CN115271511A - Method for supervising construction engineering quality - Google Patents
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Abstract
The invention discloses a construction engineering quality supervision method, which relates to the technical field of engineering supervision and comprises the following steps: the method comprises the following steps that operation workers log in a supervision platform and issue engineering detection tasks on the supervision platform; the supervision platform sorts the engineering detection tasks according to a preset rule, wherein if the engineering detection tasks are key engineering points, high-grade inspectors are allocated for detection; if the engineering points are common engineering points, primary inspectors are distributed for detection; when the inspector arrives at an engineering point, the engineering point is subjected to data acquisition and detection through an engineering measuring instrument, and the acquired supervision data is uploaded to a supervision platform through a data uploading module; a user sends a data acquisition instruction to a supervision platform through an intelligent terminal, and the supervision platform analyzes importance values of the called supervision data and judges whether the data is core data; if the supervision data is core data, encrypting and transmitting the core data; effectively avoiding data loss and stealing and greatly improving the safety of data.
Description
Technical Field
The invention relates to the technical field of project supervision, in particular to a construction project quality supervision method.
Background
Project supervision refers to the entrust of a supervision unit with related qualification by a party A, and represents a specialized service activity for monitoring the project construction of a party B by the party A according to project construction documents approved by the country, laws and regulations related to the project construction, project construction supervision contracts and other project construction contracts. After the engineering construction is finished, a supervision team is needed to check and accept the engineering result.
When the range of the construction project is large, a supervision team needs to check and examine a plurality of project points, and data acquisition and detection need to be carried out on the project points in the process of checking and accepting the project; in the prior art, corresponding inspectors cannot be reasonably allocated to carry out data acquisition and detection on engineering points according to the inspection merit values, so that the detection efficiency is low; the safety protection of the supervision data is lacked, and the risks of data loss and stealing exist; based on the defects, the invention provides a construction engineering quality supervision method.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a construction engineering quality supervision method.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides a method for supervising quality of construction engineering, including the following steps:
the method comprises the following steps: the method comprises the following steps that operation workers log in a supervision platform and issue an engineering detection task on the supervision platform; the engineering detection task comprises engineering point numbers, and each engineering point has a unique number;
step two: the supervision platform classifies and sorts the engineering detection tasks according to preset rules, sequentially allocates inspectors to detect according to the sorting of the engineering detection tasks, and the preset rules are as follows:
acquiring a detection optimal value JY of the engineering detection task, and comparing the detection optimal value JY with a preset detection optimal threshold value; if JY is more than or equal to the preset optimization threshold value, marking the corresponding engineering point as a key engineering point; if JY is less than the preset optimization threshold value, marking the corresponding engineering point as a common engineering point;
if the key engineering points are the key engineering points, high-level inspectors are distributed for detection; if the engineering point is a common engineering point, a primary inspector is allocated for detection; wherein, the grades of the inspectors comprise high grade, middle grade and low grade, and are pre-evaluated by the supervision center;
step three: when the inspector arrives at the engineering point, the engineering point is subjected to data acquisition and detection through an engineering measuring instrument, and the acquired supervision data is uploaded to a supervision platform through a data uploading module for research and analysis by operation workers; the supervision data carries security level information;
step four: a user sends a data acquisition instruction to a supervision platform through an intelligent terminal, the supervision platform analyzes the content of the data acquisition instruction to search the position of the corresponding data content after receiving the data acquisition instruction, and carries out importance value analysis on the called supervision data to judge whether the data is core data or not;
step five: when the supervision data is sent to an external environment, if the supervision data is core data, encryption transmission is carried out on the core data.
Further, the specific calculation method of the detection merit value JY is as follows:
acquiring engineering points corresponding to the engineering detection tasks, collecting the input cost and the construction time of the corresponding engineering points, and sequentially marking as Z1 and T1;
taking the position of an engineering point as a center, and marking an area with the radius of rt as a construction area; acquiring daily traffic flow information of a construction area within a preset time period; marking the daily traffic flow of the corresponding construction area as L1; comparing the traffic flow L1 with a preset traffic threshold value;
counting the number of times that the L1 is greater than a preset traffic threshold value to be Zb1; when the L1 is larger than a preset traffic threshold value, obtaining a difference value between the L1 and the preset traffic threshold value and summing the difference value to obtain a flow over-value LZ; calculating to obtain a traffic heat coefficient CS by using a formula CS = Zb1 Xg 1+ LZ Xg 2, wherein g1 and g2 are coefficient factors;
and calculating a detection merit value JY corresponding to the engineering detection task by using a formula JY = Z1 × g3+ T1 × g4+ CS × g5, wherein g3, g4 and g5 are coefficient factors.
Furthermore, a fingerprint detection unit is arranged in the data uploading module; before the inspector uploads the proctoring data, the fingerprint detection unit is used for fingerprint verification of the inspector; and after the fingerprint verification is passed, the data uploading module is used for stamping a time stamp on the supervision data and uploading the data to the supervision platform.
Further, the specific analysis steps of the supervision platform are as follows:
acquiring security level information corresponding to the supervision data, and marking the security level information as M1;
acquiring access record information corresponding to the supervision data within a preset time period; counting the total number of times of visiting the proctoring data as visiting frequency P1; setting the optimal visit coefficient of the supervision data as FY,
normalizing the access frequency, the security level value and the excellent access coefficient, taking the numerical values of the access frequency, the security level value and the excellent access coefficient, and calculating by using a formula ZY = P1 × b1+ M1 × b2+ FY × a3 to obtain an importance value ZY corresponding to the supervision data, wherein b1, b2 and b3 are preset coefficient factors;
comparing the importance value ZY with a set value; if ZY is larger than the set value, marking the corresponding supervision data as core data; otherwise, marking the corresponding proctoring data as normal data.
Further, the specific calculation method of the optimization coefficient FY is as follows:
marking the access duration in each access record information as FTi, counting the occurrence frequency of various conversion operation behaviors in the access process, and calculating to obtain a conversion value ZHI in the corresponding access process by combining the weight factors of the conversion operation behaviors stored in the database; calculating by using a formula FWi = FTi × a1+ ZHi × a2 to obtain an access value FWi, wherein a1 and a2 are preset coefficient factors;
comparing the access value FWi with a preset access threshold value; counting the number of times that FWi is greater than a preset access threshold value to be Zb2; when the FWi is larger than a preset access threshold, obtaining a difference value between the FWi and the preset access threshold, and summing to obtain an over-access total value CF; the optimization coefficient FY is calculated by using the formula FY = Zb2 × a3+ CF × a4, where a3 and a4 are preset coefficient factors.
Further, the access record information comprises access duration and conversion operation behavior in the access process; the conversion operation behavior includes zoom-out, zoom-in, copy, and modify.
Further, the specific verification method of the fingerprint detection unit is as follows:
the fingerprint detection unit randomly generates 1 to 10 finger fingerprints to be verified to a fingerprint input interface;
a detector inputs a fingerprint and collects the contact pressure and the contact area of the detector when inputting the fingerprint each time; when different fingers input fingerprints, the corresponding pressure threshold range and area threshold range are different;
comparing the contact pressure with a pressure threshold range of the corresponding finger, and comparing the contact area with an area threshold range of the corresponding finger; and if the contact pressure is within the pressure threshold range of the corresponding finger and the contact area is within the area threshold range of the corresponding finger, the fingerprint verification is passed.
Compared with the prior art, the invention has the beneficial effects that:
1. the supervision platform classifies and sorts the engineering detection tasks according to a preset rule, firstly, a detection optimal value JY corresponding to the engineering detection tasks is obtained by combining the investment cost, the construction time and the traffic heat coefficient, and if JY is more than or equal to a preset detection optimal threshold value, the corresponding engineering points are marked as key engineering points; otherwise, marking the corresponding engineering point as a common engineering point; the engineering detection tasks are sequenced according to the detection optimal value JY, and the detectors are sequentially distributed for detection; if the key engineering point is the key engineering point, allocating a high-grade inspector for detection; if the engineering point is a common engineering point, a primary inspector is allocated for detection; the human resources are reasonably utilized, and the detection efficiency is improved;
2. in the invention, when an inspector arrives at an engineering point, data acquisition and detection are carried out on the engineering point through an engineering measuring instrument, and acquired supervision data is uploaded to a supervision platform through a data uploading module for research and analysis of operation workers; before the inspector uploads the supervision data, fingerprint verification is carried out on the inspector, so that irrelevant persons are prevented from uploading the data at will, and authenticity and safety of the data are guaranteed; a user sends a data acquisition instruction to a supervision platform through an intelligent terminal, and after the supervision platform receives the data acquisition instruction, the importance value analysis is carried out on the called supervision data to judge whether the data is core data; if the core data is the core data, the core data is encrypted and transmitted, so that data loss and stealing are effectively avoided, and the data security is greatly improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic block diagram of a construction engineering quality supervision method according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a construction engineering quality supervision method includes the following steps:
the method comprises the following steps: the method comprises the following steps that operation workers log in a supervision platform and issue an engineering detection task on the supervision platform; the engineering detection task comprises engineering point numbers, and each engineering point has a unique number;
in the present embodiment, one project may be decomposed into a plurality of different project points;
step two: the supervision platform classifies and sorts the engineering detection tasks according to a preset rule, and sequentially allocates inspectors for detection according to the sorting of the engineering detection tasks, so that the human resources are reasonably utilized, and the detection efficiency is improved; the preset rule is specifically as follows:
acquiring engineering points corresponding to the engineering detection tasks, collecting the input cost and the construction time of the corresponding engineering points, and sequentially marking as Z1 and T1;
taking the position of an engineering point as a center, and marking an area with the radius of rt as a construction area; acquiring daily traffic flow information of a construction area within a preset time period; the traffic flow information comprises the flow of people and the flow of vehicles; marking the daily traffic flow of the corresponding construction area as L1;
comparing the traffic flow L1 with a preset traffic threshold, and counting the number of times that the L1 is greater than the preset traffic threshold as Zb1; when the L1 is larger than a preset traffic threshold, obtaining a difference value between the L1 and the preset traffic threshold and summing to obtain a flow over-value LZ; calculating to obtain a traffic heat coefficient CS by using a formula CS = Zb1 Xg 1+ LZ Xg 2, wherein g1 and g2 are coefficient factors;
carrying out normalization processing on the investment cost, the construction duration and the traffic heat coefficient, taking the numerical values of the investment cost, the construction duration and the traffic heat coefficient, and calculating by using a formula JY = Z1 × g3+ T1 × g4+ CS × g5 to obtain a detection merit value JY corresponding to the engineering detection task, wherein g3, g4 and g5 are coefficient factors;
comparing the detection optimal value JY with a preset detection optimal threshold value; if JY is more than or equal to the preset optimization threshold value, marking the corresponding engineering point as a key engineering point; if JY is less than a preset optimization threshold, marking the corresponding engineering point as a common engineering point;
sequencing the engineering detection tasks according to the detection optimal value JY, and sequentially allocating detectors for detection; if the key engineering point is the key engineering point, allocating a high-grade inspector for detection; if no high-level inspector exists, allocating a middle-level inspector for inspection, and so on;
if the engineering points are common engineering points, primary inspectors are distributed for detection; if no primary inspector exists, allocating a middle-level inspector to perform inspection, and so on; wherein, the grades of the inspectors comprise high grade, middle grade and low grade, and are pre-evaluated by the supervision center;
step three: when the inspector arrives at the engineering point, the engineering point is subjected to data acquisition and detection through an engineering measuring instrument, and the acquired supervision data is uploaded to a supervision platform through a data uploading module for research and analysis by operation workers; the supervision data carries the information of the security level;
wherein, a fingerprint detection unit is arranged in the data uploading module; before the inspector uploads the supervision data, the fingerprint detection unit is used for fingerprint verification of the inspector; after the fingerprint verification is passed, the data uploading module is used for stamping a time stamp on the supervision data and uploading the data to the supervision platform; therefore, irrelevant personnel are prevented from uploading data at will, and the authenticity and the safety of the data are ensured;
the specific verification method of the fingerprint detection unit comprises the following steps:
the fingerprint detection unit randomly generates 1 to 10 finger fingerprint verifications to a fingerprint input interface;
a detector inputs a fingerprint and collects the contact pressure and the contact area of the detector when inputting the fingerprint each time; the contact pressure is the contact pressure between the finger and the fingerprint input interface, and the contact area is the contact area between the finger and the fingerprint input interface; when different fingers input fingerprints, the corresponding pressure threshold range and area threshold range are different;
comparing the contact pressure with a pressure threshold range of the corresponding finger, and comparing the contact area with an area threshold range of the corresponding finger; if the contact pressure is within the pressure threshold range of the corresponding finger and the contact area is within the area threshold range of the corresponding finger, the fingerprint verification is passed;
step four: a user sends a data acquisition instruction to the supervision platform through the intelligent terminal, after the supervision platform receives the data acquisition instruction, the data acquisition instruction content is analyzed to search for the position of the corresponding data content, and then the corresponding supervision data is called and returned to the supervision platform; the supervision platform is used for analyzing the importance value of the called supervision data and judging whether the data is core data; the method specifically comprises the following steps:
acquiring security level information corresponding to the supervision data, and marking the security level information as M1;
acquiring access record information corresponding to the supervision data within a preset time period; the access record information comprises access duration and conversion operation behavior in the access process; the conversion operation behavior comprises reduction, enlargement, duplication and modification; counting the total number of times of visiting the proctoring data as visiting frequency P1;
marking the access duration in each access record information as FTi, counting the occurrence frequency of various conversion operation behaviors in the access process, and calculating to obtain a conversion value ZHI in the corresponding access process by combining the weight factors of the conversion operation behaviors stored in the database; calculating by using a formula FWi = FTi × a1+ ZHi × a2 to obtain an access value FWi, wherein a1 and a2 are preset coefficient factors;
comparing the access value FWi with a preset access threshold value; counting the number of times that FWi is greater than a preset access threshold value to be Zb2; when the FWi is larger than a preset access threshold, obtaining a difference value between the FWi and the preset access threshold, and summing to obtain an over-access total value CF; calculating to obtain a best-visit coefficient FY by using a formula FY = Zb2 × a3+ CF × a4, wherein a3 and a4 are preset coefficient factors;
normalizing the access frequency, the security level value and the excellent access coefficient, taking the numerical values of the access frequency, the security level value and the excellent access coefficient, and calculating by using a formula ZY = P1 × b1+ M1 × b2+ FY × a3 to obtain an importance value ZY corresponding to the supervision data, wherein b1, b2 and b3 are preset coefficient factors;
comparing the importance value ZY with a set value; if ZY is larger than the set value, marking the corresponding supervision data as core data; otherwise, marking the corresponding supervision data as common data;
step five: when the supervision data is sent to an external environment, if the supervision data is core data, the core data is encrypted and transmitted, data loss and stealing are effectively avoided, and data security is greatly improved.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
a method for supervising the quality of construction engineering comprises the following steps that when working, an operator logs in a supervision platform and issues an engineering detection task on the supervision platform; the supervision platform sorts and sorts the engineering detection tasks according to preset rules, firstly, the optimal detection value JY corresponding to the engineering detection tasks is obtained through calculation by combining the input cost, the construction duration and the traffic heat coefficient, and if JY is more than or equal to a preset optimal detection threshold value, the corresponding engineering points are marked as key engineering points; otherwise, marking the corresponding engineering point as a common engineering point; sequencing the engineering detection tasks according to the detection optimal value JY, and sequentially allocating detectors for detection; if the key engineering points are the key engineering points, high-level inspectors are distributed for detection; if the engineering point is a common engineering point, a primary inspector is allocated for detection; the human resources are reasonably utilized, and the detection efficiency is improved;
when the inspector arrives at the engineering point, the engineering measuring instrument acquires and detects data of the engineering point, and uploads the acquired supervision data to the supervision platform through the data uploading module for research and analysis of operation workers; the supervision data carries the information of the security level; before the inspector uploads the supervision data, fingerprint verification is carried out on the inspector, so that irrelevant personnel are prevented from uploading the data at will, and authenticity and safety of the data are guaranteed; a user sends a data acquisition instruction to a supervision platform through an intelligent terminal, and after the supervision platform receives the data acquisition instruction, the importance value analysis is carried out on the called supervision data to judge whether the data is core data; if the core data is the core data, the core data is encrypted and transmitted, so that data loss and stealing are effectively avoided, and the data security is greatly improved.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. A method for supervising the quality of construction engineering is characterized by comprising the following steps:
the method comprises the following steps: the method comprises the following steps that operation workers log in a supervision platform and issue engineering detection tasks on the supervision platform; the engineering detection task comprises engineering point numbers, and each engineering point has a unique number;
step two: the supervision platform classifies and sorts the engineering detection tasks according to preset rules, sequentially allocates inspectors to detect according to the sorting of the engineering detection tasks, and the preset rules are as follows:
acquiring a detection optimal value JY of the engineering detection task, and comparing the detection optimal value JY with a preset detection optimal threshold; if JY is larger than or equal to a preset optimization threshold, marking the corresponding engineering point as a key engineering point; if JY is less than a preset optimization threshold, marking the corresponding engineering point as a common engineering point;
if the key engineering points are the key engineering points, high-level inspectors are distributed for detection; if the engineering point is a common engineering point, a primary inspector is allocated for detection; wherein, the grades of the inspectors comprise high grade, middle grade and low grade, and are pre-evaluated by the supervision center;
step three: when the inspector arrives at the engineering point, the engineering point is subjected to data acquisition and detection through an engineering measuring instrument, and the acquired supervision data is uploaded to a supervision platform through a data uploading module for research and analysis by operation workers; the supervision data carries privacy level information;
step four: a user sends a data acquisition instruction to a supervision platform through an intelligent terminal, after the supervision platform receives the data acquisition instruction, the supervision platform analyzes the content of the data acquisition instruction to search the position of the corresponding data content, analyzes the importance value of the called supervision data and judges whether the data is core data or not;
step five: when the supervision data is sent to an external environment, if the supervision data is core data, encryption transmission is carried out on the core data.
2. The construction engineering quality supervision method according to claim 1, wherein the specific calculation method of the check merit value JY is:
acquiring engineering points corresponding to the engineering detection tasks, collecting the input cost and the construction time of the corresponding engineering points, and sequentially marking as Z1 and T1;
taking the position of an engineering point as a center, and marking an area with the radius of rt as a construction area; acquiring daily traffic flow information of a construction area within a preset time period; marking the daily traffic flow of the corresponding construction area as L1; comparing the traffic flow L1 with a preset traffic threshold value;
counting the number of times that the L1 is greater than a preset traffic threshold value to be Zb1; when the L1 is larger than a preset traffic threshold, obtaining a difference value between the L1 and the preset traffic threshold and summing to obtain a flow over-value LZ; calculating to obtain a traffic heat coefficient CS by using a formula CS = Zb1 Xg 1+ LZ Xg 2, wherein g1 and g2 are coefficient factors;
and calculating a detection merit value JY corresponding to the engineering detection task by using a formula JY = Z1 × g3+ T1 × g4+ CS × g5, wherein g3, g4 and g5 are coefficient factors.
3. The method for supervising the quality of the constructional engineering as recited in claim 1, wherein a fingerprint detection unit is disposed in the data uploading module; before the inspector uploads the proctoring data, the fingerprint detection unit is used for fingerprint verification of the inspector; and after the fingerprint verification is passed, the data uploading module is used for stamping a time stamp on the supervision data and uploading the data to the supervision platform.
4. The construction engineering quality supervision method according to claim 1, wherein the concrete analysis steps of the supervision platform are as follows:
acquiring security level information corresponding to the supervision data, and marking the security level information as M1;
acquiring access record information corresponding to the supervision data within a preset time period; counting the total number of times of visiting the supervision data as visiting frequency P1; setting the optimal visit coefficient of the supervision data as FY,
normalizing the access frequency, the security level value and the optimal access coefficient, taking the numerical values, and calculating by using a formula ZY = P1 × b1+ M1 × b2+ FY × a3 to obtain an importance value ZY corresponding to the proctoring data, wherein b1, b2 and b3 are preset coefficient factors;
comparing the importance value ZY with a set value; if ZY is larger than a set value, marking the corresponding supervision data as core data; otherwise, marking the corresponding proctoring data as normal data.
5. The method for supervising the quality of the constructional engineering as recited in claim 4, wherein the specific calculation method of the optimization coefficient FY is as follows:
marking the access duration in each access record information as FTi, counting the occurrence frequency of various conversion operation behaviors in the access process, and calculating to obtain a conversion value ZHI in the corresponding access process by combining the weight factors of the conversion operation behaviors stored in the database; calculating by using a formula FWi = FTi × a1+ ZHi × a2 to obtain an access value FWi, wherein a1 and a2 are preset coefficient factors;
comparing the access value FWi with a preset access threshold value; counting the number of times that FWi is greater than a preset access threshold value to be Zb2; when the FWi is larger than a preset access threshold, obtaining a difference value between the FWi and the preset access threshold, and summing the difference value to obtain a total over-access value CF; the optimization coefficient FY is calculated by using the formula FY = Zb2 × a3+ CF × a4, where a3 and a4 are preset coefficient factors.
6. The method for supervising the quality of construction projects according to claim 5, wherein the access log information includes access duration and conversion operation behavior during the access; the conversion operation behavior includes zoom-out, zoom-in, copy, and modification.
7. The construction engineering quality supervision method according to claim 3, wherein the specific verification method of the fingerprint detection unit is as follows:
the fingerprint detection unit randomly generates 1 to 10 finger fingerprint verifications to a fingerprint input interface;
a detector inputs a fingerprint and collects the contact pressure and the contact area of the detector when inputting the fingerprint each time; when different fingers input fingerprints, the corresponding pressure threshold range and area threshold range are different;
comparing the contact pressure with a pressure threshold range of the corresponding finger, and comparing the contact area with an area threshold range of the corresponding finger; if the contact pressure is within the pressure threshold range of the corresponding finger and the contact area is within the area threshold range of the corresponding finger, the fingerprint verification is passed.
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