CN111242456B - Inspection management method and device - Google Patents

Inspection management method and device Download PDF

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CN111242456B
CN111242456B CN202010013467.5A CN202010013467A CN111242456B CN 111242456 B CN111242456 B CN 111242456B CN 202010013467 A CN202010013467 A CN 202010013467A CN 111242456 B CN111242456 B CN 111242456B
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inspection
feature recognition
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CN111242456A (en
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陈江义
孙晓
夏群峰
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Zhejiang Supcon Technology Co Ltd
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    • G06Q50/04—Manufacturing
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
    • G07C1/20—Checking timed patrols, e.g. of watchman
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Abstract

The application discloses a patrol management method and device for effectively identifying whether patrol work is operated by a user. The method is applied to a patrol management device, wherein the patrol management device is a mobile intelligent terminal with a biological feature recognition function, and the patrol management method comprises the following steps: downloading a patrol task; starting a primary biological feature recognition function to perform biological feature recognition on a user; when the biological feature identification passes, starting the inspection task; and starting the biological feature recognition function once again when the inspection task finishes the preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished.

Description

Inspection management method and device
Technical Field
The application relates to the technical field of inspection, in particular to an inspection management method and an inspection management device.
Background
The technology-intensive industry (such as petrochemical industry) has the characteristics of complex production process, continuous production process, large dependency among links and the like, and any link is in error, so that chain reaction is possibly generated, and even disastrous results are caused.
The inspection quality is continuously improved, various occasional and random potential safety hazards are timely disappeared in germination, and an effective way for safe production is further realized. However, in some existing manual inspection works, illegal behaviors of other people for inspection sometimes occur, but the existing inspection management system cannot effectively identify and feed back the illegal behaviors, so that inspection quality is difficult to guarantee.
Disclosure of Invention
In view of the above, the present application provides a method and apparatus for managing patrol, so as to effectively identify whether the patrol is operated by the user in the whole process.
The inspection management method is applied to an inspection management device, wherein the inspection management device is a mobile intelligent terminal with a biological feature recognition function, and the inspection management method comprises the following steps:
downloading a patrol task;
starting a primary biological feature recognition function to perform biological feature recognition on a user;
when the biological feature identification passes, starting the inspection task;
and starting the biological feature recognition function once again when the inspection task finishes the preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished.
Optionally, the restarting the biometric feature recognition function when the inspection task completes the preset progress each time includes:
and restarting the biological feature recognition function once when the inspection task completes inspection points with preset proportions.
Optionally, the step of restarting the biometric feature recognition function once when the inspection task completes the inspection points with a preset ratio includes:
calculating the inspection progress when the current inspection point is reached, wherein the calculation formula is as follows
Wherein N is the total number of inspection points in the current inspection route, and x i The number of the inspection items under the ith inspection point in the current inspection route is x, the number of the inspection items in the current inspection point is the sorting number of the inspection items in the current inspection point, and t is the sorting number of the current inspection point in the current inspection route;
judging whether the current inspection point reaches a preset inspection progress y or not, wherein a judgment formula is g (t, x) = [ f (t+1, x)/y ] - [ f (t-1, x)/y ];
wherein [ (] is a Gaussian rounding function INT (); y is a preset percentage;
and if the current inspection point reaches a preset inspection progress y, executing biological feature recognition.
Optionally, the restarting the biometric feature recognition function when the inspection task completes the preset progress each time includes:
and starting the biological feature recognition function once again when the inspection task is carried out for a preset time.
Optionally, the complexity of the primary biometric feature recognition function performed before the start of the inspection task is highest, and the complexity of each biometric feature recognition function performed from the start of the inspection task to the end of the inspection task is randomly set.
Optionally, the randomly setting the complexity of each biometric feature recognition function from the start to the end of the inspection task includes:
the complexity of each biological feature recognition function performed from the start to the end of the inspection task is randomly set according to the weight.
Optionally, in the process of performing the inspection task, when the user passes the biometric feature recognition within a preset period of time or passes the biometric feature recognition continuously for a certain number of times, the biometric feature recognition function is not started again within a subsequent preset period of time.
Optionally, in the process of performing the inspection task, an information-summary algorithm MD5 is used to process the device name, the device ID and the inspection specific time in the image shot by each inspection point, and the processing result is used as the file name suffix of the image shot by the inspection point.
The utility model provides a management device patrols and examines, management device patrols and examines for the mobile intelligent terminal that has, and it includes biological feature recognition function module and main control module, wherein:
the main control module is used for downloading the inspection task; starting a primary biological feature recognition function to perform biological feature recognition on a user; when the biological feature identification passes, starting the inspection task; and starting the biological feature recognition function once again when the inspection task finishes the preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished.
Optionally, the main control module is further configured to process, by using MD5, a device name, a device ID, and a specific time of inspection in each inspection point shot picture in the process of performing the inspection task, and use a processing result as a file name suffix of the inspection point shot picture.
According to the technical scheme, the biological characteristic recognition is executed once at the beginning of the starting of the inspection task and every time the inspection task finishes the preset progress, the biological characteristics of the user are intermittently collected for a short time for many times to increase the difficulty of replacement inspection of other people, and whether the whole inspection work is operated by the user is effectively recognized, so that a good supervision function is achieved, and the inspection quality is ensured.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a patrol management method disclosed in an embodiment of the application;
FIG. 2 is a flowchart of a specific implementation method for restarting a biometric feature recognition function once every time a preset proportion of inspection points are completed in the inspection task according to the embodiment of the present application;
fig. 3 is a schematic diagram of an application scenario of a patrol management device according to an embodiment of the present application;
fig. 4 is a schematic diagram of an application scenario of another inspection management device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a patrol management device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application discloses a patrol management method which is applied to a patrol management device, wherein the patrol management device is a mobile intelligent terminal with a biological characteristic recognition function, and the mobile intelligent terminal can be a smart phone, a PDA (Personal Digital Assistant, a palm computer) or a tablet personal computer and the like. Referring to fig. 1, the inspection management method includes:
step S01: downloading the inspection task.
Specifically, a patrol operator logs in a patrol management system platform on a mobile intelligent terminal, downloads a patrol task from a central server, then carries out on-site patrol according to the patrol task by holding the mobile intelligent terminal to a specified patrol area, records patrol data, and uploads the acquired data to the central server.
A plurality of inspection points are distributed in an inspection area, and inspection basic data of each inspection point includes, but is not limited to: device code, device name (e.g., shaft, bearing, gear, etc.), device location (e.g., motor or drive location, etc.), inspection content (e.g., temperature, amount of wear, vibration or damage, etc.), inspection requirements (e.g., whether to take a photograph, whether to leave-on, etc.), inspection content standard values (e.g., upper temperature limit for heat generation, allowable values for wear, etc.). At least one inspection item is included under one inspection point, for example, the bearing wear and the motor temperature are two inspection items. The route that the patrol operator passes when patrolling a plurality of patrol points is called a patrol route. The enterprise self-defines the inspection point and plans the inspection route on the inspection management system platform according to the inspection basic requirement, when the inspection route is planned, the inspection task is set on the basis of the inspection route, and the same inspection route can be set into a plurality of inspection tasks. It can be said that the inspection task is set depending on the inspection route, and the inspection route is composed of inspection points.
The enterprise can make a patrol plan on a patrol management system platform according to the patrol basic requirements, distribute and issue patrol tasks, track the plan and task execution conditions, and effectively perform early warning management on the plan, the tasks and the execution.
In the process of making the inspection plan, the inspection plan can be made according to different dimensions such as hours, days, weeks, months and the like according to the frequency requirement of the inspection route execution, and meanwhile, the inspection task can be restrained from being lifted or delayed to be executed.
On the distribution and distribution of the inspection tasks, the inspection management system platform automatically or manually decomposes the responsibility people and responsibility groups of each inspection route in the inspection plan and distributes the inspection tasks in the form of formal tasks/inspection work orders. And the patrol operators download the patrol tasks which are required to be responsible by the mobile intelligent terminal. One patrol task may cross a plurality of patrol areas, so as to realize standardized management, the patrol management system platform generally allocates the patrol areas for each patrol operator, and when the patrol areas are switched, the mobile intelligent terminals of the original patrol operators are not allowed to enter, and the mobile intelligent terminals of other patrol operators need to be replaced, so that one patrol task is completed jointly through two or more mobile intelligent terminals.
Step S02: and starting a primary biological characteristic recognition function to perform biological characteristic recognition on the user.
Step S03: and when the biological characteristic identification passes, starting the inspection task.
Step S04: and starting the biological feature recognition function once again when the inspection task finishes the preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished.
Specifically, during the inspection process, there are illegal behaviors that are detected by others instead, and when the actual inspection is performed by others instead, a plurality of potential problems are caused, for example, say: the specific operation of some inspection often needs to be better understood and practical operation experience of inspection operators on business and equipment, and a certain training is needed to perform and complete tasks well, when other people replace inspection, comprehensive quality and operation experience of inspection personnel cannot be ensured, inspection requirements and inspection details of specific inspection points cannot be well controlled, and therefore related problems of equipment operation abnormality are often relatively slow, and hidden dangers cannot be found timely or cannot be accurately described. Efficient identification and feedback of these violations is now highly desirable. In this regard, the embodiment of the application increases the difficulty of substitution inspection of other people by intermittently collecting the biological characteristics of the user for a plurality of times in a short time, and effectively identifies whether the inspection work is operated by the user in the whole course, and is specifically described as follows:
the biological characteristic recognition technology is a technology for personal identity authentication through unique biological characteristics (such as fingerprints and faces) of human bodies, and is a personal identity authentication mode which has high reliability and is difficult to forge.
Biometric identification at inspection is intended to ensure that the inspection process operation is performed by the person. The mobile intelligent terminal requires a user to perform one time of biological feature identification before starting one inspection task, and requires the user to perform one time of biological feature identification when the inspection task completes a preset progress (for example, 10% of progress). The total times of biological feature recognition performed in the same inspection task are required to be kept at a reasonable frequency, the accuracy and the authenticity of fingerprint identification information verification cannot be guaranteed due to the fact that the frequency is too low, inspection progress can be delayed due to the fact that the frequency is too high, and an inspection operator can generate boring psychology.
The step S04 may be that the biometric feature recognition function is restarted once every time the inspection task completes the preset progress, or the biometric feature recognition function is restarted once every time the inspection task completes the inspection points of the preset proportion.
As shown in fig. 2, after the present inspection task is started to before the end, the biological feature recognition function is started again when the present inspection task completes the inspection point with the preset proportion, which specifically includes:
step S041: calculating the inspection progress when the current inspection point is reached, wherein the calculation formula is as follows
Wherein N is the total number of inspection points in the current inspection route, and x i And the number of the inspection items under the ith inspection point in the current inspection route is x, the sorting number of the inspection items in the current inspection point is x, and t is the sorting number of the current inspection point in the current inspection route.
Step S042: and judging whether the current inspection point reaches a preset inspection progress y, if so, entering a step S043, and if not, returning to the step S041. Wherein the judgment formula is
g(t,x)＝[f(t+1,x)/y]-[f(t-1,x)/y]；
Wherein [ (] is a Gaussian rounding function, i.e., INT (); y is a preset percentage; here we recommend that the fingerprint identification of the inspection operator is performed once every 10% of the inspection points after inspection, i.e. the recommended setting y=10%. And if the calculation result of the judgment formula is not 0, the current inspection point is considered to just reach the specified inspection progress to be detected.
Step S043: biometric identification is performed.
The biometric function that is activated each time may be, from the type of biometric, a fingerprint recognition function (as shown in fig. 3) or a face recognition function (as shown in fig. 4), and is not limited. In addition, the complexity of the biometric identification performed each time may be the same or different. The following only shows a fingerprint recognition method which is commonly used and has the lowest complexity: when the biological characteristics are fingerprints, the mobile intelligent terminal collects the fingerprints recorded by the user in a fingerprint scanning area, compares and contrasts the fingerprints in two or more fingerprint images stored in the mobile intelligent terminal in advance, and if the fingerprints are found to be consistent, the identity authentication is passed; otherwise the user needs to re-enter the fingerprint.
When the complexity of the biometric feature recognition modes performed each time is different, the complexity of the one-time biometric feature recognition mode performed before the start of the inspection task is the highest, and the complexity of each biometric feature recognition mode performed from the start of the inspection task to the end of the inspection task is randomly set. The random may be equal random or weight random, that is, weight is allocated to each secondary biological feature recognition mode according to complexity of biological feature recognition to form a random number table, and then a random number algorithm is adopted to extract corresponding random numbers from the random number table so as to obtain the current biological feature recognition mode.
Optionally, when the patrol operator passes the biometric identification within a preset period of time or passes the biometric identification a certain number of times continuously, the patrol operator will obtain a certain "exemption time" within a certain period of time. In the exemption time, the patrol operator does not need to perform biological feature recognition operation when executing a specific patrol task, namely, even if the patrol operator executes the patrol task to reach a specified patrol progress, the patrol operator does not need to perform biological feature recognition operation.
In addition, considering that the fake work of the inspection operator on the inspection point image information often adopts to directly select the inspection point image information shot before. Based on this, in the embodiment of the present application, MD5 (Message-Digest Algorithm) is used to process the device name, the device ID, and the specific time of inspection of each inspection point, and the processing result is used as the file name suffix of the image information of the inspection point, so as to prevent the situation of counterfeiting the image information of the inspection point.
Specifically, when a specific inspection task is executed, an inspection operator can directly shoot inspection point image information through an interface provided by a calling application, or store the newly shot inspection point image information into a local file system and then call the newly shot inspection point image information from the local file system. The directly shot inspection point image information can generally ensure the authenticity and instantaneity. However, if the image information of the inspection point is obtained from the local file system, it is possible that the inspection operator directly selects the image information of the inspection point photographed long before to perform the forgery work. Based on this, in the embodiment of the present application, MD5 (Message-Digest Algorithm) is used to process the device name, the device ID, and the specific time of inspection of each inspection point, and the processing result is used as the file name suffix of the image information of the inspection point.
The MD5 algorithm has the following characteristics: 1) Irreversible, the data information before encryption cannot be restored through the processing result of the MD5 encryption algorithm; 2) The result of the processing by the MD5 encryption algorithm is not regularly reproducible with a high degree of discreteness. Slight variations in the original information are likely to cause tremendous variations in the encryption algorithm; 3) Uniquely, the processing result after the data information is encrypted by the MD5 encryption algorithm is 128 bits, and the probability of generating the same processing result is very small. These characteristics of the MD5 algorithm prevent counterfeiting of the inspection point image information.
Therefore, the embodiment of the application executes the biological characteristic recognition once at the beginning of the starting of the inspection task and when the inspection task finishes the preset progress, and increases the difficulty of the inspection of other people by intermittently collecting the biological characteristics of the user for a plurality of times in a short time, and effectively recognizes whether the inspection work is operated by the user in the whole course, thereby playing a good role in supervision. In addition, the embodiment of the application ensures the instantaneity, the authenticity and the effectiveness of the data synchronized by the inspection work by using the MD5 algorithm to encrypt the inspection data, and further ensures the inspection quality. From the objective results, the embodiment of the application achieves the following purposes of patrol business management: the inspection operation flow is standardized, scientific working quality assessment is provided, and the illegal phenomenon of inspection data by other people instead of inspection or individual counterfeiting is prevented, so that the occurrence probability of potential safety hazards and safety accidents caused by human factors in the inspection flow is reduced, and the inspection operation flow can meet and be suitable for the inspection business requirements of high precision, high precision and high efficiency.
Corresponding to the above method embodiment, the embodiment of the present application also discloses a patrol management device, which is a mobile intelligent terminal, as shown in fig. 5, and includes a biometric feature recognition function module 100 and a main control module 200, wherein:
the main control module 200 is used for downloading the inspection task; starting a primary biological feature recognition function to perform biological feature recognition on a user; when the biological feature identification passes, starting the inspection task; and starting the biological feature recognition function once again when the inspection task finishes the preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished.
Optionally, the main control module 200 is further configured to process, by using MD5, the device name, the device ID and the specific time of inspection in each inspection point shot picture, and use the processing result as a file name suffix of the inspection point shot picture in the process of performing the inspection task.
Optionally, in any of the above-disclosed inspection management devices, the main control module 200 is specifically configured to restart the biometric feature recognition function once every time the inspection task completes an inspection point with a preset ratio.
Optionally, when the main control module 200 is configured to restart the biometric identification function once when the inspection task completes the inspection points with the preset ratio, the main control module 200 is specifically configured to calculate the inspection progress when the inspection task progresses to the current inspection point, where the calculation formula is
Wherein N is the total number of inspection points in the current inspection route, and x i The number of the inspection items under the ith inspection point in the current inspection route is x, the number of the inspection items in the current inspection point is the sorting number of the inspection items in the current inspection point, and t is the sorting number of the current inspection point in the current inspection route;
judging whether the current inspection point reaches a preset inspection progress y or not, wherein a judgment formula is g (t, x) = [ f (t+1, x)/y ] - [ f (t-1, x)/y ];
wherein [ (] is a Gaussian rounding function INT (); y is a preset percentage;
and if the current inspection point reaches a preset inspection progress y, executing biological feature recognition.
Alternatively, in any of the above-disclosed inspection management apparatuses, the main control module 200 is specifically configured to restart the biometric identification function once every preset time the present inspection task is performed.
Optionally, in any of the above-disclosed inspection management devices, the main control module 200 specifically adopts a configuration in which the complexity of the primary biometric feature recognition function performed before the inspection task is started is highest (the higher the complexity is, the higher the security level is), and the complexity of the primary biometric feature recognition function performed from the start to the end of the inspection task is randomly set.
Optionally, the complexity of each biometric feature recognition function performed from the start to the end of the inspection task is randomly set according to the weight.
Optionally, the main control module 200 is further configured to not start the biometric feature recognition function in a subsequent preset period of time when the user passes the biometric feature recognition within the preset period of time or passes the biometric feature recognition a certain number of times continuously during the inspection task.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
Those of skill in the art would understand that information, messages, and signals may be represented using any of a variety of different technologies and techniques. For example, the messages, information mentioned in the above description may be expressed as voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or any combination thereof.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
For system embodiments, the description is relatively simple as it corresponds substantially to method embodiments, and reference is made to the description of method embodiments for relevant points. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present application without undue burden.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in the embodiments may be accomplished by computer programs stored in a computer-readable storage medium, which when executed, may include the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the embodiments of the application. Thus, the present embodiments are not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1. The inspection management method is characterized by being applied to an inspection management device, wherein the inspection management device is a mobile intelligent terminal with a biological feature recognition function, and the inspection management method comprises the following steps:
downloading a patrol task;
starting a primary biological feature recognition function to perform biological feature recognition on a user;
when the biological feature identification passes, starting the inspection task;
starting a biological feature recognition function again when the inspection task finishes a preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished;
the method for restarting the biological feature recognition function when the inspection task finishes the preset progress comprises the following steps:
starting the biological feature recognition function once again when the inspection task completes inspection points with preset proportions;
the biological feature recognition function is started once again when the inspection task completes inspection points with preset proportions, and the method comprises the following steps:
calculating the inspection progress when the current inspection point is reached, wherein the calculation formula is as follows
Wherein N is the total number of inspection points in the current inspection route, and x i The number of the inspection items under the ith inspection point in the current inspection route is x, the number of the inspection items in the current inspection point is the sorting number of the inspection items in the current inspection point, and t is the sorting number of the current inspection point in the current inspection route;
judging whether the current inspection point reaches a preset inspection progress y or not, wherein a judgment formula is that
g(t,x)＝[f(t+1,x)/y]-[f(t-1,x)/y]；
Wherein [ (] is a Gaussian rounding function INT (); y is a preset percentage;
and if the current inspection point reaches a preset inspection progress y, executing biological feature recognition.
2. The inspection management method according to claim 1, wherein the restarting the biometric identification function each time the inspection task completes a preset schedule comprises:
and starting the biological feature recognition function once again when the inspection task is carried out for a preset time.
3. The inspection management method according to claim 1, wherein the complexity of the one-time biometric feature recognition function performed before the inspection task is started is highest, and the complexity of each biometric feature recognition function performed from the start to the end of the inspection task is randomly set.
4. The inspection management method according to claim 1, wherein the complexity of each biometric feature recognition function performed from the start to the end of the inspection task is randomly set, comprising:
the complexity of each biological feature recognition function performed from the start to the end of the inspection task is randomly set according to the weight.
5. The inspection management method according to claim 4, wherein during the inspection task, when the user passes the biometric identification within a predetermined period of time or passes the biometric identification a predetermined number of times continuously, the biometric identification function is not started for a predetermined period of time.
6. The inspection management method according to claim 1, wherein in the process of performing the inspection task, an information-summary algorithm MD5 is adopted to process a device name, a device ID and an inspection specific time in each inspection point shot picture, and a processing result is used as a file name suffix of the inspection point shot picture.
7. The utility model provides a management device patrols and examines, its characterized in that, management device patrols and examines for the mobile intelligent terminal that has, and it includes biological feature recognition function module and main control module, wherein:
the main control module is used for downloading the inspection task; starting a primary biological feature recognition function to perform biological feature recognition on a user; when the biological feature identification passes, starting the inspection task; starting a biological feature recognition function again when the inspection task finishes a preset progress, and continuing the inspection task only when the current biological feature recognition is passed until the inspection task is finished;
the method for restarting the biological feature recognition function when the inspection task finishes the preset progress comprises the following steps:
starting the biological feature recognition function once again when the inspection task completes inspection points with preset proportions;
the biological feature recognition function is started once again when the inspection task completes inspection points with preset proportions, and the method comprises the following steps:
calculating the inspection progress when the current inspection point is reached, wherein the calculation formula is as follows
Wherein N is the total number of inspection points in the current inspection route, and x i The number of the inspection items under the ith inspection point in the current inspection route is x, the number of the inspection items in the current inspection point is the sorting number of the inspection items in the current inspection point, and t is the sorting number of the current inspection point in the current inspection route;
judging whether the current inspection point reaches a preset inspection progress y or not, wherein a judgment formula is that
g(t,x)＝[f(t+1,x)/y]-[f(t-1,x)/y]；
Wherein [ (] is a Gaussian rounding function INT (); y is a preset percentage;
and if the current inspection point reaches a preset inspection progress y, executing biological feature recognition.
8. The inspection management device according to claim 7, wherein the main control module is further configured to process, by using MD5, a device name, a device ID, and an inspection specific time in each inspection point shot picture during the inspection task, and use a processing result as a file name suffix of the inspection point shot picture.
CN202010013467.5A 2020-01-07 2020-01-07 Inspection management method and device Active CN111242456B (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103400426A (en) * 2013-07-22 2013-11-20 北京新一代照明有限公司 Highway facility polling device and method
CN104751532A (en) * 2015-03-30 2015-07-01 国家电网公司 Universal patrol system and patrol method thereof
CN108873826A (en) * 2017-05-08 2018-11-23 台泥资讯股份有限公司 inspection management method and system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103400426A (en) * 2013-07-22 2013-11-20 北京新一代照明有限公司 Highway facility polling device and method
CN104751532A (en) * 2015-03-30 2015-07-01 国家电网公司 Universal patrol system and patrol method thereof
CN108873826A (en) * 2017-05-08 2018-11-23 台泥资讯股份有限公司 inspection management method and system

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