Intelligent measuring tool for building electromechanical installation engineering and measuring method thereof

Abstract

The application relates to the technical field of building electromechanical installation, and discloses an intelligent measuring tool for building electromechanical installation engineering and a measuring method thereof. The system comprises a measuring environment preparation unit, a multi-parameter acquisition unit, a space topology analysis unit, an error optimization unit and a measuring verification unit. The measuring environment preparation unit acquires initial environment parameters and generates an environment parameter sequence; the multi-parameter acquisition unit synchronously captures multiple types of data, calculates a space adaptation value, and establishes an initial set of measuring characteristics; the space topology analysis unit identifies the topology connection direction of a device group and a conflict area, and generates a space topology deviation data set; the error optimization unit calculates a space positioning compensation value, and adjusts the coordinate mapping relationship of the device; and the measuring verification unit compares the deviation amount, reacquires data if necessary, and finally generates a measuring topology graph. The tool can realize the collaborative processing and accurate measurement of multiple parameters in the building electromechanical installation process, and is suitable for the field of building electromechanical installation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of building mechanical and electrical installation, in particular to an intelligent measuring tool for building mechanical and electrical installation engineering and a measuring method thereof. BACKGROUND

[0002] In building mechanical and electrical installation engineering, measurement work runs through all stages of construction, and its accuracy is directly related to the installation accuracy of equipment and the subsequent operation effect. Traditional measurement methods rely on manual operation, using basic tools such as level and theodolite to collect data. These tools are easily affected by the skill level of the operator, the site environment and other factors during operation, resulting in measurement data deviation. With the development of the construction industry, the types of mechanical and electrical equipment are increasing, and the installation space is becoming more and more complex. Traditional measurement tools can only measure single parameters and are difficult to realize the synchronous collection and correlation analysis of multiple parameters. For example, when collecting equipment positioning coordinates, environmental temperature and humidity data cannot be obtained at the same time, so that the influence of environmental factors on equipment installation is ignored, thereby affecting the accuracy of installation. The traditional measurement method lacks effective analysis of spatial topological relations. In a complex installation environment, the connection relationship between devices is complex, and it is difficult to accurately identify the topological connection direction between device groups through manual judgment, and it is also difficult to timely find the direction conflict area. This not only leads to rework in the installation process, but also may affect the overall operation performance of the mechanical and electrical system. The error correction method of traditional measurement data is relatively single, usually relying on manual experience for adjustment, lacking scientific calculation basis. When the environmental parameters fluctuate, the equipment coordinates cannot be accurately compensated according to the changes of temperature and humidity and other factors, resulting in a decrease in the reliability of the measurement results. Moreover, the traditional measurement method lacks effective feedback mechanism in the result verification link, and it is difficult to ensure the accuracy of the measurement data, which brings potential risks to the quality of building mechanical and electrical installation engineering. SUMMARY

[0003] The purpose of the present application is to provide an intelligent measuring tool for building mechanical and electrical installation engineering and a measuring method thereof to solve the problems raised in the background.

[0004] To achieve the above purpose, the present application provides an intelligent measuring tool for building mechanical and electrical installation engineering, which comprises:

[0005] A measurement environment preparation unit is used to obtain the initial environmental parameters of the building mechanical and electrical installation space, collect the space reference point coordinates according to the preset time interval and generate the environmental parameter sequence;

[0006] A multi-parameter acquisition unit synchronously captures real-time spatial coordinates of the installation area, equipment positioning coordinates, and environmental temperature and humidity data based on the environmental parameter sequence, associates the equipment type identifier of each coordinate point, calculates the spatial adaptation value of the environmental parameter and the equipment positioning, and establishes an initial set of measurement features;

[0007] A spatial topology analysis unit calls the spatial adaptation value in the initial set of measurement features, performs adjacent relationship sorting on all equipment coordinate points in the installation area, identifies the topology connection direction between equipment groups and marks the direction conflict area, and generates a spatial topology deviation data set;

[0008] An error optimization unit extracts the coordinate point sequence of the direction conflict area according to the spatial topology deviation data set, calculates a spatial positioning compensation value in combination with the temperature and humidity fluctuation feature in the environmental parameter sequence, adjusts the spatial mapping relationship of the equipment coordinate point based on the compensation value, and outputs the mechanical and electrical equipment installation spatial positioning calibration result;

[0009] A measurement verification unit compares the equipment coordinate deviation amount before and after adjustment based on the spatial positioning calibration result, and triggers the multi-parameter acquisition unit to reacquire the equipment positioning coordinates when the deviation amount exceeds a preset threshold, and finally generates a mechanical and electrical installation spatial measurement topology map.

[0010] Preferably, the initial set of measurement features includes spatial coordinate mapping relationship, environmental adaptation parameter set, and equipment type association identifier; the spatial topology deviation data set includes equipment group topology relationship chain, direction conflict area coordinate index, and adjacent equipment connection deviation value; and the spatial positioning calibration result includes compensation value adjustment parameter, coordinate mapping correction parameter, and equipment positioning verification label.

[0011] Preferably, the multi-parameter acquisition unit includes:

[0012] A spatial coordinate analysis subunit acquires a real-time spatial coordinate sequence of the installation area, identifies the positioning coordinate point of the mechanical and electrical equipment and marks the equipment type code, and acquires the environmental temperature and humidity parameters of the corresponding position of each coordinate point;

[0013] An environmental adaptation calculation subunit calls the environmental temperature and humidity parameters, calculates the environmental adaptation coefficient of each coordinate point in combination with the standard environmental range value corresponding to the equipment type code;

[0014] A feature integration subunit spatially maps and associates the equipment positioning coordinates and the environmental adaptation coefficient, records the binding relationship of the equipment type code and the coordinate point, generates an initial set of measurement features, and transmits the initial set to the spatial topology analysis unit.

[0015] Preferably, the spatial topology analysis unit includes:

[0016] The device group construction subunit constructs a device group based on the device positioning coordinates in the initial set of measurement features, performs spatial sorting on all device coordinate points based on an adjacent distance threshold, divides the device group, and establishes a group connection relationship chain;

[0017] The topology direction identification subunit extracts the spatial extension direction of each connection relationship chain in the device group, compares the direction angle values between adjacent groups, and marks the angle conflict area;

[0018] The deviation analysis subunit calculates the position offset of each coordinate point in the direction conflict area, determines the offset weight coefficient in combination with the device type association identifier, generates a spatial topology deviation data set, and transmits it to the error optimization unit.

[0019] Preferably, the error optimization unit comprises:

[0020] The environmental fluctuation extraction subunit calls the coordinate index of the direction conflict area in the spatial topology deviation data set, and extracts the temperature and humidity fluctuation amplitude value of the corresponding time node from the environmental parameter sequence;

[0021] The compensation calculation subunit calculates the spatial compensation parameter of each conflict coordinate point according to the corresponding relationship between the temperature and humidity fluctuation amplitude value and the coordinate point position offset;

[0022] The mapping adjustment subunit superimposes the spatial compensation parameter to the device positioning coordinates, updates the coordinate mapping relationship in the device group connection relationship chain, generates a spatial positioning calibration result, and transmits it to the measurement verification unit;

[0023] The spatial compensation parameter generated by the compensation calculation subunit is transmitted to the device group construction subunit; the device group construction subunit optimizes the setting range of the adjacent distance threshold according to the spatial compensation parameter.

[0024] Preferably, the measurement verification unit comprises:

[0025] The calibration comparison subunit obtains the coordinate mapping correction parameter in the spatial positioning calibration result, and compares the deviation value of the original device positioning coordinates and the corrected coordinates;

[0026] The reference point verification subunit screens the device coordinate points whose deviation value exceeds the preset threshold, marks them as to-be-verified reference points, and triggers the multi-parameter acquisition unit to reacquire the environmental temperature and humidity data of the points;

[0027] The topology reconstruction subunit updates the device group connection relationship chain based on the reacquired data, integrates all verified device coordinate points to generate a mechanical and electrical installation space measurement topology map.

[0028] Preferably, the reference point verification subunit synchronously calls the device connection deviation value in the topological deviation data set output by the space topology analysis unit when reacquiring the environment temperature and humidity data, and adjusts the environment parameter acquisition density based on the connection deviation value.

[0029] Preferably, the measurement environment preparation unit sends an environment acquisition completion instruction to the error optimization unit after generating the environment parameter sequence; and the error optimization unit starts the calculation process of the space positioning compensation value after receiving the instruction.

[0030] Preferably, the environment adaptation calculation subunit transmits the calculated environment adaptation coefficient to the topological direction identification subunit; and the topological direction identification subunit adjusts the determination threshold of the device group direction angle value in combination with the environment adaptation coefficient.

[0031] Preferably, the application further includes an intelligent measurement method for building mechanical and electrical installation engineering, which is applied to the intelligent measurement tool for building mechanical and electrical installation engineering as described above.

[0032] Step 1: Obtain the initial environment parameters of the building mechanical and electrical installation space, acquire the space reference point coordinates at a preset time interval, and generate an environment parameter sequence;

[0033] Step 2: Based on the environment parameter sequence, synchronously capture the real-time space coordinates, device positioning coordinates and environment temperature and humidity data of the installation area, associate the device type identifier of each coordinate point, calculate the space adaptation value of the environment parameters and the device positioning, and establish an initial measurement feature set;

[0034] Step 3: Call the space adaptation value in the initial measurement feature set, perform adjacent relationship sorting on all device coordinate points in the installation area, identify the topological connection direction between the device groups and mark the direction conflict area, and generate a space topological deviation data set;

[0035] Step 4: According to the space topological deviation data set, extract the coordinate point sequence of the direction conflict area, calculate the space positioning compensation value in combination with the temperature and humidity fluctuation characteristics in the environment parameter sequence, adjust the space mapping relationship of the device coordinate points based on the compensation value, and output the mechanical and electrical device installation space positioning calibration result;

[0036] Step 5: Based on the space positioning calibration result, compare the device coordinate deviation amount before and after adjustment, return to step 2 to reacquire the device positioning coordinates when the deviation amount exceeds the preset threshold, and finally generate a mechanical and electrical installation space measurement topological map.

[0037] Compared with the prior art, the application has the following beneficial effects:

[0038] The initial environment parameters are obtained and the environment parameter sequence is generated by measuring the environment preparation unit, which provides comprehensive environment basic information for subsequent measurement work. These information can reflect the environmental changes of the installation space, so that the measurement work is no longer carried out away from the actual environment.

[0039] The multi-parameter acquisition unit realizes the synchronous capture of real-time spatial coordinates, equipment positioning coordinates and environmental temperature and humidity data, and associates with the equipment type identifier, calculates the spatial adaptation value and establishes the initial set of measurement characteristics. This multi-parameter synchronous acquisition and association breaks the isolated situation of parameter acquisition in traditional measurement, and the internal relationship between various data is reflected, which can more comprehensively reflect the actual situation of equipment installation.

[0040] The spatial topology analysis unit sorts the adjacent relationship of the equipment coordinate points, identifies the topology connection direction and marks the direction conflict area, and generates the spatial topology deviation data set. This process can clearly present the spatial relationship between the equipment, so that the installer can intuitively understand the connection situation of the equipment group and the possible problem area, which helps to avoid potential connection conflicts in the installation process.

[0041] The error optimization unit calculates the spatial positioning compensation value according to the spatial topology deviation data set combined with the temperature and humidity fluctuation characteristics in the environment parameter sequence, and adjusts the spatial mapping relationship of the equipment coordinate points. This error optimization method based on data and environmental factors breaks the limitation of traditional manual experience correction, so that the adjustment of equipment coordinates is more in line with the actual environmental changes, and the accuracy of coordinate positioning is improved.

[0042] The measurement verification unit compares the equipment coordinate deviation amount before and after adjustment, and triggers reacquisition when the deviation amount exceeds the preset threshold, and finally generates the mechanical and electrical installation space measurement topology graph. This verification mechanism forms a closed loop, which can timely find and correct the problems in the measurement process, and ensure that the generated measurement topology graph is more in line with the actual installation situation, providing a reliable reference for the smooth progress of building mechanical and electrical installation engineering. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 The working principle diagram of the intelligent measurement tool for building mechanical and electrical installation engineering is described in the present application;

[0044] Figure 2 The flowchart for measurement characteristics and topology data structure is defined;

[0045] Figure 3 The flowchart for the multi-parameter acquisition unit is described;

[0046] Figure 4 The flowchart for the spatial topology analysis unit is described;

[0047] Figure 5Flowchart of the measurement verification unit. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0049] Referring to Figure 1 The present application provides an intelligent measurement tool for building mechanical and electrical installation engineering, which comprises:

[0050] The measurement environment preparation unit is started before equipment installation, obtains space temperature and humidity, air pressure basic parameters through a distributed environment sensor array, and collects 16 three-dimensional coordinates of space reference points obtained by a laser positioner at intervals of 30 seconds. The continuously collected data stream generates an environment parameter sequence according to a time stamp, and is stored as a structured data set of {time point, temperature and humidity value, reference point coordinate}. The multi-parameter acquisition unit is subsequently activated, while maintaining the environment acquisition frequency, captures the spatial coordinates (X, Y, Z) of all mechanical and electrical equipment in the region in real time through the UWB positioning module, synchronously associates the equipment type identifier corresponding to the equipment RFID tag (such as "HVAC-203"), and extracts the real-time temperature and humidity within a radius of 0.5 meters of each coordinate point. The unit calculates the adaptation degree of the actual measured value of the environment of each positioning point to the standard value (such as the operating humidity range of the power distribution cabinet 40-60%RH), and forms an initial set of measurement features containing the device positioning coordinates, the environment adaptation coefficient, and the type identifier triplet.

[0051] The spatial topology analysis unit calls the spatial adaptation coefficient of the set, first constructs a minimum spanning tree model with a device spacing of 1.2 meters as the adjacency threshold, and identifies the connection direction vector of the device group after topological sorting. When the angle between adjacent group direction vectors exceeds 15°, it is marked as a direction conflict area, records the offset of the conflict area coordinate point set and the associated equipment type weight (such as the heavy equipment weight coefficient 0.7 / light equipment 0.3), and outputs the spatial topology deviation data set containing the topology relationship chain JSON structure, the conflict area index table, and the deviation matrix. The error optimization unit extracts the conflict area coordinate sequence, combines the temperature and humidity fluctuation curve (such as ±5℃ / hour) in the corresponding time period in the environment parameter sequence, and calculates the position compensation amount δ=(material expansion coefficient x temperature change gradient x reference distance) through a thermal expansion compensation algorithm. After the compensation amount is superimposed on the original coordinates of the equipment, the coordinate mapping relationship table in the topology relationship chain is updated, and the spatial positioning calibration result containing the compensation parameter pair [original coordinate, compensation amount], the corrected coordinate value, and the verification state label is generated.

[0052] The measurement verification unit performs calibration result verification, calculates the Euclidean distance deviation before and after the coordinate correction of each device. When the pipeline connection point deviation exceeds 2mm, the multi-parameter acquisition unit is triggered to restart high-precision scanning at this point (the acquisition frequency is increased to 10Hz), and finally a BIM compatible topology graph containing all verification points is generated through topology reconstruction.

[0053] Embodiment 1: refer to Figure 2 The construction of the initial set of measurement features uses a structured data storage mechanism. The spatial coordinate mapping relationship is implemented in a dynamic relational database table, which includes device unique identification code, spatial coordinate three-dimensional value, and parent node number data items. Each device record forms an independent data row, and the spatial coordinate value record is based on the world coordinate system floating point data, accurate to 0.1 millimeter; the parent node number maintains the device level attribution information, establishing a device position topology network. The data table is updated in real time, and when a new device positioning coordinate is added, a topology connection relationship index is automatically generated.

[0054] The environmental adaptation parameter set is stored in the in-memory database in the form of a key-value pair set, with the key name being the device unique identification code and the key value being the environmental adaptation coefficient of the device. When calculating the adaptation coefficient, the device type database is retrieved to obtain the corresponding standard parameters: for heating and ventilation devices, the humidity standard threshold range [Min, Max] is extracted, and for electrical devices, the temperature allowed interval [T_min, T_max] is extracted. After the measured temperature and humidity values are input, difference operation is performed: the average value of the three temperature and humidity sensors within a radius of 0.5 meters of the device coordinate point at the current timestamp is obtained, and the average value is subtracted from the midpoint of the standard range. Finally, the normalized coefficient value is output (when the measured value is at the midpoint of the standard interval, the coefficient is 1.0, and when it deviates from the standard boundary, it decreases linearly to 0).

[0055] The device type association identifier uses a composite encoding format. The first character is the device main class code: the capital letter H represents heating and ventilation devices, P represents pipeline devices, and E represents electrical power devices. The following six digits are composed of three segments: the first two digits identify the device subclass (such as 01 for air supply unit / 02 for fresh air unit), the middle two digits represent the installation area number, and the last two digits are the serial number. The code is injected into the device tag through the RFID reader, and is automatically associated with the device record during the spatial coordinate analysis process. When the device position is updated, the type identifier is migrated synchronously with the coordinate data.

[0056] The core elements of the spatial topology deviation dataset are organized by three types of data structures. The device group topology relationship chain is stored in a graph structure: the node set saves the device unique identification code, and the edge set records the connection relationship between devices. The attribute of each edge stores a three-dimensional spatial vector [x, y, z] as the connection direction vector, and records the angle value (unit: degree) of the direction with the theoretical direction of the design drawing. The coordinate index of the direction conflict area is implemented by a spatial hash table: the installation space is divided into 0.5x0.5x0.5 cubic cells, and when there are direction conflict devices in a certain cell, the hash value of the cell is added to the index table. The index value is associated with the conflict detail record, including the conflict device identification code list, the direction angle deviation value, the conflict duration, etc. The adjacent device connection deviation value matrix is stored in the form of a symmetric matrix: the row and column indexes of the matrix correspond to the device number, and the matrix elements record the absolute difference (unit: millimeter) between the actual measured device distance and the engineering design value. The diagonal elements of the matrix store the state code of the device's own coordinate verification, and the non-diagonal elements record the relative position error between the physically connected devices.

[0057] The spatial positioning calibration result is composed of three types of parameters. The compensation value adjustment parameter is stored as an object array, and each element contains the device identification code, the three-axis compensation displacement amount, and the compensation calculation timestamp. The compensation amount record is based on the world coordinate system floating point offset value, and the sign indicates the displacement direction. The coordinate mapping correction parameter is stored in an independent transaction table, and a new record is generated for each compensation operation: the original coordinate value is stored as an eight-byte floating-point number, the corrected coordinate value is recalculated according to the new space mapping model, and the correction operator identification and correction trigger condition code are also recorded. The device positioning verification label adopts a state machine management mode, including four states of initial unverified, compensation pending confirmation, manual verification, and automatic verification passed. Each label is associated with the device coordinate correction history record, and stores at least the timestamp and deviation calculation result of the latest three verification operations. When the device moves more than the preset range, the system automatically resets the verification state and triggers the alarm protocol.

[0058] The data flow mechanism establishes a multi-level transmission channel. After the spatial topology deviation data set is generated, it is transmitted to the compensation calculation module through a dedicated message middleware. The message body contains the graph structure serialization data of the device group topology relationship chain, the hash value list of the direction conflict area coordinate index, and the compressed binary format of the adjacent device connection deviation value matrix. When the receiving end module parses the message, it automatically reconstructs the matrix data into a memory calculation model. The environment adaptation parameter set is updated after each temperature and humidity collection period, and the change data is notified to the topology analysis module through the publish / subscribe mode. When the device type association identifier changes, the system automatically rebuilds the spatial coordinate mapping relationship table and broadcasts the device identifier change event to all associated modules. The topology analysis module performs incremental update every five minutes, reconstructs the device group topology relationship chain based on the newly collected data, recalculates only the direction vector on the path related to the changed device, and distinguishes the data update state by version number. The calibration result database implements a transaction lock mechanism to ensure the atomicity of the compensation value writing and coordinate correction operation. A data snapshot is generated after each calibration result is submitted, which contains the coordinate state of all devices at that time, the environment adaptation coefficient state, and the topology relationship checksum, which is used for the reference comparison operation of the measurement verification unit.

[0059] Example 2: see Figure 3 The implementation of the multi-parameter collection unit relies on a three-layer data processing architecture. The spatial coordinate analysis subunit constructs a spatial coordinate system network by deploying four groups of ultra-wideband positioning base stations on the top of the building. The base stations transmit coded pulse signals at a frequency of 100 times per second. The electromechanical device carrying a miniature response tag returns a response containing the device serial number after receiving the signal. The system calculates the three-dimensional position coordinates of the device by the time difference of arrival algorithm. The solving process uses an adaptive filtering algorithm to eliminate multipath effect interference. The position data output is a three-element data group containing millisecond-level timestamps, decimal device serial numbers, and double-precision floating-point coordinate values. The device type code is pre-set by the embedded chip. When the spatial coordinate analysis subunit obtains the device serial number, it synchronously extracts the 32-bit type code string from the device registration database.

[0060] The environmental temperature and humidity collection is implemented by a distributed sensor array. The installation area space is divided into 0.5-meter-long standard cubic grids in length, width, and height directions, and an environmental sensor with a protective shell is deployed at the center of each grid. Each sensor is configured with an independent MAC address and forms a network through low-power Bluetooth, uploading environmental data packets every 500 milliseconds. The packet data structure includes a six-byte grid number, a single-precision floating-point temperature value, a single-precision floating-point humidity value, and a check code. The sensor array initializes to establish a global index table of grid coordinates, which records the absolute position of the grid center point in the world coordinate system.

[0061] The environmental adaptation computing subunit runs on the edge computing node. The node maintains a standard parameter knowledge base to store environmental threshold parameters indexed by device type code. When inputting specific device data, the subsystem performs a query process: the first three characters of the device type code are mapped to the device category, and the subsequent number field matches the specific model parameter table. For example, the device type code "H010203" is parsed as: category "heating and ventilation equipment", subclass "01 fan coil", model "02-C type", corresponding temperature standard interval [16.0, 26.0] ℃, humidity interval [40, 60]%. The adaptation coefficient calculation uses real-time interpolation method: the system retrieves environmental data of the grid where the device coordinate point is located, and if the device is located at the intersection of multiple grids, the weighted average of the data of the three nearest grids is taken. The temperature adaptation value calculation formula is a relative position function, and the function output is a linear mapping coefficient.

[0062] The feature integration subunit constructs a spatial mapping matrix. When the subunit receives a device spatial coordinate data stream, it first queries the grid index table based on the coordinate value to determine the main belonging grid. When the device is close to the grid boundary, a spherical influence area is set up to calculate the contribution weight of each grid data. When the environmental adaptation coefficient is combined with the device spatial position, the device coordinate system data record is generated: a four-dimensional vector containing the device serial number, double-precision coordinate value, 32-bit type code, and single-precision adaptation coefficient is established. These vectors are stored in distributed database partitions, and each partition manages a device data set with a space range of five cubic meters.

[0063] Data transmission is achieved through the message queue mechanism. The feature integration subunit encapsulates the generated device data record into a JSON format message and injects it into the message broker server. The message header contains metadata such as generation time, device quantity, and spatial region code, and the data segment arranges all device four-dimensional feature vectors in order. The spatial topology analysis unit subscribes to the message queue of the specified topic and immediately parses the JSON message to reconstruct the device feature set after receiving it. The message queue sets a priority channel, and when the adaptation coefficient is less than 0.3, the transmission priority is automatically promoted.

[0064] The time synchronization system adopts a three-layer architecture. The positioning base station group obtains standard time through GPS receivers, the environmental sensor array is time-synchronized through the Bluetooth master node, and the computing nodes use the NTP protocol to synchronize the clock. The time stamps of all collected data records are based on a unified clock source, ensuring the time alignment of data from different sources. Each data message carries the time reference value of the source device, and the receiving end automatically compensates for network transmission delay.

[0065] The abnormal handling mechanism sets multiple threshold values. When the device fails to solve the problem and times out, the spatial coordinate analysis subunit automatically increases the number of attempts to five; when the environmental sensor reads out of range, it triggers temporary sampling frequency to increase to ten times per second. In the case of missing device type code, the system interpolates and infers the category information of the nearest three devices based on the device spatial position.

[0066] The device initialization process includes three states. The newly added device first locates into the identification mode: the system records the device serial number and marks it as a to-be-registered state; when the environmental adaptation calculation unit fails to query the device type code, it automatically sends a registration request to the central database; after successful registration, it enters the verification mode, at which time the device coordinates and environmental data are temporarily stored in the cache area; after the stable results are collected for three times in succession, the device enters the running mode and is allocated a storage partition address.

[0067] The data persistence processing follows a specific protocol. The spatial coordinate analysis subunit writes the original coordinate data into the time series database every 30 seconds, and the environmental temperature and humidity data are stored in batches every minute. The feature integration subunit backs up the device feature set processed to the distributed file system in real time, while retaining the current ten-minute window data in the memory cache. When the environmental adaptation calculation unit detects that the data fluctuation amplitude exceeds the standard, it automatically extends the cache time until the fluctuation ends.

[0068] Type code change executes a linkage update. When the device registration information is modified, the central database broadcasts a change event message. After the feature integration subunit listens to the event, it retrieves the local device set, matches the serial number, and immediately performs code update. The update operation records a log track, including the original code, the new code, the change time, and the operator information. The adaptation coefficient calculation of the device is suspended during the change process, and the parameter table is reloaded after the new code is confirmed.

[0069] The environmental sensor calibration module runs periodically. Every six hours, the automatic calibration program is activated: the sensor array starts the standard source reference mode, and the master node sends standard temperature and humidity reference values to the specified grid. When the deviation of each sensor reading from the reference value exceeds the preset range, a compensation coefficient table is automatically generated. The compensation value is applied to subsequent data collection, and each compensation operation is recorded in the device operation and maintenance log.

[0070] Example 3: refer to Figure 4 The device group construction subunit of the spatial topology analysis unit adopts a progressive spatial clustering method. Initially, all device positioning coordinate points are scanned, and an original point set containing the three-dimensional coordinates of each device point and a unique identification code is established. The basic adjacent distance threshold is set to 1.2 meters, and range search is performed through a spatial index tree structure: taking any device point as the center, the nearby points within a radius of 1.2 meters are retrieved. When two device points are located within each other's search radius, a bidirectional connection relationship is established, and the spatial vector information of the connection line segment is recorded. Group division is based on the connected graph principle, and the mutually connected point sets are classified into the same group, and a global group identifier is assigned to each group. The group connection relationship chain is stored in the graph database format, and the node attributes include the three-dimensional coordinates of the device and the type code, and the edge attributes store the measured distance value and the spatial direction angle.

[0071] The topological direction recognition sub-unit runs the direction consistency detection algorithm. After receiving the device group data, the unit first calculates the group principal axis direction: select the two device points with the largest distance in the group as the direction reference endpoints, and the line connecting the two points forms a space vector V. The direction alignment of other device points in the group is verified, and a local coordinate system is established to calculate the cosine value of the position vector of each point and the vector V. When more than 15% of the device points in the group have a cosine value less than 0.85, mark the group as an internal unstable group. The relationship between groups is analyzed using the boundary point interaction verification mechanism. When the distance between the nearest boundary points of adjacent groups is less than a threshold, perform direction comparison: draw the convex hull cut plane of the two groups, and calculate the dot product value of the plane normal vectors. When the dot product result is less than a set threshold for three consecutive sampling periods, a direction conflict area record is established. The area boundary coordinates are automatically generated by the convex hull algorithm, and the conflict type level and duration parameters are recorded.

[0072] The bias analysis sub-unit activates the displacement monitoring function after identifying the conflict area. The unit constructs a reference coordinate system: taking the theoretical position point of the design drawing as the origin, a local rectangular coordinate system is established. For each device point in the conflict area, calculate the Euclidean distance offset between the current coordinates and the theoretical position, and record the X and Y direction component values in the horizontal plane projection. The device type association identifier is used to determine the weight coefficient distribution rule: the base weight of heavy equipment is 0.7, the weight of pipe connection points is 0.9, and the weight of light equipment is 0.4. A time decay factor is introduced in the weighted offset calculation formula, and the recent offset weight is increased by 20%. Finally, the offset feature table is generated: the row records the conflict area number, the column is divided by the device type, and the cell stores the weighted average offset value and its standard deviation.

[0073] The environmental fluctuation extraction sub-unit of the error optimization unit deploys a time series matching engine. The engine locates the affected environmental sensor nodes according to the conflict area coordinate index provided by the spatial topology analysis unit. A three-layer time alignment mechanism is established: extract the temperature and humidity records within ±200ms of the device coordinate collection time from the environmental parameter sequence, and use cubic spline interpolation to fill in the missing data. The temperature fluctuation feature calculation uses the difference method to compare the temperature gradient change in adjacent time windows; the humidity fluctuation record is the relative humidity percentage change rate. The environmental influence degree of a specific device point is determined by the data of the three nearest sensors, and the weight coefficients are inversely proportional to the spatial distance between the device and the sensor.

[0074] The compensation calculation sub-unit runs the material deformation prediction model. The core algorithm of the model is based on the principle of thermal expansion, and the calculation formula of the device position compensation δ is:

[0075]

[0076] In the formula: represents the linear expansion of the object (change in length). The coefficient of linear expansion of a material (usually measured in units of 1000 ppm) or ); The original length of an object; The change in temperature ( The formula (i.e., the difference between the initial and final temperatures) is a fundamental calculation formula for thermal expansion, used to quantitatively calculate the change in length of a solid due to temperature changes.

[0077] The mapping adjustment subunit implements spatial coordinate transformation matrix operations. The original device coordinates [X,Y,Z] undergo affine transformation for displacement compensation: a 4×4 transformation matrix is ​​established, where the translation component is set to the three components of the compensation vector. The transformed new coordinates [X',Y',Z'] are written to the device spatial attribute table, while a copy of the original coordinates is retained for verification. Group connection chains are synchronously updated: the adjusted device spacing values ​​are recalculated, and the connection status markers in the relationship chain are updated when the spacing change exceeds 3%. The topology relationship data version number is automatically incremented, and new version relationship chains are marked with a "pending verification" status.

[0078] A dynamic feedback mechanism for spatial compensation parameters establishes a two-way data channel. Each time the compensation calculation subunit completes the compensation calculation for a batch of equipment, it immediately pushes a parameter update package to the equipment group construction subunit. The update package uses a binary encoding format: the first four bytes identify the equipment group number, the following twelve bytes store the floating-point numbers of the three-axis compensation components, and the last byte is a compensation reliability flag. After parsing the parameter package, the equipment group construction subunit dynamically adjusts the adjacent distance threshold calculation rules: the basic threshold is adjusted according to T=1.2+k×|δ|, where k is the compensation sensitivity coefficient, with a default value of 0.3; when the compensation amount of heavy equipment |δ|>0.5mm, its surrounding adjacent judgment radius shrinks to 80% of the original value. Threshold changes are recorded in the group construction configuration table, and the new parameters are automatically loaded during the next topology reconstruction. The equipment group boundary judgment algorithm adds a compensation amount verification step: when the dot product of the compensation vectors of two equipment points is negative, it is forcibly marked as a potential conflict point for pre-diagnostic analysis.

[0079] Example 4: See Figure 5 The execution flow of the measurement verification unit begins with the data receiving stage of the calibration comparison subunit. This subunit obtains the spatial positioning calibration result dataset from the error optimization unit. This dataset contains three core data blocks: the original coordinate matrix of the equipment, the corrected coordinate matrix, and the compensation parameter vector. After the verification engine starts, it loads the baseline parameter configuration: the preset coordinate deviation threshold is 2.0 mm, the special threshold for pipe connection points is 1.5 mm, and the electrical cabinet positioning threshold is relaxed to 3.0 mm.

[0080] The benchmark point verification subunit scans the equipment verification state table and identifies the equipment record with excessive deviation. When the value of a certain equipment D exceeds the threshold value of the corresponding type, the equipment is marked as "benchmark point to be verified", triggering a three-level response protocol: first, the icon is marked with a red flash in the spatial topology map; at the same time, send instruction code 0xB3 to the multi-parameter acquisition unit; finally, lock the equipment coordinate point within a range of 0.8 meters as a high-priority acquisition area. The multi-parameter acquisition unit switches to the working mode after responding: for general equipment points, start the standard review process (sampling frequency 10 Hz), and for pipe connection points, activate the precision scanning scheme (sampling frequency 100 Hz). The environmental temperature and humidity acquisition is enhanced synchronously, and six sensors deployed around the target point are started synchronously, uploading 20 sets of environmental parameters per second.

[0081] After receiving the re-acquired equipment data set, the topology reconstruction subunit executes the topology relationship reconstruction algorithm. The algorithm first compares the coordinate difference between the old and new equipment, and confirms the stable state when the coordinate fluctuation of three consecutive acquisitions is less than 0.1 mm. The device connection relationship verification adopts the principle of spatial proximity: all pairs of devices with a distance less than 1.5 meters are retrieved, and their connection state is verified to see if it meets the engineering design specifications. After verification, the device state label is updated, and the topology map is displayed in green solid model. The final generated electromechanical installation space measurement topology map adopts a multi-layer data structure: the bottom layer stores the equipment spatial coordinate index, the middle layer records the device interconnection relationship table, and the surface rendering layer outputs the three-dimensional visualization model.

[0082] The environmental parameter compensation function is most evident in the electrical area: a group of power distribution cabinets still produces 0.8-1.2 mm fluctuation after coordinate correction. The benchmark point verification subunit analyzes historical data and finds that the environmental temperature changes by 4°C per hour, immediately starts the temperature and humidity compensation protocol: increases the environmental sampling frequency to 10 times per second, and adds the temperature change rate as a weight factor to the coordinate filtering algorithm. The data of three consecutive acquisition periods shows that the Y-axis position of the cabinet body shifts 0.2 mm for every 1°C temperature rise, and the system establishes a dynamic compensation model accordingly. The temperature drift component is automatically deducted during subsequent coordinate acquisition, which improves the stability of the equipment coordinate to ±0.3 mm, and finally passes the topology verification.

[0083] After the entire verification period is completed, the topology map generation module performs final rendering: verified equipment is displayed as a green solid model; equipment to be verified remains in a red flashing state; newly added unverified equipment is displayed as a yellow semi-transparent icon. Physical connection relationships are distinguished by different color bands: black solid lines represent verified rigid connections, blue dashed lines represent flexible connections to be verified, and red wavy lines represent connection conflicts. The output topology map includes a spatial coordinate grid auxiliary layer, with each grid representing an actual distance of 500 mm, which is convenient for construction personnel to compare and measure on site.

[0084] Example 5: The fiducial point verification subunit executes dynamic sampling control logic. When the specific device connection bias value exceeds 1.5 millimeters in three consecutive acquisition cycles, the device coordinate point is marked as a high sensitivity area. The system automatically activates the environmental acquisition density improvement protocol: a three-dimensional space area with a radius of 2 meters is established with the target device as the center, and the communication parameters of the sensor nodes deployed in the area are reset. The default acquisition density is four monitoring points per cubic meter, and after upgrading, the node spacing is reduced to 50% of the original configuration, forming sixteen data acquisition points per cubic meter. The node reconfiguration process includes three-stage operation: first, release the original Bluetooth low-power network connection, second, redistribute the communication time slots and channels, and finally establish a high-speed data transmission channel. The sensor sampling frequency is increased from two times per second to ten times, and the data stream bandwidth occupancy is automatically expanded by three times. This state is maintained until the device coordinate fluctuation value is below the warning threshold for six consecutive acquisitions, and the standard density configuration is restored.

[0085] The measurement environment preparation unit sends a state instruction frame to the message bus after completing the environmental parameter sequence acquisition. The instruction frame format uses binary encoding rules: the first byte is fixed as 0xAA identifier, the second byte records the total time length of the sequence, and the subsequent bytes store the fiducial point check code. The error optimization unit continuously monitors the 0xAA instruction channel and immediately completes three-step response after receiving the instruction: suspend the coordinate compensation calculation thread; call the latest environment parameter snapshot to load into the cache; activate the compensation calculation main process. The time synchronization mechanism ensures the time sequence consistency of instruction reception and environment data update - the error optimization unit checks the time stamp of the last frame of the environment sequence, and only when the time difference is less than 50 milliseconds, the calculation process is started.

[0086] The environment adaptation calculation subunit transmits the real-time generated environment adaptation coefficient to the topology direction recognition system. The transmission channel uses shared memory mapping method, and the coefficient data set is updated every millisecond. After receiving the coefficient data, the topology direction recognition unit establishes the association rule between the coefficient and the direction determination threshold. The default direction angle determination threshold is 0.85 dot product value, and when the environment adaptation coefficient is less than 0.6, the threshold adaptive adjustment protocol is triggered: calculate the new threshold parameter K = 0.75 + (η - 0.6) x 0.2, where η is the real-time adaptation coefficient. The system maintains a dual coefficient coexistence verification mechanism, which retains the historical records of the last five cycles while receiving new adaptation coefficients, and delays the threshold adjustment operation when the single coefficient change amplitude exceeds 0.15 until the fluctuation is stable.

[0087] The device type change response flow sets a special processing queue. When the spatial coordinate analysis subunit detects a device type code update, it immediately sends a change event to the feature integration subunit and the environment adaptation calculation subunit. The feature integration subunit retrieves all pending data buffers within five milliseconds, and the data set containing the device serial number is immediately suspended for processing. The environment adaptation calculation subunit synchronously clears the adaptation coefficient cache of the related device and requests the threshold table corresponding to the new type code from the parameter standard library. The data transmission interruption protection mechanism intervenes: the environment data generated during the change is temporarily stored in an independent buffer, and after the new type code is confirmed, it is re-injected into the processing flow.

[0088] The calibration instruction delivery path configures three check nodes. The environment ready instruction issued by the measurement environment preparation unit is split into four data packets at the transmission layer, and each packet is attached with a CRC-32 check code. The receiving module of the error optimization unit detects the data packet order and integrity, and single packet error triggers a single packet retransmission mechanism. After the data is finally integrated, a checksum is executed for verification, and if the verification fails, the sending end is requested to resend the complete instruction frame. The instruction transmission timeout threshold is set to three seconds, and the timeout event triggers the measurement environment preparation unit to automatically restart the instruction sending sequence.

[0089] The time synchronization system establishes a hierarchical time calibration scheme in the environment data acquisition link. The spatial reference point coordinate acquisition device obtains the reference clock through the satellite timing module, with an error less than ten microseconds. The environment sensor array maintains time synchronization through a distributed phase-locked loop system, and the main controller sends a time correction pulse every ten seconds. The data receiver of the multi-parameter acquisition unit sets a clock offset compensation algorithm, automatically calculates the transmission delay of each sensor node and corrects the time stamp. The collection time of all data records is accurate to the millisecond level, and the maximum clock difference between different subsystems is controlled within twenty milliseconds.

[0090] The device abnormal state switching process includes a stable monitoring period. After the newly registered device enters the verification mode, it starts continuous monitoring, recording a group of coordinates and environment data every five seconds. The state conversion system analyzes the standard deviation of the last fifteen groups of data, and when the coordinate fluctuation is less than zero point one millimeter and the environment adaptation coefficient standard deviation is less than zero point zero five, it automatically approves the device to enter the running mode. The state switching event triggers the resource allocation operation: the device is allocated a permanent storage partition address, a topology analysis queue index is added, and a real-time compensation monitoring channel is opened. The data storage period of the running mode device is migrated from the temporary buffer to the persistent database, and a complete data archiving chain is established.

[0091] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude myriad other embodiments of the present application that other inventors can develop based on the same general inventive concepts embodied by the described embodiments. That is, although the present application is described in terms of particular embodiments and illustrative figures, it should be apparent that the scope of the present application is not limited to these specific embodiments.

[0092] While the embodiments of the application have been shown and described herein, it will be understood by those skilled in the art that many changes, modifications, substitutions and alterations to these embodiments can be made without departing from the principles and spirits of the application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent measuring tool for building electromechanical installation works, characterized in that, The method comprises the following steps: A measurement environment preparation unit is used to obtain initial environmental parameters of a building mechanical and electrical installation space, collect space reference point coordinates at a preset time interval, and generate an environmental parameter sequence; A multi-parameter acquisition unit is used to capture real-time space coordinates, equipment positioning coordinates, and environmental temperature and humidity data of the installation area based on the environmental parameter sequence, associate the equipment type identifier of each coordinate point, calculate the space adaptation value of the environmental parameters and equipment positioning, and establish an initial set of measurement characteristics; A space topology analysis unit is used to call the space adaptation value in the initial set of measurement characteristics, perform adjacent relationship sorting on all equipment coordinate points in the installation area, identify the topology connection direction between equipment groups and mark the direction conflict area, and generate a space topology deviation data set; An error optimization unit is used to extract the coordinate point sequence of the direction conflict area based on the space topology deviation data set, calculate the space compensation parameter combined with the temperature and humidity fluctuation characteristics in the environmental parameter sequence, adjust the space mapping relationship of the equipment coordinate points based on the compensation parameter, and output the mechanical and electrical equipment installation space positioning calibration result; A measurement verification unit is used to compare the equipment coordinate deviation amount before and after adjustment based on the space positioning calibration result, trigger the multi-parameter acquisition unit to reacquire the equipment positioning coordinates when the deviation amount exceeds the preset threshold, and finally generate a mechanical and electrical installation space measurement topology map; The error optimization unit comprises: An environmental fluctuation extraction subunit is used to call the coordinate index of the direction conflict area in the space topology deviation data set, and extract the temperature and humidity fluctuation amplitude value of the corresponding time node from the environmental parameter sequence; A compensation calculation subunit is used to calculate the space compensation parameter of each conflict coordinate point based on the corresponding relationship between the temperature and humidity fluctuation amplitude value and the coordinate point position offset; A mapping adjustment subunit is used to add the space compensation parameter to the equipment positioning coordinates, update the coordinate mapping relationship in the equipment group connection relationship chain, generate a space positioning calibration result, and transmit it to the measurement verification unit; The space compensation parameter generated by the compensation calculation subunit is transmitted to the equipment group construction subunit; the equipment group construction subunit optimizes the setting range of the adjacent distance threshold based on the space compensation parameter.

2. The intelligent measuring tool for mechanical and electrical installation works in buildings as claimed in claim 1, wherein: The initial set of measurement characteristics includes space coordinate mapping relationship, environmental adaptation parameter set, and equipment type association identifier; the space topology deviation data set includes equipment group topology relationship chain, direction conflict area coordinate index, and adjacent equipment connection deviation value; The space positioning calibration result includes compensation value adjustment parameter, coordinate mapping correction parameter, and equipment positioning verification label.

3. The intelligent measuring tool for building electromechanical installation engineering according to claim 1, characterized in that: The multi-parameter acquisition unit comprises: A space coordinate analysis subunit is used to obtain the real-time space coordinate sequence of the installation area, identify the positioning coordinate points of the mechanical and electrical equipment and mark the equipment type code, and collect the environmental temperature and humidity parameters of the corresponding positions of each coordinate point; An environmental adaptation calculation subunit is used to call the environmental temperature and humidity parameters, calculate the environmental adaptation coefficient of each coordinate point combined with the standard environmental range value corresponding to the equipment type code; The feature integrator unit is configured to map and associate device positioning coordinates with environmental adaptation coefficients, record the binding relationship between device type codes and coordinate points, and generate an initial set of measurement features and transmit the initial set to the spatial topology analysis unit.

4. The intelligent measuring tool for building electromechanical installation engineering according to claim 3, characterized in that: The spatial topology analysis unit comprises: The device group construction unit is configured to sort all device coordinate points in the initial set of measurement features based on device positioning coordinates and a neighbor distance threshold, divide device groups, and establish group connection relationship chains; The topology direction identification unit is configured to extract the spatial extension direction of each connection relationship chain in a device group, compare the direction angle values between adjacent groups, and mark angle conflict areas; The deviation analysis unit is configured to calculate the position offset of each coordinate point in the direction conflict area, determine an offset weight coefficient in combination with a device type association identifier, generate a spatial topology deviation data set, and transmit the data set to the error optimization unit.

5. The intelligent measuring tool for mechanical and electrical installation works according to claim 1, characterized in that: The measurement verification unit comprises: The calibration comparison unit is configured to obtain coordinate mapping correction parameters in the spatial positioning calibration result, compare the deviation values of original device positioning coordinates and corrected coordinates, and mark the coordinates as to-be-verified reference points when the deviation values exceed a preset threshold. The reference point verification unit is configured to trigger the multi-parameter acquisition unit to reacquire environmental temperature and humidity data of the to-be-verified reference points. The topology reconstruction unit is configured to update device group connection relationship chains based on the reacquired data, and integrate all verified device coordinate points to generate a mechanical and electrical installation space measurement topology map.

6. The intelligent measuring tool for building electromechanical installation engineering according to claim 5, characterized in that: The reference point verification unit is configured to synchronize the device connection deviation values in the topology deviation data set output by the spatial topology analysis unit when reacquiring environmental temperature and humidity data, and adjust the environmental parameter acquisition density based on the connection deviation values.

7. The intelligent measuring tool for mechanical and electrical installation works according to claim 1, characterized in that: The measurement environment preparation unit is configured to send an environmental acquisition completion instruction to the error optimization unit after generating an environmental parameter sequence.

8. The intelligent measuring tool for building electromechanical installation engineering according to claim 4, characterized in that: The environmental adaptation calculation unit is configured to transmit the calculated environmental adaptation coefficients to the topology direction identification unit.

9. An intelligent measuring method for building mechanical and electrical installation engineering, applied to the intelligent measuring tool for building mechanical and electrical installation engineering according to any one of claims 1 to 8, characterized in that, The method comprises: Step 1: Obtain initial environmental parameters of a building mechanical and electrical installation space, acquire space reference point coordinates at a preset time interval, and generate an environmental parameter sequence; Step 2: Based on the environmental parameter sequence, simultaneously capture real-time space coordinates, device positioning coordinates, and environmental temperature and humidity data of an installation area, associate device type identifiers of each coordinate point, calculate spatial adaptation values of environmental parameters and device positioning, and establish an initial set of measurement features; Step 3: Call the spatial adaptation values in the initial set of measurement features, perform neighbor relationship sorting on all device coordinate points in the installation area, identify the topology connection direction between device groups, mark direction conflict areas, and generate a spatial topology deviation data set; Step 4: According to the spatial topological deviation data set, the coordinate point sequence of the direction conflict area is extracted, the space compensation parameters are calculated combined with the temperature and humidity fluctuation characteristics in the environmental parameter sequence, the spatial mapping relationship of the equipment coordinate points is adjusted based on the compensation value, and the mechanical and electrical equipment installation space positioning calibration result is output; Step 5: Based on the spatial positioning calibration result, the equipment coordinate deviation before and after adjustment is compared, and when the deviation exceeds the preset threshold, step 2 is returned to reacquire the equipment positioning coordinates, and finally the mechanical and electrical installation space measurement topological graph is generated.

Images