A construction supervision system based on big data analysis

Abstract

The present invention relates to the field of construction engineering, and specifically to a construction engineering construction supervision system based on big data analysis, which is used to solve the problems of low efficiency, untimely information and inaccurate data in traditional construction engineering construction supervision methods, resulting in low precision and efficiency of construction engineering construction supervision, affecting construction efficiency, reducing quality level, and even construction risks; the system includes a construction environment supervision module, a construction information analysis module, a construction abnormality judgment module, a safe construction supervision module and a construction equipment supervision module; the system adopts the Internet of Things technology to realize the real-time collection and transmission of construction site data, improves the real-time and accuracy of data, and uses big data analysis technology to deeply mine and analyze the construction environment and equipment status, improves the precision and efficiency of supervision, improves construction efficiency and quality level, ensures project quality, reduces construction costs, and improves user experience.

Description

Technical Field

[0001] The present invention relates to the field of construction engineering, and in particular to a construction engineering supervision system based on big data analysis. Background Art

[0002] With the acceleration of urbanization, the scale and complexity of construction projects are increasing, and the difficulty of supervision during the construction process is also increasing. With the rapid development of the construction industry, the supervision requirements for the construction environment and construction equipment are increasing. When the construction environment and construction equipment of a construction project are abnormal, it may not only threaten the health of construction workers and surrounding residents, but also affect the construction quality, efficiency and cost. The traditional construction environment and equipment supervision methods mainly rely on manual inspections and static data analysis, which are inefficient, untimely, and inaccurate. This leads to low accuracy and efficiency in construction supervision, affecting construction efficiency, reducing quality levels, and even construction risks. Therefore, developing a construction supervision system for construction projects based on big data analysis is of great significance for improving supervision efficiency, ensuring construction safety, and reducing construction costs. Summary of the invention

[0003] In order to overcome the above-mentioned technical problems, the purpose of the present invention is to provide a construction project construction supervision system based on big data analysis, which solves the problems of low efficiency, untimely information and inaccurate data in traditional construction project construction supervision methods, resulting in low accuracy and efficiency of construction project construction supervision, affecting construction efficiency, reducing quality levels, and even construction risks.

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] A construction project supervision system based on big data analysis, comprising:

[0006] The construction environment monitoring module is used to collect data on the construction environment of the construction area o, obtain the construction environment monitoring data of the construction area o, and send the construction environment monitoring data to the construction information analysis module; wherein the construction environment monitoring data includes air information KQ, sound intensity information SQ and ground information DM;

[0007] The construction information analysis module is used to obtain the construction environment supervision coefficient SHo according to the construction environment supervision data, and send the construction environment supervision coefficient SHo to the construction abnormality judgment module;

[0008] The specific process of the construction information analysis module obtaining the construction environment supervision coefficient SHo is as follows:

[0009] The air information KQ, the sound intensity information SQ and the ground information DM are normalized, and the values ​​of the air information KQ, the sound intensity information SQ and the ground information DM are quantified according to the preset construction environment supervision model to obtain the construction environment supervision coefficient SHo, and the construction environment supervision coefficient SHo is sent to the construction abnormality judgment module;

[0010] The construction environment supervision model is as follows: Where:

[0011] γ is the preset error adjustment factor, and γ=1.208 is taken;

[0012] π and e are both mathematical constants;

[0013] h1, h2 and h3 are preset weight factors corresponding to the set air information KQ, sound intensity information SQ and ground information DM respectively, h1, h2 and h3 satisfy h1>h3>h2>1.329, h1=2.44, h2=1.61, h3=1.95;

[0014] The construction abnormality judgment module is used to obtain the abnormal environment area according to the construction environment supervision coefficient SHo, generate an abnormal environment instruction, and send the abnormal environment area and abnormal environment instruction to the safe construction supervision module;

[0015] The safe construction supervision module is used to sound the environmental alarm bell upon receiving an environmental abnormality instruction, and send the environmental abnormality area to the terminal of the construction supervision manager.

[0016] As a further solution of the present invention: the specific process of the construction environment supervision module obtaining the construction environment supervision data is as follows:

[0017] The construction area of ​​the building project is randomly divided into several sub-areas, and they are marked as construction areas o, o=1, ..., v, v is a positive integer, o is the number of any construction area, and v is the total number of construction areas;

[0018] Collect data on the construction environment of construction area o, obtain the dust content and volatile organic matter content in the air environment of construction area o, and mark them as dust value HC and volatile value HF respectively, quantify the dust value HC and volatile value HF, extract the values ​​of dust value HC and volatile value HF, and substitute them into the formula for calculation. The air information KQ is obtained; wherein k1 and k2 are preset proportional coefficients corresponding to the set dust value HC and volatility value HF, respectively, k1 and k2 satisfy k1+k2=1, 0<k2<k1<1, k1=0.66, k2=0.34;

[0019] Get the real-time sound intensity in the construction area o and mark it as the real sound value SS, get the maximum real sound value SS per unit time and mark it as the maximum sound value ZS, get the preset real sound threshold SSy, get the total duration of the real sound value SS ≥ the real sound threshold SSy and mark it as the sound duration ST, quantify the maximum sound value ZS and the sound duration ST, extract the values ​​of the maximum sound value ZS and the sound duration ST, and substitute them into the formula for calculation. The sound intensity information SQ is obtained; wherein s1 and s2 are preset proportional coefficients corresponding to the set maximum sound value ZS and the sound time value ST, respectively, s1 and s2 satisfy s1+s2=1, 0<s1<s2<1, and s1=0.23 and s2=0.77;

[0020] Obtain the ground hardness and ground water content of the construction area o, and mark them as ground hardness value DY and ground water value DS respectively, quantify the ground hardness value DY and ground water value DS, extract the values ​​of ground hardness value DY and ground water value DS, and substitute them into the formula for calculation. Get ground information DM; where d1 and d2 are preset proportional coefficients corresponding to the set ground hardness value DY and ground water value DS, respectively, d1 and d2 satisfy d1+d2=1, 0<d2<d1<1, d1=0.55, d2=0.45;

[0021] The air information KQ, sound intensity information SQ and ground information DM are sent to the construction information analysis module.

[0022] As a further solution of the present invention: the specific process of the construction abnormality judgment module obtaining the abnormal environment area and generating the abnormal environment instruction is as follows:

[0023] The construction environment supervision coefficient SHo is compared with the preset construction environment supervision threshold SHy, and the comparison results are as follows:

[0024] If the construction environment supervision coefficient SHo ≥ the construction environment supervision threshold SHy, the construction area o corresponding to the construction environment supervision coefficient SHo is marked as an environmental abnormality area, and an environmental abnormality instruction is generated at the same time, and the environmental abnormality area and environmental abnormality instruction are sent to the safe construction supervision module.

[0025] As a further solution of the present invention: the construction supervision system based on big data analysis also includes:

[0026] The construction equipment supervision module is used to collect data on the construction equipment in the construction area o, obtain the construction equipment supervision data of the monitoring equipment i, and send the construction equipment supervision data to the construction information analysis module; wherein the construction equipment supervision data includes frequency difference information PC, noise difference information ZC and usage information SY.

[0027] As a further solution of the present invention: the specific process of the construction equipment supervision module acquiring the construction equipment supervision data is as follows:

[0028] Data is collected from the construction equipment in the construction area o, and all the construction equipment in the construction area o are marked as monitoring equipment i in sequence, where i=1, ..., n, where n is a positive integer, i is the number of any monitoring equipment, and n is the total number of monitoring equipment;

[0029] Obtain the vibration frequency of each part during the first operation of the monitoring device i, obtain the average value of the vibration frequency of each part, and mark it as the first frequency mean value SP; obtain the vibration frequency of each part during the most recent operation of the monitoring device i, obtain the average value of the vibration frequency of each part, and mark it as the most frequent mean value ZP; obtain the difference between the first frequency mean value SP and the most frequent mean value ZP, and mark it as the frequency difference information PC;

[0030] Obtain the noise sound intensity of each part during the first operation of the monitoring device i, obtain the average value of the noise sound intensity of each part, and mark it as the first noise mean value SZ, obtain the noise sound intensity of each part during the most recent operation of the monitoring device i, obtain the average value of the noise sound intensity of each part, and mark it as the most noisy mean value ZZ, obtain the difference between the first noise mean value SZ and the most noisy mean value ZZ, and mark it as noise difference information ZC;

[0031] Obtain the total operating time and total maintenance times of the monitoring device i, and mark them as the operating time value YS and the maintenance value WX respectively, increase the value of the maintenance value WX by one, and mark it as the maintenance adjustment value WT, obtain the product of the operating time value YS and the maintenance adjustment value WT, and mark it as the usage information SY;

[0032] The frequency difference information PC, noise difference information ZC and usage information SY are sent to the construction information analysis module.

[0033] As a further solution of the present invention: the construction information analysis module is also used to obtain the construction equipment supervision coefficient SKoi according to the construction equipment supervision data, and send the construction equipment supervision coefficient SKoi to the construction abnormality judgment module.

[0034] As a further solution of the present invention: the specific process of the construction information analysis module obtaining the construction equipment supervision coefficient SBoi is as follows:

[0035] The frequency difference information PC, the noise difference information ZC and the usage information SY are normalized, and the values ​​of the frequency difference information PC, the noise difference information ZC and the usage information SY are quantified according to a preset construction equipment supervision model to obtain a construction equipment supervision coefficient SBoi, and the construction equipment supervision coefficient SBoi is sent to the construction abnormality judgment module;

[0036] Among them, the construction equipment supervision model is as follows: Where:

[0037] η is the preset error adjustment factor, taking η=0.793;

[0038] κ is a preset mathematical constant, κ=π+0.329, π is a mathematical constant;

[0039] e is a mathematical constant;

[0040] b1, b2 and b3 are preset weight factors corresponding to the set frequency difference information PC, noise difference information ZC and usage information SY respectively. b1, b2 and b3 satisfy b1>b2>b3>0.563, and b1=2.65, b2=1.69, b3=0.88 are taken.

[0041] As a further solution of the present invention: the construction abnormality judgment module is also used to obtain the equipment abnormal area and abnormal equipment according to the construction equipment supervision coefficient SBoi, and generate equipment abnormal instructions at the same time, and send the equipment abnormal area, abnormal equipment and equipment abnormal instructions to the safe construction supervision module.

[0042] As a further solution of the present invention: the specific process of the construction abnormality judgment module obtaining the equipment abnormal area and abnormal equipment and generating the equipment abnormality instruction is as follows:

[0043] The construction equipment supervision coefficient SBoi is compared with the preset construction equipment supervision threshold SBy, and the comparison results are as follows:

[0044] If the construction equipment supervision coefficient SBoi ≥ the construction equipment supervision threshold SBy, the construction area o corresponding to the construction equipment supervision coefficient SBoi is marked as an equipment abnormality area, and the monitoring equipment i corresponding to the construction equipment supervision coefficient SBoi is marked as an abnormal equipment. At the same time, an equipment abnormality instruction is generated, and the equipment abnormality area, abnormal equipment and equipment abnormality instruction are sent to the safe construction supervision module.

[0045] As a further solution of the present invention: the safety construction supervision module is also used to sound an equipment alarm ring upon receiving an equipment abnormality instruction, and send the equipment abnormal area and abnormal equipment to the terminal of the construction supervision manager.

[0046] Beneficial effects of the present invention:

[0047] A construction supervision system for a building project based on big data analysis of the present invention first collects and analyzes data on a construction environment in a construction area to obtain construction environment supervision data. A construction environment supervision coefficient obtained based on the construction environment supervision data can comprehensively measure the degree of abnormality of the construction environment. A larger construction environment supervision coefficient indicates a higher degree of abnormality. When the degree of abnormality is high, an abnormality alarm is issued. Then, data is collected and analyzed on construction equipment in the construction area to obtain construction equipment supervision data. A construction equipment supervision coefficient obtained based on the construction equipment supervision data can comprehensively measure the degree of abnormality of the construction equipment. A larger construction equipment supervision coefficient indicates a higher degree of abnormality. When the degree of abnormality is high, an abnormality alarm is issued.

[0048] The present invention discloses a construction supervision system for a building project based on big data analysis, which adopts the Internet of Things technology to realize the real-time collection and transmission of construction site data, improves the real-time and accuracy of the data, and uses big data analysis technology to deeply mine and analyze the construction environment and equipment status, so as to timely discover abnormal situations and issue early warnings, reduce construction risks, provide decision-making support and optimization suggestions for project managers, realize intelligent analysis and judgment of the construction process, improve the accuracy and efficiency of supervision, improve construction efficiency and quality level, ensure project quality, reduce construction costs, provide strong support for the sustainable development of the construction industry, and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Figure 1 It is a principle block diagram of a construction supervision system for building engineering based on big data analysis in the present invention;

[0051] Figure 2 It is a flow chart of a working method of a construction project supervision system based on big data analysis in the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1: Please refer to Figure 1 As shown, this embodiment is a construction supervision system for building engineering based on big data analysis, including the following modules: a construction environment supervision module, a construction information analysis module, a construction abnormality judgment module, a safe construction supervision module and a construction equipment supervision module;

[0054] The construction environment monitoring module is used to collect data on the construction environment of the construction area o, obtain the construction environment monitoring data of the construction area o, and send the construction environment monitoring data to the construction information analysis module; wherein the construction environment monitoring data includes air information KQ, sound intensity information SQ and ground information DM;

[0055] The construction information analysis module is used to obtain the construction environment supervision coefficient SHo according to the construction environment supervision data, and send the construction environment supervision coefficient SHo to the construction abnormality judgment module; it is also used to obtain the construction equipment supervision coefficient SBoi according to the construction equipment supervision data, and send the construction equipment supervision coefficient SBoi to the construction abnormality judgment module;

[0056] The construction abnormality judgment module is used to obtain the abnormal environment area according to the construction environment supervision coefficient SHo, generate the abnormal environment instruction, and send the abnormal environment area and the abnormal environment instruction to the safe construction supervision module; it is also used to obtain the abnormal equipment area and abnormal equipment according to the construction equipment supervision coefficient SBoi, generate the abnormal equipment instruction, and send the abnormal equipment area, abnormal equipment and the abnormal equipment instruction to the safe construction supervision module;

[0057] The safety construction supervision module is used to sound an environmental alarm upon receiving an environmental abnormality instruction, and send the environmental abnormality area to the terminal of the construction supervision manager; it is also used to sound an equipment alarm upon receiving an equipment abnormality instruction, and send the equipment abnormality area and abnormal equipment to the terminal of the construction supervision manager;

[0058] Among them, the construction equipment supervision module is used to collect data on the construction equipment in the construction area o, obtain the construction equipment supervision data of the monitoring equipment i, and send the construction equipment supervision data to the construction information analysis module; among them, the construction equipment supervision data includes frequency difference information PC, noise difference information ZC and usage information SY.

[0059] Example 2: Please refer to Figure 2 As shown, this embodiment is a working method of a construction project supervision system based on big data analysis, comprising the following steps:

[0060] Step 1: The construction environment supervision module collects data on the construction environment of the construction area o, obtains the construction environment supervision data of the construction area o, wherein the construction environment supervision data includes air information KQ, sound intensity information SQ and ground information DM, and sends the construction environment supervision data to the construction information analysis module;

[0061] Step 2: The construction information analysis module obtains the construction environment supervision coefficient SHo according to the construction environment supervision data, and sends the construction environment supervision coefficient SHo to the construction abnormality judgment module;

[0062] Step 3: The construction abnormality judgment module obtains the abnormal environment area according to the construction environment supervision coefficient SHo, generates an abnormal environment instruction, and sends the abnormal environment area and abnormal environment instruction to the safe construction supervision module;

[0063] Step 4: The safety construction supervision module receives the environmental abnormality instruction and sounds the environmental alarm bell, and sends the environmental abnormality area to the terminal of the construction supervision manager;

[0064] Step 5: The construction equipment supervision module collects data on the construction equipment in the construction area o, obtains the construction equipment supervision data of the monitoring device i, wherein the construction equipment supervision data includes the frequency difference information PC, the noise difference information ZC and the usage information SY, and sends the construction equipment supervision data to the construction information analysis module;

[0065] Step 6: The construction information analysis module obtains the construction equipment supervision coefficient SBoi according to the construction equipment supervision data, and sends the construction equipment supervision coefficient SBoi to the construction abnormality judgment module;

[0066] Step 7: The construction abnormality judgment module obtains the equipment abnormal area and abnormal equipment according to the construction equipment supervision coefficient SBoi, generates equipment abnormality instructions, and sends the equipment abnormal area, abnormal equipment and equipment abnormality instructions to the safe construction supervision module;

[0067] Step 8: The safe construction supervision module receives the equipment abnormality instruction and sounds the equipment alarm bell, and sends the equipment abnormal area and abnormal equipment to the terminal of the construction supervision manager.

[0068] Embodiment 3: Based on any of the above embodiments, Embodiment 3 of the present invention is a construction environment monitoring module. The function of the construction environment monitoring module is to obtain construction environment monitoring data, wherein the construction environment monitoring data includes air information KQ, sound intensity information SQ and ground information DM. The specific process is as follows:

[0069] The construction environment supervision module randomly divides the construction area of ​​the building project into several sub-areas and marks them as construction areas o, o=1, ..., v, v is a positive integer, o is the number of any construction area, and v is the total number of construction areas;

[0070] The construction environment monitoring module collects data on the construction environment of the construction area o, obtains the dust content and volatile organic matter content in the air environment of the construction area o, and marks them as dust value HC and volatile value HF respectively, quantifies the dust value HC and volatile value HF, extracts the values ​​of the dust value HC and volatile value HF, and substitutes them into the formula for calculation. The air information KQ is obtained; wherein k1 and k2 are preset proportional coefficients corresponding to the set dust value HC and volatility value HF, respectively, k1 and k2 satisfy k1+k2=1, 0<k2<k1<1, k1=0.66, k2=0.34;

[0071] The construction environment monitoring module obtains the real-time sound intensity in the construction area o and marks it as the real sound value SS, obtains the maximum real sound value SS per unit time and marks it as the maximum sound value ZS, obtains the preset real sound threshold SSy, obtains the total duration of the real sound value SS ≥ the real sound threshold SSy, and marks it as the sound duration ST, quantifies the maximum sound value ZS and the sound duration ST, extracts the values ​​of the maximum sound value ZS and the sound duration ST, and substitutes them into the formula for calculation. The sound intensity information SQ is obtained; wherein s1 and s2 are preset proportional coefficients corresponding to the set maximum sound value ZS and the sound time value ST, respectively, s1 and s2 satisfy s1+s2=1, 0<s1<s2<1, and s1=0.23 and s2=0.77;

[0072] The construction environment supervision module obtains the ground hardness and ground moisture content of the construction area o, and marks them as ground hardness value DY and ground water value DS respectively, quantifies the ground hardness value DY and ground water value DS, extracts the values ​​of ground hardness value DY and ground water value DS, and substitutes them into the formula for calculation. Get ground information DM; where d1 and d2 are preset proportional coefficients corresponding to the set ground hardness value DY and ground water value DS, respectively, d1 and d2 satisfy d1+d2=1, 0<d2<d1<1, d1=0.55, d2=0.45;

[0073] The construction environment monitoring module sends the air information KQ, sound intensity information SQ and ground information DM to the construction information analysis module.

[0074] Embodiment 4: Based on any of the above embodiments, Embodiment 4 of the present invention is a construction information analysis module, which has two functions:

[0075] One of the functions is to obtain the construction environment supervision coefficient SHo. The specific process is as follows:

[0076] The construction information analysis module normalizes the air information KQ, the sound intensity information SQ and the ground information DM, and quantifies the values ​​of the air information KQ, the sound intensity information SQ and the ground information DM according to the preset construction environment supervision model to obtain the construction environment supervision coefficient SHo, and sends the construction environment supervision coefficient SHo to the construction abnormality judgment module;

[0077] The construction environment supervision model is as follows: Where:

[0078] γ is the preset error adjustment factor, and γ=1.208 is taken;

[0079] π and e are both mathematical constants;

[0080] h1, h2 and h3 are preset weight factors corresponding to the set air information KQ, sound intensity information SQ and ground information DM respectively, h1, h2 and h3 satisfy h1>h3>h2>1.329, h1=2.44, h2=1.61, h3=1.95;

[0081] The second function is to obtain the construction equipment supervision coefficient SBoi. The specific process is as follows:

[0082] The construction information analysis module normalizes the frequency difference information PC, the noise difference information ZC and the usage information SY, and quantifies the values ​​of the frequency difference information PC, the noise difference information ZC and the usage information SY according to the preset construction equipment supervision model to obtain the construction equipment supervision coefficient SBoi, and sends the construction equipment supervision coefficient SBoi to the construction abnormality judgment module;

[0083] Among them, the construction equipment supervision model is as follows: Where:

[0084] η is the preset error adjustment factor, taking η=0.793;

[0085] κ is a preset mathematical constant, κ=π+0.329, π is a mathematical constant;

[0086] e is a mathematical constant;

[0087] b1, b2 and b3 are preset weight factors corresponding to the set frequency difference information PC, noise difference information ZC and usage information SY respectively. b1, b2 and b3 satisfy b1>b2>b3>0.563, and b1=2.65, b2=1.69, b3=0.88 are taken.

[0088] Embodiment 5: Based on any of the above embodiments, Embodiment 5 of the present invention is a construction abnormality judgment module, which has two functions:

[0089] One of the functions is to obtain the abnormal environment area and generate abnormal environment instructions. The specific process is as follows:

[0090] The construction abnormality judgment module compares the construction environment supervision coefficient SHo with the preset construction environment supervision threshold SHy. The comparison results are as follows:

[0091] If the construction environment supervision coefficient SHo ≥ the construction environment supervision threshold SHy, the construction area o corresponding to the construction environment supervision coefficient SHo is marked as an abnormal environment area, and an abnormal environment instruction is generated at the same time, and the abnormal environment area and the abnormal environment instruction are sent to the safe construction supervision module;

[0092] The second function is to obtain the abnormal area and abnormal device of the device, and generate the abnormal device instruction. The specific process is as follows:

[0093] The construction abnormality judgment module compares the construction equipment supervision coefficient SBoi with the preset construction equipment supervision threshold SBy. The comparison results are as follows:

[0094] If the construction equipment supervision coefficient SBoi ≥ the construction equipment supervision threshold SBy, the construction area o corresponding to the construction equipment supervision coefficient SBoi is marked as an equipment abnormality area, and the monitoring equipment i corresponding to the construction equipment supervision coefficient SBoi is marked as an abnormal equipment. At the same time, an equipment abnormality instruction is generated, and the equipment abnormality area, abnormal equipment and equipment abnormality instruction are sent to the safe construction supervision module.

[0095] Embodiment 6: Based on any of the above embodiments, Embodiment 6 of the present invention is a safety construction supervision module, which has two functions:

[0096] One function is to sound the environmental alarm bell when receiving an environmental abnormality instruction, and send the environmental abnormality area to the terminal of the construction supervision manager;

[0097] The second function is to sound the equipment alarm bell when receiving equipment abnormality instructions, and send the equipment abnormal area and abnormal equipment to the terminal of the construction supervision manager.

[0098] Embodiment 7: Based on any of the above embodiments, Embodiment 7 of the present invention is a construction equipment supervision module. The function of the construction equipment supervision module is to obtain construction equipment supervision data, wherein the construction equipment supervision data includes frequency difference information PC, noise difference information ZC and usage information SY. The specific process is as follows:

[0099] The construction equipment monitoring module collects data on the construction equipment in the construction area o, and marks all the construction equipment in the construction area o as monitoring equipment i in sequence, where i=1, ..., n, where n is a positive integer, i is the number of any monitoring equipment, and n is the total number of monitoring equipment;

[0100] The construction equipment supervision module obtains the vibration frequency of each part during the first operation of the monitoring equipment i, obtains the average value of the vibration frequency of each part, and marks it as the first frequency mean value SP, obtains the vibration frequency of each part during the most recent operation of the monitoring equipment i, obtains the average value of the vibration frequency of each part, and marks it as the most frequent mean value ZP, obtains the difference between the first frequency mean value SP and the most frequent mean value ZP, and marks it as the frequency difference information PC;

[0101] The construction equipment supervision module obtains the noise sound intensity of each part during the first operation of the monitoring equipment i, obtains the average value of the noise sound intensity of each part, and marks it as the first noise mean SZ, obtains the noise sound intensity of each part during the most recent operation of the monitoring equipment i, obtains the average value of the noise sound intensity of each part, and marks it as the most noisy mean ZZ, obtains the difference between the first noise mean SZ and the most noisy mean ZZ, and marks it as noise difference information ZC;

[0102] The construction equipment supervision module obtains the total operation time and total maintenance times of the monitoring equipment i, and marks them as the operation time value YS and the maintenance value WX respectively, adds one to the value of the maintenance value WX, and marks it as the maintenance adjustment value WT, obtains the product of the operation time value YS and the maintenance adjustment value WT, and marks it as the usage information SY;

[0103] The construction equipment supervision module sends the frequency difference information PC, the noise difference information ZC and the usage information SY to the construction information analysis module.

[0104] Based on the above embodiments 1-7, the working principle of the present invention is as follows:

[0105] The present invention discloses a construction supervision system for a construction project based on big data analysis. The system collects data on the construction environment of a construction area through a construction environment supervision module to obtain construction environment supervision data of the construction area, wherein the construction environment supervision data includes air information, sound intensity information and ground information. The system obtains a construction environment supervision coefficient according to the construction environment supervision data through a construction information analysis module. The system obtains an abnormal environment area according to the construction environment supervision coefficient through a construction abnormality judgment module, and generates an abnormal environment instruction at the same time. When the abnormal environment instruction is received through a safe construction supervision module, an environmental alarm ring is sounded, and the abnormal environment area is sent to a terminal of a construction supervision manager. The system collects data on the construction equipment in the construction area through a construction equipment supervision module to obtain construction equipment supervision data of the monitoring equipment, wherein the construction equipment supervision data includes frequency difference information, noise difference information and usage information. The system obtains a construction equipment supervision coefficient according to the construction equipment supervision data through a construction information analysis module. The system obtains an abnormal equipment area and abnormal equipment according to the construction equipment supervision coefficient through a construction abnormality judgment module, and generates an abnormal equipment instruction at the same time. When the abnormal equipment instruction is received through a safe construction supervision module, an equipment alarm ring is sounded, and the abnormal equipment area and abnormal equipment are sent to a terminal of a construction supervision manager. The terminal of the construction supervision manager; the system first collects and analyzes the construction environment of the construction area, obtains the construction environment supervision data, and the construction environment supervision coefficient obtained according to the construction environment supervision data can comprehensively measure the abnormality of the construction environment, and the larger the construction environment supervision coefficient is, the higher the abnormality is. When the abnormality is high, an abnormal alarm is issued. Then, data is collected and analyzed for the construction equipment in the construction area, and the construction equipment supervision data is obtained. The construction equipment supervision coefficient obtained according to the construction equipment supervision data can comprehensively measure the abnormality of the construction equipment, and the larger the construction equipment supervision coefficient is, the higher the abnormality is. When the abnormality is high, an abnormal alarm is issued; the present invention adopts the Internet of Things technology to realize the real-time collection and transmission of construction site data, improves the real-time and accuracy of the data, and uses the big data analysis technology to deeply mine and analyze the construction environment and equipment status, which can timely discover abnormal situations and give early warnings, reduce construction risks, provide decision support and optimization suggestions for project managers, realize intelligent analysis and judgment of the construction process, improve the accuracy and efficiency of supervision, improve construction efficiency and quality level, ensure project quality, reduce construction costs, provide strong support for the sustainable development of the construction industry, and improve user experience.

[0106] It should be further explained that the above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technical personnel in this field according to actual conditions.

[0107] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0108] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined in this application, they shall all fall within the protection scope of the present invention.

Claims

1. A construction supervision system based on big data analysis, characterized in that: include: The construction environment monitoring module is used to collect data on the construction environment of the construction area o, obtain the construction environment monitoring data of the construction area o, and send the construction environment monitoring data to the construction information analysis module; wherein the construction environment monitoring data includes air information KQ, sound intensity information SQ and ground information DM; The specific process of the construction environment supervision module obtaining the construction environment supervision data is as follows: The construction area of ​​the building project is randomly divided into several sub-areas, and they are marked as construction areas o in turn; Collect data on the construction environment of construction area o, obtain the dust content and volatile organic matter content in the air environment of construction area o, and mark them as dust value HC and volatile value HF respectively. Quantify the dust value HC and volatile value HF according to the formula The air information KQ is obtained; wherein k1 and k2 are preset proportional coefficients corresponding to the set dust value HC and volatility value HF respectively; Get the real-time sound intensity in the construction area o and mark it as the real sound value SS, get the maximum real sound value SS per unit time and mark it as the maximum sound value ZS, get the preset real sound threshold SSy, get the total duration of the real sound value SS ≥ the real sound threshold SSy and mark it as the sound duration ST, quantify the maximum sound value ZS and the sound duration ST, and use the formula The sound intensity information SQ is obtained; wherein s1 and s2 are preset proportional coefficients corresponding to the set maximum sound value ZS and sound duration value ST respectively; Obtain the ground hardness and ground water content of the construction area o, and mark them as ground hardness value DY and ground water value DS respectively. Quantify the ground hardness value DY and ground water value DS according to the formula Get ground information DM; where d1 and d2 are preset proportional coefficients corresponding to the set ground hardness value DY and ground water value DS respectively; Send the air information KQ, sound intensity information SQ and ground information DM to the construction information analysis module; The construction information analysis module is used to obtain the construction environment supervision coefficient SHo according to the construction environment supervision data, and send the construction environment supervision coefficient SHo to the construction abnormality judgment module; The specific process of the construction information analysis module obtaining the construction environment supervision coefficient SHo is as follows: The air information KQ, the sound intensity information SQ and the ground information DM are quantified according to the preset construction environment supervision model to obtain the construction environment supervision coefficient SHo, and the construction environment supervision coefficient SHo is sent to the construction abnormality judgment module; The construction environment supervision model is as follows: Wherein: γ is the preset error adjustment factor; π and e are mathematical constants; h1, h2 and h3 are the preset weight factors corresponding to the set air information KQ, sound intensity information SQ and ground information DM respectively; The construction abnormality judgment module is used to obtain the abnormal environment area according to the construction environment supervision coefficient SHo, generate an abnormal environment instruction, and send the abnormal environment area and abnormal environment instruction to the safe construction supervision module; The safe construction supervision module is used to sound the environmental alarm bell upon receiving an environmental abnormality instruction and send the environmental abnormality area to the terminal of the construction supervision manager.

2. According to the big data analysis-based construction supervision system of claim 1, it is characterized in that: The specific process of the construction abnormality judgment module obtaining the abnormal environment area and generating the abnormal environment instruction is as follows: The construction environment supervision coefficient SHo is compared with the preset construction environment supervision threshold SHy, and the comparison results are as follows: If the construction environment supervision coefficient SHo ≥ the construction environment supervision threshold SHy, the construction area o corresponding to the construction environment supervision coefficient SHo is marked as an environmental abnormality area, and an environmental abnormality instruction is generated at the same time, and the environmental abnormality area and environmental abnormality instruction are sent to the safe construction supervision module.

3. The construction supervision system based on big data analysis according to claim 1 is characterized in that: Also includes: The construction equipment supervision module is used to collect data on the construction equipment in the construction area o, obtain the construction equipment supervision data of the monitoring equipment i, and send the construction equipment supervision data to the construction information analysis module; wherein the construction equipment supervision data includes frequency difference information PC, noise difference information ZC and usage information SY.

4. The construction supervision system based on big data analysis according to claim 3 is characterized in that: The specific process of the construction equipment supervision module obtaining the construction equipment supervision data is as follows: Collect data from the construction equipment in the construction area o, and mark all the construction equipment in the construction area o as monitoring equipment i in sequence; Obtain the vibration frequency of each part during the first operation of the monitoring device i, obtain the average value of the vibration frequency of each part, and mark it as the first frequency mean value SP; obtain the vibration frequency of each part during the most recent operation of the monitoring device i, obtain the average value of the vibration frequency of each part, and mark it as the most frequent mean value ZP; obtain the difference between the first frequency mean value SP and the most frequent mean value ZP, and mark it as the frequency difference information PC; Obtain the noise sound intensity of each part during the first operation of the monitoring device i, obtain the average value of the noise sound intensity of each part, and mark it as the first noise mean value SZ, obtain the noise sound intensity of each part during the most recent operation of the monitoring device i, obtain the average value of the noise sound intensity of each part, and mark it as the most noisy mean value ZZ, obtain the difference between the first noise mean value SZ and the most noisy mean value ZZ, and mark it as noise difference information ZC; Obtain the total operating time and total maintenance times of the monitoring device i, and mark them as the operating time value YS and the maintenance value WX respectively, increase the value of the maintenance value WX by one, and mark it as the maintenance adjustment value WT, obtain the product of the operating time value YS and the maintenance adjustment value WT, and mark it as the usage information SY; The frequency difference information PC, noise difference information ZC and usage information SY are sent to the construction information analysis module.

5. The construction supervision system based on big data analysis according to claim 1 is characterized in that: The construction information analysis module is also used to obtain a construction equipment supervision coefficient SBoi according to the construction equipment supervision data, and send the construction equipment supervision coefficient SBoi to the construction abnormality judgment module.

6. The construction supervision system based on big data analysis according to claim 5 is characterized in that: The specific process of the construction information analysis module obtaining the construction equipment supervision coefficient SBoi is as follows: The frequency difference information PC, the noise difference information ZC and the usage information SY are quantified according to the preset construction equipment supervision model to obtain the construction equipment supervision coefficient SBoi, and the construction equipment supervision coefficient SBoi is sent to the construction abnormality judgment module; Among them, the construction equipment supervision model is as follows: In the formula: η is a preset error adjustment factor; κ is a preset mathematical constant; π is a mathematical constant; e is a mathematical constant; b1, b2 and b3 are preset weight factors corresponding to the set frequency difference information PC, noise difference information ZC and usage information SY respectively.

7. The construction supervision system based on big data analysis according to claim 1 is characterized in that: The construction abnormality judgment module is also used to obtain the equipment abnormal area and abnormal equipment according to the construction equipment supervision coefficient SBoi, generate equipment abnormality instructions, and send the equipment abnormal area, abnormal equipment and equipment abnormality instructions to the safe construction supervision module.

8. The construction supervision system based on big data analysis according to claim 7 is characterized in that: The specific process of the construction abnormality judgment module obtaining the equipment abnormal area and abnormal equipment and generating the equipment abnormality instruction is as follows: The construction equipment supervision coefficient SBoi is compared with the preset construction equipment supervision threshold SBy, and the comparison results are as follows: If the construction equipment supervision coefficient SBoi ≥ the construction equipment supervision threshold SBy, the construction area o corresponding to the construction equipment supervision coefficient SBoi is marked as an equipment abnormality area, and the monitoring equipment i corresponding to the construction equipment supervision coefficient SBoi is marked as an abnormal equipment. At the same time, an equipment abnormality instruction is generated, and the equipment abnormality area, abnormal equipment and equipment abnormality instruction are sent to the safe construction supervision module.

9. The construction supervision system based on big data analysis according to claim 1 is characterized in that: The safety construction supervision module is also used to sound an equipment alarm bell upon receiving an equipment abnormality instruction, and send the equipment abnormal area and abnormal equipment to the terminal of the construction supervision manager.

Images