Engineering production and operation early warning index management system

Abstract

The invention belongs to the field of engineering production abnormity early warning, and discloses an engineering production operation early warning index management system. By means of the sensor and image recognition, materials in static storage and processing are synchronously considered, allowance calculation deviation is avoided, real consumption of the materials is accurately reflected, and more reliable data are provided for construction progress control and abnormal condition recognition. According to the method, spatial influence is quantified by means of regional deviation, abnormity is accurately positioned from time-space two dimensions, abnormity grades are judged according to multi-deviation threshold grading, stepped early warning is provided, risks of different degrees such as slight waste and serious process problems can be rapidly identified, managers are helped to make decisions efficiently, and the engineering management refinement level and the risk prevention and control capability are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of engineering production anomaly warning, and relates to an engineering production operation warning index management system. Background Art

[0002] Engineering production is a complex process involving a series of activities from project planning to final delivery. In engineering production, material management is of great significance. It accurately obtains material information through technology, analyzes the actual consumption, ensures the continuity of construction, and avoids construction suspension due to material shortage. At the same time, by comparing the actual and theoretical material consumption, it can effectively control costs, prevent waste and overstock. Accurate material management can also ensure the use of qualified materials and guarantee the project quality. Therefore, the research on engineering production operation warning index management is of great significance.

[0003] In the prior art, there are also related solutions for engineering production anomaly warning technology. For example, a Chinese invention patent application for a construction plan and schedule optimization and dispatching management system for a wind farm construction project with the publication number CN114049002A includes: using an intelligent management system to plan and monitor the progress of each part of the project, and then calculating the gap between the current construction progress and the planned construction progress to complete the construction plan with quality and quantity guaranteed. By visually displaying the planned completion ratio of the completed and uncompleted sub-projects in each part of the project and the current construction progress of the total project, it is convenient for project managers to adjust the personnel and material resources in the construction tasks through these data, and then effectively adjust the current construction progress in real time.

[0004] Although the above solution proposes some solutions for engineering production anomaly warning technology, there are still certain limitations. For example, on the one hand, the prior art solutions lack a comprehensive analysis of static stacking stock and dynamic processing allowance, and cannot accurately identify the actual material consumption.

[0005] On the other hand, the prior art solutions lack a comprehensive analysis and anomaly identification of time-series anomaly detection and spatial correlation anomaly analysis, which may lead to errors in the actual anomaly judgment process and affect the project progress and project quality. Summary of the Invention

[0006] In view of this, to solve the problems raised in the above background art, an engineering production operation warning index management system is proposed.

[0007] The object of the present invention can be achieved by the following technical solutions: An engineering production operation warning index management system includes: a material dynamic monitoring module that obtains the static stacking stock of each construction unit based on image recognition technology and uses a weighing sensor installed on the construction machinery device to detect and analyze the dynamic processing allowance, and accordingly analyzes the actual material consumption of each construction unit.

[0008] The progress coupling analysis module uses an image acquisition device to collect structural entity images of each construction unit, adopts a convolutional neural network to identify the completion status of components, matches the current construction stage of each construction unit according to a preset progress plan model, and outputs the corresponding theoretical material consumption.

[0009] The multi-dimensional deviation warning module performs time-series anomaly detection and spatial correlation anomaly analysis on the actual material consumption and the theoretical material consumption, and makes construction anomaly judgments and anomaly level identifications based on the analysis results.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Through sensors and image recognition, the present invention synchronously considers the materials in static storage and processing, avoids deviation in allowance calculation, accurately reflects the true consumption of materials, and provides more reliable data for construction progress control and anomaly identification.

[0011] (2) The present invention uses regional deviation to quantify the spatial influence, accurately locates anomalies from both time and space dimensions, determines the anomaly level according to multiple deviation thresholds, provides stepped warnings, can quickly identify risks of different degrees from minor waste to serious process problems, helps managers make efficient decisions, and improves the refinement level of project management and risk prevention and control capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0013] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention.

[0014] Figure 2 It is a schematic diagram of the positioning of the reference distribution position points corresponding to an embodiment provided by the present invention.

[0015] Figure 3 It is a schematic diagram of the division of the reference distribution intervals corresponding to an embodiment provided by the present invention.

[0016] Reference numerals: 1 - component, 2 - central distribution position, 3 - reference distribution position point, 4 - construction unit, 5 - reference distribution interval. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Please refer to Figure 1 As shown, the present invention provides an engineering production and operation early warning index management system, including a material dynamic monitoring module, a progress coupling analysis module, and a multi-dimensional deviation early warning module. Among them, the material dynamic monitoring module is connected to the progress coupling analysis module, and the progress coupling analysis module is connected to the multi-dimensional deviation early warning module.

[0019] The material dynamic monitoring module is used to obtain the static stacking stock of each construction unit based on image recognition technology and detect and analyze the dynamic processing margin using the weighing sensors installed on the construction machinery device, and accordingly analyze the actual material consumption of each construction unit.

[0020] The specific analysis method of the static stacking stock is as follows: Use the image acquisition device to obtain the construction images of each construction unit, locate the corresponding material stacking area, use the image processing technology to obtain the material images of each material in the material stacking area, and then compare and match with the pre-saved standard material appearance images to obtain the types of each material, and at the same time obtain the volume of each material.

[0021] Exemplarily, the materials may be steel bars, cement, and yellow sand.

[0022] Combine the volume of each material and the corresponding pre-set reference density to obtain the static stacking stock of each material.

[0023] It should be noted that the reference density is derived from the product specifications of the materials.

[0024] The specific analysis method of the dynamic processing margin is as follows: Use the weighing sensors installed on the construction machinery device to obtain the total weight of the processed materials, and at the same time obtain the material ratio of the corresponding processed materials, and perform material quality analysis based on the total weight of the processed materials and the material ratio to obtain the dynamic processing margin of each material.

[0025] Preferably, the specific method for analyzing the dynamic processing margin of each material is: Multiply the total weight of the processed materials by the proportion of each material in the material ratio to obtain the dynamic processing margin of each material.

[0026] It should be noted that the analysis of dynamic processing allowance is extremely crucial in engineering production and operation management. By combining the static stockpile and the material receipt records, through the analysis of dynamic processing allowance, the actual consumption of each material in each construction unit can be accurately obtained, providing accurate data for the evaluation of material use. Secondly, it helps to control the construction progress in real time.

[0027] The specific process of analyzing the actual material consumption of each construction unit is as follows: Extract the material receipt records at the material storage location, and obtain the construction unit, material type, and receipt quantity corresponding to each material receipt record.

[0028] Classify the material receipt records according to the construction unit to obtain the material receipt records corresponding to each construction unit, and at the same time accumulate the receipt quantities corresponding to the same material type to obtain the total receipt quantity of each material.

[0029] Sum the static stockpile and the dynamic processing allowance of each material in each construction unit to obtain the material allowance corresponding to each material.

[0030] Conduct a net consumption calculation of the total receipt quantity and the material allowance of each material in each construction unit to obtain the actual material consumption of each material in each construction unit.

[0031] It should be noted that the material allowance consists of the static stockpile and the dynamic processing allowance. The total receipt quantity is the cumulative quantity of materials received by each construction unit extracted from the material storage location. Subtracting the material allowance from the total receipt quantity can obtain the actual quantity of materials consumed, that is, the actual material consumption. For example, a construction unit received 100 tons of cement, and after calculation, the material allowance is 30 tons, then the actual material consumption of cement in this construction unit is 70 tons. Accurate actual material consumption data helps to analyze the material use efficiency of the construction unit, judge whether there is waste or material shortage, and provide an important basis for subsequent material procurement, allocation, and construction progress adjustment.

[0032] It should be noted that the present invention synchronously considers the materials in static storage and processing through sensors and image recognition, avoids calculation deviation of the allowance, accurately reflects the real consumption of materials, and provides more reliable data for the control of construction progress and the identification of abnormal situations.

[0033] The progress coupling analysis module is used to collect the structural entity images of each construction unit by using an image acquisition device, identify the completion status of components by using a convolutional neural network, and match the current construction stage of each construction unit according to a preset progress plan model and output the corresponding theoretical material consumption.

[0034] The specific process of identifying the completion status of components is as follows: Based on the structural entity images of each construction unit, construct the actual contour images corresponding to each component, and at the same time obtain the expected contour images corresponding to each component based on the construction plan.

[0035] It should be noted that the actual contour images of each component are constructed based on the structural entity images of the construction units, which reflect the true shapes of the components at the current construction stage; the expected contour images are obtained according to the construction plan, representing the shapes that the components should present under the ideal construction progress.

[0036] Compare the actual contour images of each component with the corresponding expected contour images, and mark the overlapping parts of the actual contour images of each component with the corresponding expected contour images as the effective contour images, which are then used as the completion status of each component.

[0037] It should be noted that when comparing the actual contour image and the expected contour image, the overlapping part is the effective contour image. For example, when building a house, the expected contour of a beam is a standard rectangle, and the contour of the beam in actual construction may not be completely regular due to construction errors and other factors. After comparing the two, the parts with the same shape and overlapping are the effective contour images. The effective contour images are directly used as the basis for the completion status of each component.

[0038] The specific analysis method of the theoretical material consumption is as follows: Compare the completed contour volumes of the effective contour images of each component with the expected contour images of the corresponding components in the construction plan to obtain the completion degrees of each component.

[0039] Preferably, the specific analysis method of the completion degrees of each component is as follows: Divide the volume of the effective contour image by the volume of the expected contour image, and the obtained value is the completion degree of the component.

[0040] Based on the construction plan, obtain the types and theoretical consumption amounts of each material corresponding to each component.

[0041] Mark the materials that are not needed and are outside the effective contour images of each component as the materials that have been used up, and at the same time match them with the theoretical consumption amounts of each material of each component to obtain the theoretical consumption amounts of each material that has been used up for each component.

[0042] Mark the materials that are still needed and are outside the effective contour images of each component as the materials to be used, and then match them with the theoretical consumption amounts of each material of each component to obtain the complete component theoretical consumption amounts of each material to be used. Then, conduct a fusion analysis in combination with the completion degrees of each component to obtain the theoretical consumption amounts of each material to be used for each component.

[0043] It should be further explained that classifying materials and calculating their theoretical consumption helps to accurately master the usage and demand prediction of materials, providing an important basis for construction management. Specifically: (1) Calculation of the theoretical consumption of materials that have been used up: After constructing the effective contour images of each component, the materials outside the effective contour images and not required for subsequent construction are marked as materials that have been used up. The actual usage of this part of the materials has ended. By matching it with the theoretical consumption of each material for each component in the construction plan, it is possible to determine how much these materials that have been used up should consume at the theoretical level. For example, when building a building, some materials used for temporary support structures are no longer used after the effective contour of the main structure is determined. By matching with the theoretical consumption, the quantity that should be consumed theoretically can be known.

[0044] (2) Calculation of the theoretical consumption of materials to be used: Outside the effective contour image, the materials required for subsequent construction are materials to be used. First, match according to the construction plan to obtain the theoretical consumption of these materials to be used in the complete components. Since the components have a certain degree of completion, not all materials to be used need to be immediately put into use in full. Therefore, by combining the degree of completion of each component for integrated analysis, the actual required theoretical consumption of each material to be used for each component at the current construction progress can be obtained. For example, if a component has a completion degree of 50% and originally requires 100 units of a certain material to be used for the complete component, then considering the degree of completion, the current required theoretical consumption of this material is 50 units.

[0045] Classify and sum up the theoretical consumption of materials that have been used up for each component and the theoretical consumption of materials to be used to obtain the theoretical material consumption of each material for each construction unit.

[0046] The multi-dimensional deviation warning module is used to perform time-series anomaly detection and spatial correlation anomaly analysis on the actual material consumption and the theoretical material consumption, and make construction anomaly judgments and anomaly level identifications based on the analysis results.

[0047] The specific analysis process of the time-series anomaly detection is as follows: Based on the preset adaptive sliding time window length, set several monitoring periods, extract the theoretical material consumption and the actual material consumption of each construction unit corresponding to each material within each monitoring period, and then conduct deviation analysis to obtain the absolute deviation of the actual material consumption relative to the theoretical material consumption. Perform mean analysis on each absolute deviation to obtain the material consumption deviation of each construction unit for each monitoring period.

[0048] It should be noted that the length of the adaptive sliding time window is a flexible time setting parameter. The time window can be set according to the actual engineering situation and management requirements, and multiple monitoring periods can be divided based on it. For example, if the length of the adaptive sliding time window is set to one week, then monitoring periods such as the first week and the second week can be divided in sequence. This adaptive setting can better adapt to the characteristics of different construction stages because the material consumption patterns may vary in different stages.

[0049] Preferably, the specific method for performing deviation analysis is as follows: Calculate the difference between the actual material consumption of each material and the theoretical material consumption, and then calculate the ratio with the theoretical material consumption to obtain the absolute deviation of the actual material consumption relative to the theoretical material consumption.

[0050] It should be explained that the mean analysis of each absolute deviation is to eliminate the contingency of the deviation of a single material or a single measurement, and comprehensively consider the overall deviation degree of the material consumption of an entire construction unit within a certain monitoring period. Because the deviation of a single material may be affected by special factors and cannot represent the material consumption situation of the entire construction unit. By taking the average value, a more representative value, that is, the material consumption deviation, can be obtained.

[0051] Compare the end time of each monitoring period with the end time of the current monitoring period to obtain the time sequence deviation reference coefficient of each monitoring period.

[0052] Preferably, the system will set multiple monitoring periods based on the pre-set length of the adaptive sliding time window. Each monitoring period has a corresponding end time, and the current monitoring period is the period being analyzed. Compare the end times of the previous monitoring periods with the end time of the current monitoring period. This comparison operation can reflect the relative position relationship of different monitoring periods on the time axis. For example, the current monitoring period is the 5th week, and the end time is the end of the 5th week. The end time of the previous 3rd week monitoring period is the end of the 3rd week, and there is a time interval between the two.

[0053] A method for calculating the time sequence deviation reference coefficient: Calculate the time interval of each monitoring period relative to the current monitoring period by calculating the difference between the end time of each monitoring period and the end time of the current monitoring period, and calculate the ratio of the preset reference time interval to the time interval of each monitoring period relative to the current monitoring period to obtain the time sequence deviation reference coefficient of each monitoring period.

[0054] It should be explained that the analysis of the time sequence deviation reference coefficient is used to measure the time difference between monitoring periods. By calculating this difference, the referability of the change in material consumption between different periods can be judged. Because the material consumption pattern may change over time.

[0055] The material consumption deviation and the time - series deviation reference coefficient of each construction unit in each monitoring period are linearly weighted and comprehensively analyzed to obtain the reference time - series material deviation of each construction unit. Then, the actual material consumption and the theoretical material consumption of each material of each construction unit are combined to conduct a time - series material deviation analysis to obtain the adjacent - time - series material deviation of each construction unit.

[0056] Preferably, the specific analysis method of the adjacent - time - series material deviation is as follows: Calculate the mean of the absolute deviations of the actual material consumption and the theoretical material consumption of each material of each construction unit to obtain the absolute material deviation of each construction unit. Then, calculate the difference between the reference time - series material deviation and the absolute material deviation of each construction unit, take the absolute value, and then calculate the ratio with the reference time - series material deviation to obtain the adjacent - time - series material deviation.

[0057] The specific analysis method of the spatial correlation anomaly analysis is as follows: Please refer to Figure 2 As shown, obtain the central distribution positions 2 of each component 1 of each construction unit, and then locate the reference distribution position points 3 of each construction unit.

[0058] Please refer to Figure 3 As shown, connect the reference distribution position points 3 of each construction unit 4 with those of other construction units 4 to obtain the reference distribution distances 5 between each construction unit 4 and other construction units 4, and then compare with the pre - set reference distribution distance threshold to identify the adjacent construction units of each construction unit.

[0059] Based on the analysis of the reference distribution distances between each construction unit and its corresponding adjacent construction units, obtain the regional deviation reference coefficients of each construction unit corresponding to its adjacent construction units.

[0060] Calculate the absolute deviation of the actual material consumption of each material of each construction unit relative to the theoretical material consumption by calculating the absolute deviation.

[0061] Linearly weight and fuse the regional deviation reference coefficients of each adjacent construction unit and the absolute deviation of the actual material consumption of each material relative to the theoretical material consumption to obtain the reference regional material deviation of each material. Then, compare and select the maximum reference regional material deviation as the reference regional material deviation of the corresponding construction unit.

[0062] Conduct a deviation analysis of the reference regional material deviation of each construction unit and the absolute deviation of the actual material consumption relative to the theoretical material consumption to obtain the adjacent - region material deviation of each construction unit.

[0063] It should be noted that the specific calculation method of the adjacent - region material deviation can refer to the calculation method of the adjacent - time - series material deviation.

[0064] The specific analysis method for judging construction anomalies is as follows: The absolute deviation of the actual material consumption of each material in each construction unit from the theoretical material consumption is recorded as the absolute material deviation, and the maximum absolute material deviation is used as the absolute material deviation of each construction unit.

[0065] The absolute material deviation, adjacent time-series material deviation, and adjacent area material deviation of each construction unit are respectively compared with the preset absolute material deviation threshold, adjacent time-series material deviation threshold, and adjacent area material deviation threshold to obtain the judgment result of whether there is a construction anomaly in each construction unit.

[0066] Specifically, if the absolute material deviation of a certain construction unit is greater than the absolute material deviation threshold, it is judged that there is a construction anomaly in this construction unit.

[0067] The specific analysis of anomaly level identification is as follows: If the absolute material deviation, adjacent time-series material deviation, and adjacent area material deviation of a certain construction unit are all greater than the corresponding absolute material deviation threshold, adjacent time-series material deviation threshold, and adjacent area material deviation threshold, the specific anomaly level is identified as a first-level anomaly.

[0068] It should be noted that a first-level anomaly means that this construction unit has severely deviated from the normal range in terms of the actual and theoretical comparison of material consumption, time-series changes, and spatial correlation. For example, in terms of material consumption, the actual usage far exceeds the theoretical usage, and there are significant differences in the time dimension compared with past cycles and also in space compared with adjacent construction units. This indicates that there are very likely serious problems in the construction process, such as construction process errors, material management chaos, etc., and comprehensive and in-depth measures need to be taken immediately for rectification.

[0069] If the absolute material deviation of a certain construction unit is greater than the absolute material deviation threshold, and at the same time, one of the adjacent time-series material deviation and adjacent area material deviation is greater than the corresponding threshold, the specific anomaly level is identified as a second-level anomaly.

[0070] It should be noted that a second-level anomaly indicates that there are obvious problems in the construction unit. It may be that there is an anomaly in a certain key link during the material usage process, such as serious material waste, or there are large fluctuations in the material consumption law in terms of time or space. However, compared with the first-level anomaly, the severity of the problem is slightly lower. At this time, key investigations and adjustments need to be carried out for the aspects with deviations to avoid the further deterioration of the problem.

[0071] If the absolute material deviation of a certain construction unit is greater than the absolute material deviation threshold, and at the same time, the adjacent time-series material deviation and adjacent area material deviation are both less than the corresponding thresholds, the specific anomaly level is identified as a third-level anomaly.

[0072] It should be noted that a third-level anomaly indicates that although there is an anomaly in the overall comparison of material consumption in the current construction unit, the fluctuations in the time and space dimensions are relatively small. It may be due to improper local material use, such as the material loss in a certain construction link exceeding expectations, but it has not had a great impact on the overall construction rhythm and surrounding construction units. In this regard, targeted local inspections and optimizations can be carried out to prevent the anomaly from expanding.

[0073] No anomalies are identified in other cases.

[0074] It should be noted that the present invention uses regional deviation to quantify the spatial impact, accurately locates anomalies from both the time and space dimensions, determines the anomaly level according to multiple deviation thresholds for hierarchical classification, provides a stepped early warning, can quickly identify risks of different degrees from minor waste to serious process problems, helps managers make efficient decisions, and improves the refined level of project management and the risk prevention and control ability.

[0075] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. A project production and operation early warning index management system, characterized in that: include: The material dynamic monitoring module obtains the static stockpiling inventory of each construction unit based on image recognition technology, and uses the weighing sensor installed on the construction device to detect and analyze the dynamic processing allowance, and analyzes the actual material consumption of each construction unit based on this; The progress coupling analysis module collects the structural entity images of each construction unit, uses a convolutional neural network to identify the completion status of the components, matches the current construction stage of each construction unit according to the preset progress plan model, and outputs the corresponding theoretical material consumption; The multi-dimensional deviation warning module performs time series anomaly detection and spatial correlation anomaly analysis on the actual material consumption and theoretical material consumption, and makes construction anomaly judgments and anomaly level identification based on the analysis results.

2. The engineering production and operation early warning index management system according to claim 1, characterized in that: The specific analysis method of the static stockpile is as follows: Obtain the construction images of each construction unit, locate the corresponding material stacking area, use image processing technology to obtain the images of each material in the material stacking area, and then compare and match them with the pre-saved standard material appearance images to obtain the type of each material and the volume of each material; The static stockpiling inventory of each material is obtained by combining the volume of each material and the corresponding preset reference density.

3. The engineering production and operation early warning index management system according to claim 2, characterized in that: The specific analysis method of the dynamic machining allowance is as follows: The weighing sensor installed on the construction machinery is used to obtain the total weight of the processed materials, and the material ratio of the corresponding processed materials is obtained. Based on the total weight of the processed materials and the material ratio, the material quality analysis is performed to obtain the dynamic processing allowance of each material.

4. The engineering production and operation early warning index management system according to claim 3, characterized in that: The specific process of analyzing the actual material consumption of each construction unit is as follows: Extract the material collection records of the material storage location, and obtain the construction unit, material type, and collection quantity corresponding to each material collection record; The material collection records are classified according to the construction units to obtain the material collection records corresponding to each construction unit, and the collection quantities corresponding to the same material type are accumulated to obtain the total collection quantity of each material; The static stockpiling stock and dynamic processing allowance of each material in each construction unit are summed to obtain the material allowance of each material; The total amount of each material collected by each construction unit and the material surplus are used to calculate the net consumption to obtain the actual material consumption of each material in each construction unit.

5. The engineering production and operation early warning index management system according to claim 1, characterized in that: The specific process of identifying the component completion status is as follows: Based on the structural entity image of each construction unit, the actual contour image of each component is constructed, and at the same time, the expected contour image of each component is obtained based on the construction plan; The actual contour image of each component is compared with the corresponding expected contour image, and the portion of the actual contour image of each component that overlaps with the corresponding expected contour image is recorded as a valid contour image, which is then used as the completion status of each component.

6. The engineering production and operation early warning index management system according to claim 5, characterized in that: The specific analysis method of the theoretical material consumption is as follows: Compare the effective contour image of each component with the expected contour image of the corresponding component in the construction plan to obtain the completion degree of each component; Based on the construction plan, obtain the type and theoretical consumption of each material corresponding to each component; The unnecessary materials other than the effective contour images of each component are recorded as the used materials, and at the same time, they are matched with the theoretical consumption of each material of each component to obtain the theoretical consumption of each used material of each component; The materials that still need to be used outside the effective contour image of each component are recorded as the materials to be used, and then matched with the theoretical consumption of each material of each component to obtain the complete component theoretical consumption of each material to be used, and then combined with the completion degree of each component for fusion analysis to obtain the theoretical consumption of each material to be used of each component; The theoretical consumption of each material that has been used for each component and the theoretical consumption of each material to be used are classified and summed to obtain the theoretical material consumption of each material in each construction unit.

7. The engineering production and operation early warning index management system according to claim 1, characterized in that: The specific analysis process of the timing anomaly detection is as follows: Several monitoring cycles are set based on the preset adaptive sliding time window length, and the theoretical material consumption and actual material consumption of each material of each construction unit in each monitoring cycle are extracted. Then, the deviation analysis is performed to obtain the absolute deviation of the actual material consumption relative to the theoretical material consumption, and the mean analysis of each absolute deviation is performed to obtain the material consumption deviation of each construction unit in each monitoring cycle; Compare the end time of each monitoring cycle with the end time of the current monitoring cycle to obtain the timing deviation reference coefficient of each monitoring cycle; The material consumption deviation of each construction unit in each monitoring period is integrated with the timing deviation reference coefficient for linear weighted comprehensive analysis to obtain the reference timing material deviation of each construction unit. Then, the actual material consumption and theoretical material consumption of each material in each construction unit are combined to perform timing material deviation analysis to obtain the adjacent timing material deviation of each construction unit.

8. The engineering production and operation early warning index management system according to claim 7, characterized in that: The specific analysis method of the spatial correlation anomaly analysis is as follows: Obtain the central distribution position of each component of each construction unit, and then locate the reference distribution position point of each construction unit; Connecting the reference distribution position points of each construction unit with other construction units to obtain the reference distribution distance between each construction unit and other construction units, and then comparing with the preset reference distribution distance threshold to identify the adjacent construction units of each construction unit; Based on the reference distribution spacing analysis between each construction unit and the corresponding adjacent construction units, the regional deviation reference coefficient of each construction unit corresponding to each adjacent construction unit is obtained; The absolute deviation between the actual material consumption and the theoretical material consumption of each material in each construction unit is calculated to obtain the absolute deviation of the actual material consumption relative to the theoretical material consumption; The reference coefficient of the regional deviation of each adjacent construction unit and the absolute deviation of the actual material consumption of each material relative to the theoretical material consumption are linearly weighted and fused to obtain the reference regional material deviation of each material, and then the maximum reference regional material deviation is selected as the reference regional material deviation of the corresponding construction unit through comparison; The material deviation of the reference area of ​​each construction unit and the absolute deviation of the actual material consumption relative to the theoretical material consumption are analyzed to obtain the material deviation of the adjacent area of ​​each construction unit.

9. The engineering production and operation early warning index management system according to claim 8, characterized in that: The specific analysis method for determining construction abnormality is as follows: The absolute deviation of the actual material consumption of each material in each construction unit relative to the theoretical material consumption is recorded as the absolute material deviation, and the maximum absolute material deviation is taken as the absolute material deviation of each construction unit; The absolute material deviation, adjacent time series material deviation and adjacent area material deviation of each construction unit are compared with the preset absolute material deviation threshold, adjacent time series material deviation threshold and adjacent area material deviation threshold to obtain the judgment result whether there is construction abnormality in each construction unit.

10. The engineering production and operation early warning index management system according to claim 9, characterized in that: The specific analysis of the abnormal level identification is as follows: If the absolute material deviation, adjacent time series material deviation and adjacent area material deviation of a construction unit are all greater than the corresponding absolute material deviation threshold, adjacent time series material deviation threshold and adjacent area material deviation threshold, the specific abnormality level is identified as level one abnormality; If the absolute material deviation of a construction unit is greater than the absolute material deviation threshold, and at the same time, one of the adjacent time series material deviation and the adjacent area material deviation is greater than the corresponding threshold, the specific abnormality level is identified as a secondary abnormality; If the absolute material deviation of a construction unit is greater than the absolute material deviation threshold, and the adjacent time series material deviation and the adjacent area material deviation are both less than the corresponding threshold, the specific abnormality level is identified as level 3 abnormality; In other cases, no abnormalities were identified.

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