the server and can be sent to the corresponding anomaly sensors. The calibration of the anomaly sensor is accomplished by writing parameters into the memory of the sensor or by processing and adjusting by an intermediate device, such as a data collector or controller.
After the early warning prompt is output, whether the abnormal sensor and the abnormal data are determined correctly or not is further determined by acquiring the judgment result of the supervision personnel on the abnormal data. And according to the judgment result, the calibration parameters input by the supervision personnel aiming at the abnormal sensor are obtained, and then the calibration parameters are sent to the abnormal sensor, so that the calibration operation of the abnormal sensor is realized.
By adopting the technical scheme, the vibration data of the building is acquired through the vibration sensor. Through preprocessing, operations such as filtering, denoising and the like can be performed on the vibration data, so that the accuracy and reliability of the data are improved, and subsequent data analysis is facilitated. And then, comparing the difference values of the plurality of processing data of the same time node, so that abnormal data in the processing data can be found. Because vibrations generated by a tall building are typically transmitted to different vibration sensors, the differences are typically within an acceptable range, i.e., the differences in the plurality of vibration data are within a range, although there is a difference in the magnitude. If there is a large difference, the corresponding anomaly data may be due to vibration sensor failure, signal interference, or other anomalies. Further, by tracking the source of the abnormal data, it is possible to determine which vibration sensor has a problem in acquiring the data. And outputting an early warning prompt to inform a supervisor that the abnormal sensor needs to be calibrated. Thereby, in the supervision process of the high-rise building, abnormal data generated by abnormal sensors are searched.
The embodiment also discloses an engineering supervision device for high-rise buildings, referring to fig. 2, comprising an acquisition module 201, a processing module 202, a comparison module 203, a sensor positioning module 204 and an output module 205, wherein:
an acquisition module 201, configured to acquire vibration data acquired by each vibration sensor.
The processing module 202 is configured to pre-process the plurality of vibration data to obtain a plurality of processed data.
The comparison module 203 is configured to perform difference comparison on the plurality of processing data of the same time node, and determine abnormal data in the plurality of processing data.
The sensor positioning module 204 is configured to determine an abnormal sensor corresponding to the abnormal data from among the plurality of vibration sensors.
And the output module 205 is used for outputting an early warning prompt to prompt the proctoring personnel that the abnormal sensor needs to be calibrated.
In one possible implementation manner, the comparison module 203 is configured to determine, according to first data collected by each vibration sensor at a first time node and second data collected by a second time node, a fluctuation difference value between the first data and the second data, where the first time node and the second time node are any two adjacent time nodes in a plurality of times.
The comparison module 203 is configured to determine a first difference value among the plurality of fluctuation difference values that is less than or equal to a preset difference value.
The processing module 202 is configured to determine a fluctuation range according to a plurality of first sub-data, where the first sub-data is second data corresponding to the first difference value among the plurality of second data.
The comparison module 203 is configured to determine a second difference value greater than the preset difference value among the plurality of fluctuation difference values.
The comparison module 203 is configured to determine whether the second sub-data is in a fluctuation range, where the second sub-data is a second data corresponding to a second difference value among the plurality of second data.
The processing module 202 is configured to determine that the second sub-data is abnormal data if the second sub-data is not in the fluctuation range.
In one possible implementation, the sensor positioning module 204 is configured to obtain the physical address of each vibration sensor based on a preset positioning rule.
The comparison module 203 is configured to establish a mapping relationship between a first physical address and first vibration data, where the first physical address is a physical address corresponding to a first sensor, the first vibration data is vibration data collected by the first sensor, and the first sensor is any one of a plurality of vibration sensors.
In one possible implementation, the comparison module 203 is configured to determine, according to the mapping relationship, a second physical address corresponding to the abnormal data, where the second physical address is any one physical address of the plurality of physical addresses.
The sensor positioning module 204 is configured to determine an abnormal sensor of the plurality of vibration sensors according to the second physical address.
In a possible implementation manner, the obtaining module 201 is configured to obtain a result of the judgment of the proctor on the abnormal data.
The obtaining module 201 is configured to obtain a calibration parameter for the abnormal sensor input by a supervisor if the determination result is that the calibration of the abnormal sensor is abnormal.
An output module 205 for sending the calibration parameters to the anomaly sensor.
In one possible implementation, the processing module 202 is configured to perform a cleaning process on the plurality of vibration data, and remove noise values to obtain a plurality of first vibration data.
The processing module 202 is configured to perform normalization processing on the plurality of first vibration data to obtain a plurality of second vibration data in the same form.
The processing module 202 is configured to perform interpolation processing on the plurality of first vibration data to obtain a plurality of processing data.
In one possible implementation, the obtaining module 201 is configured to obtain a BIM model of a high-rise building.
The sensor positioning module 204 is configured to determine a model position of the abnormal sensor in the BIM model according to the second physical address.
An output module 205 for displaying the anomaly sensor in the BIM model based on the model location.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The embodiment also discloses an electronic device, referring to fig. 3, the electronic device may include: at least one processor 301, at least one communication bus 302, a user interface 303, a network interface 304, at least one memory 305.
Wherein the communication bus 302 is used to enable connected communication between these components.
The user interface 303 may include a Display screen (Display), a Camera (Camera), and the optional user interface 303 may further include a standard wired interface, and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 301 may include one or more processing cores. The processor 301 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and invoking data stored in the memory 305. Alternatively, the processor 301 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 301 may integrate one or a combination of several of a central processor 301 (Central Processing Unit, CPU), an image processor 301 (Graphics Processing Unit, GPU), a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 301 and may be implemented by a single chip.
The Memory 305 may include a random access Memory 305 (Random Access Memory, RAM), or may include a Read-Only Memory 305 (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 305 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. Memory 305 may also optionally be at least one storage device located remotely from the aforementioned processor 301. As shown, the memory 305, which is a computer storage medium, may include an operating system, a network communication module, a user interface 303 module, and an application program of an engineering supervision method for a high-rise building.
In the electronic device shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 301 may be used to invoke an application in the memory 305 that stores an engineering supervision method for a high-rise building, which when executed by the one or more processors 301, causes the electronic device to perform the method as in one or more of the embodiments described above.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory 305. Based on this understanding, the technical solution of the present application may be embodied essentially or partly in the form of a software product, or all or part of the technical solution, which is stored in a memory 305, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned memory 305 includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.
Claims (10)
1. A method for engineering supervision of a high-rise building, the method comprising:
Acquiring vibration data acquired by each vibration sensor;
preprocessing a plurality of vibration data to obtain a plurality of processed data;
Comparing the difference values of a plurality of processing data of the same time node, and determining abnormal data in the plurality of processing data;
determining an abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors;
And outputting an early warning prompt to prompt a prisoner that the abnormal sensor needs to be calibrated.
2. The method for engineering supervision of a high-rise building according to claim 1, wherein the comparing the difference values of the plurality of processing data of the same time node to determine the abnormal data in the plurality of processing data specifically comprises:
According to first data acquired by each vibration sensor at a first time node and second data acquired by a second time node, determining fluctuation difference values of the first data and the second data, wherein the first time node and the second time node are any two adjacent time nodes in a plurality of times;
Determining a first difference value which is smaller than or equal to a preset difference value in the fluctuation difference values;
determining a fluctuation range according to a plurality of first sub-data, wherein the first sub-data is second data corresponding to the first difference value in a plurality of second data;
Determining a second difference value larger than the preset difference value in the fluctuation difference values;
Judging whether second sub-data is in the fluctuation range or not, wherein the second sub-data is second data corresponding to a second difference value in a plurality of second data;
And if the second sub-data is not in the fluctuation range, determining that the second sub-data is abnormal data.
3. The method for engineering supervision of a high-rise building according to claim 1, wherein after the acquisition of the vibration data collected by the respective vibration sensors, the method further comprises:
acquiring physical addresses of the vibration sensors based on a preset positioning rule;
Establishing a mapping relation between a first physical address and first vibration data, wherein the first physical address is a physical address corresponding to a first sensor, the first vibration data is vibration data acquired by the first sensor, and the first sensor is any one of a plurality of vibration sensors.
4. The method for supervising engineering of a high-rise building according to claim 3, wherein the determining an anomaly sensor corresponding to the anomaly data among the plurality of vibration sensors, specifically further comprises:
Determining a second physical address corresponding to the abnormal data according to the mapping relation, wherein the second physical address is any one physical address of a plurality of physical addresses;
and determining an abnormal sensor in the plurality of vibration sensors according to the second physical address.
5. The method for engineering supervision of a high-rise building according to claim 1, wherein after the outputting of the early warning prompt, the method further comprises:
acquiring a judgment result of the supervision personnel on the abnormal data;
If the judgment result is that the abnormal sensor is abnormal in calibration, acquiring calibration parameters which are input by the supervision personnel and aim at the abnormal sensor;
And sending the calibration parameters to the anomaly sensor.
6. The method for engineering supervision of a high-rise building according to claim 1, wherein the preprocessing of the plurality of vibration data to obtain a plurality of processed data specifically includes:
Cleaning the vibration data to remove noise values and obtain first vibration data;
performing standardization processing on the plurality of first vibration data to obtain a plurality of second vibration data in the same form;
And carrying out interpolation processing on the plurality of first vibration data to obtain a plurality of processing data.
7. The method for supervising the engineering of a high-rise building according to claim 4, wherein the outputting the early warning prompt specifically comprises:
Acquiring a BIM model of a high-rise building;
determining a model position of the anomaly sensor in the BIM model according to the second physical address;
And according to the model position, displaying the abnormal sensor in the BIM model.
8. The utility model provides an engineering supervision device of high-rise building, its characterized in that includes acquisition module (201), processing module (202), comparison module (203), sensor positioning module (204) and output module (205), wherein:
the acquisition module (201) is used for acquiring vibration data acquired by each vibration sensor;
The processing module (202) is used for preprocessing a plurality of vibration data to obtain a plurality of processing data;
the comparison module (203) is used for comparing the difference values of the plurality of processing data of the same time node and determining abnormal data in the plurality of processing data;
the sensor positioning module (204) is used for determining an abnormal sensor corresponding to the abnormal data in the plurality of vibration sensors;
and the output module (205) is used for outputting an early warning prompt to prompt a supervisor that the abnormal sensor needs to be calibrated.
9. An electronic device comprising a processor (301), a memory (305), a user interface (303) and a network interface (304), the memory (305) being adapted to store instructions, the user interface (303) and the network interface (304) being adapted to communicate with other devices, the processor (301) being adapted to execute the instructions stored in the memory (305) to cause the electronic device to perform the method according to any of claims 1-7.
10. A computer readable storage medium storing instructions which, when executed, perform the method of any one of claims 1-7.
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