Workshop inspection method, system, equipment and medium based on industrial Internet of Things

Abstract

The present application discloses a workshop inspection method, system, equipment and medium based on the industrial Internet of Things, and relates to the technical field of the industrial Internet of Things. The method comprises: obtaining the current status of each production equipment in the workshop, and determining the equipment to be inspected from the production equipment according to the current status; obtaining the dust concentration data of the workshop, and determining at least one inspection sub-area according to the dust concentration data and the equipment to be inspected; for each inspection sub-area, determining the distribution density according to the area of ​​the sub-area and the number of equipment; for each inspection sub-area, determining the dust concentration representative value of the inspection sub-area according to the dust concentration data, and determining the inspection parameters of the inspection sub-area according to the dust concentration representative value and the distribution density; generating inspection control instructions according to the inspection parameters. The present application has the effect of improving the intelligent level of workshop inspection.

Description

Technical Field

[0001] The present application relates to the technical field of industrial Internet of Things, and in particular to a workshop inspection method, system, equipment and medium based on the industrial Internet of Things. Background Art

[0002] In modern production workshops, smooth equipment operation and safety are of vital importance, directly affecting the production efficiency and economic benefits of enterprises. In order to ensure the good condition of equipment and avoid potential safety hazards, regular equipment inspections are indispensable. Traditional inspection methods usually rely on manual scheduled inspections, and inspectors inspect and maintain equipment according to a set schedule. Although this method can ensure a certain frequency of inspections, there are often many shortcomings, such as fatigue, lack of concentration and missed inspections that may occur during manual inspections, which not only restricts the coverage and accuracy of inspections, but also increases the risk of equipment failure, thereby affecting the continuity and safety of production.

[0003] The continuous advancement of science and technology has prompted robot inspections to gradually enter workshop management. At present, robot inspections are scheduled inspections. Through automated means, robot inspections can efficiently and accurately obtain the real-time status of equipment. Robot inspections reduce the burden of manual tasks and ensure the inspection progress to a certain extent. However, with the complexity of the production environment, this inspection method is relatively limited and it is difficult to meet the current intelligent and complex inspection requirements of workshops. Summary of the invention

[0004] In order to improve the intelligence level of workshop inspection and thus improve the management ability of the workshop, this application provides a workshop inspection method, system, equipment and medium based on industrial Internet of Things.

[0005] In the first aspect, the present application provides a workshop inspection method based on the industrial Internet of Things, which adopts the following technical solutions:

[0006] The workshop inspection method based on the industrial Internet of Things is applied to the industrial Internet of Things system, wherein the industrial Internet of Things system includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication. The method is executed by the management platform and includes:

[0007] Obtain the current status of each production equipment in the workshop, and determine the equipment to be inspected from the production equipment according to the current status;

[0008] Acquire dust concentration data of the workshop, and determine at least one inspection sub-area according to the dust concentration data and the equipment to be inspected;

[0009] For each inspection sub-area, obtaining the sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area, and determining the distribution density according to the sub-area area and the number of devices;

[0010] For each inspection sub-area, determining a representative value of dust concentration of the inspection sub-area according to the dust concentration data, and determining an inspection parameter of the inspection sub-area according to the representative value of dust concentration and the distribution density;

[0011] An inspection control instruction is generated according to the inspection parameters to control the inspection robot to inspect the at least one inspection sub-area.

[0012] By adopting the above technical scheme, the current status of each production equipment in the workshop is first obtained, and the equipment to be inspected is determined from the production equipment according to the current status, and then the dust concentration data of the workshop is obtained, and at least one inspection sub-area is determined according to the dust concentration data and the equipment to be inspected, and then for each inspection sub-area, the sub-area area corresponding to the inspection sub-area and the number of equipment to be inspected in the inspection sub-area are obtained, and the distribution density is determined according to the sub-area area and the number of equipment, and then for each inspection sub-area, the representative value of the dust concentration of the inspection sub-area is determined according to the dust concentration data, and the inspection parameters of the inspection sub-area are determined according to the representative value of the dust concentration and the distribution density, and finally, the inspection control instructions are generated according to the inspection parameters to control the inspection robot to inspect at least one inspection sub-area. Compared with the manual inspection or the scheduled inspection by the inspection robot in the workshop, the reliability and accuracy of the workshop inspection are improved, and it can better meet the current intelligent and complex inspection requirements of the workshop.

[0013] Optionally, the step of acquiring the current status of each production equipment in the workshop and determining the equipment to be inspected from the production equipment according to the current status includes:

[0014] Acquire the current status of each production equipment in the workshop, wherein the current status includes working status, waiting status and shutdown status;

[0015] The production equipment in the working state and the waiting state is used as equipment to be inspected.

[0016] By adopting the above technical solution, the current status of each production equipment in the workshop is first obtained, and the current status includes working status, waiting status and shutdown status. Then, the production equipment in the working status and waiting status is taken as the equipment to be inspected.

[0017] Optionally, the step of determining at least one inspection sub-area according to the dust concentration data and the equipment to be inspected includes:

[0018] Acquire the location data of the equipment to be inspected, and determine the estimated value of the dust concentration at the location of the equipment to be inspected according to the location data and the dust concentration data;

[0019] Acquire wind speed data in the workshop, and determine an estimated wind speed value at the location of the equipment to be inspected based on the wind speed data;

[0020] A feature vector corresponding to the equipment to be inspected is constructed according to the dust concentration estimate value, the wind speed estimate value and the position data, and the workshop is divided into at least one inspection sub-area based on a preset clustering algorithm and the feature vector.

[0021] By adopting the above technical solution, in order to determine at least one inspection sub-area, the location data of the equipment to be inspected is first obtained, and the estimated dust concentration value of the location of the equipment to be inspected is determined based on the location data and the dust concentration data, then the wind speed data in the workshop is obtained, and the estimated wind speed value of the location of the equipment to be inspected is determined based on the wind speed data, then a feature vector corresponding to the equipment to be inspected is constructed based on the dust concentration estimate, the wind speed estimate and the location data, and the workshop is divided into at least one inspection sub-area based on a preset clustering algorithm and the feature vector.

[0022] Optionally, the step of determining the estimated value of dust concentration at the location of the equipment to be inspected according to the location data and the dust concentration data includes:

[0023] extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data;

[0024] For each device to be inspected, the coordinate data of each dust concentration monitoring point is obtained, and the monitoring distance from each dust concentration monitoring point to the device to be inspected is determined according to the position data and the coordinate data;

[0025] The monitoring distance is screened according to a preset distance range to obtain a corresponding effective monitoring distance;

[0026] Acquire the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance according to the effective monitoring distance, and use the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance as the effective dust concentration;

[0027] An estimated value of dust concentration at the location of the equipment to be inspected is calculated based on the effective monitoring distance and the effective dust concentration.

[0028] By adopting the above technical scheme, in order to determine the estimated value of dust concentration, the dust concentration monitoring value corresponding to each dust concentration monitoring point is extracted from the dust concentration data according to the dust concentration data, and then for each equipment to be inspected, the coordinate data of each dust concentration monitoring point is obtained, and the monitoring distance from each dust concentration monitoring point to the equipment to be inspected is determined according to the position data and the coordinate data, and then the monitoring distance is screened according to the preset distance range to obtain the corresponding effective monitoring distance, and then the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance is obtained according to the effective monitoring distance, and the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance is used as the effective dust concentration, and finally the dust concentration estimate of the location of the equipment to be inspected is calculated according to the effective monitoring distance and the effective dust concentration.

[0029] Optionally, the step of determining the representative value of the dust concentration of the inspection sub-area according to the dust concentration data includes:

[0030] extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data;

[0031] Obtaining a spatial model of the workshop, and determining an effective coverage space corresponding to the dust concentration monitoring point according to the spatial model;

[0032] Determine the dust amount representative value corresponding to the inspection sub-area according to the dust concentration monitoring value corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and determine the corresponding coverage space range according to the effective coverage space corresponding to the dust concentration monitoring point;

[0033] The representative value of dust concentration in the inspection sub-area is determined according to the representative value of dust amount and the coverage space range.

[0034] By adopting the above technical scheme, in order to determine the representative value of dust concentration in the inspection sub-area, the dust concentration monitoring values ​​corresponding to each dust concentration monitoring point are first extracted from the dust concentration data according to the dust concentration data, and then the spatial model of the workshop is obtained, and the effective coverage space corresponding to the dust concentration monitoring point is determined according to the spatial model, and then the representative value of dust amount corresponding to the inspection sub-area is determined according to the dust concentration monitoring values ​​corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and the corresponding coverage space range is determined according to the effective coverage space corresponding to the dust concentration monitoring point, and finally the representative value of dust concentration in the inspection sub-area is determined according to the representative value of dust amount and the coverage space range.

[0035] Optionally, the inspection parameters include an optimal number of inspection robots;

[0036] The step of determining the inspection parameters of the inspection sub-area according to the dust concentration representative value and the distribution density comprises:

[0037] Obtaining the number of sub-areas corresponding to the inspection sub-area, and determining the average value of dust concentration according to the representative value of dust concentration and the number of sub-areas, and determining the average value of distribution density according to the distribution density and the number of sub-areas;

[0038] Determine the weight corresponding to each inspection sub-area according to the dust concentration average value, the distribution density average value, the dust concentration representative value and the distribution density, and determine the corresponding inspection robot ratio according to the weight corresponding to each inspection sub-area;

[0039] The total number of inspection robots in the workshop is obtained, and the optimal number of inspection robots corresponding to each inspection sub-area is determined according to the inspection robot ratio and the total number of robots.

[0040] By adopting the above technical scheme, in order to determine the optimal number of inspection robots corresponding to each inspection sub-area, the number of sub-areas corresponding to the inspection sub-area is obtained, and the average dust concentration value is determined according to the representative value of dust concentration and the number of sub-areas, and the average distribution density value is determined according to the distribution density and the number of sub-areas, and then the weight corresponding to each inspection sub-area is determined according to the average dust concentration value, the average distribution density value, the representative value of dust concentration and the distribution density, and the corresponding proportion of inspection robots is determined according to the weight corresponding to each inspection sub-area, and then the total number of inspection robots in the workshop is obtained, and the optimal number of inspection robots corresponding to each inspection sub-area is determined according to the proportion of inspection robots and the total number of robots.

[0041] Optionally, also include:

[0042] During the inspection by the inspection robot, the inspection robot obtains the current working parameters of the device to be inspected, and determines whether the current working parameters are within a preset range according to the current working parameters;

[0043] If not, abnormal operation information is generated according to the current working parameters, and the abnormal operation information is sent to the inspection terminal of the inspection personnel;

[0044] If so, normal operation information is generated according to the current working parameters, and the normal operation information is sent to the inspection terminal of the inspection personnel.

[0045] By adopting the above-mentioned technical scheme, during the inspection process of the inspection robot, the current working parameters of the equipment to be inspected are obtained by the inspection robot, and it is determined whether the current working parameters are within the preset range based on the current working parameters. If the current working parameters are within the preset range, abnormal operation information is generated based on the current working parameters, and the abnormal operation information is sent to the inspection terminal of the inspection personnel. If the current working parameters are not within the preset range, normal operation information is generated based on the current working parameters, and the normal operation information is sent to the inspection terminal of the inspection personnel.

[0046] On the second aspect, this application also provides a workshop inspection system based on the industrial Internet of Things, which adopts the following technical solutions:

[0047] The workshop inspection system based on the industrial Internet of Things includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication, and the management platform is configured with:

[0048] A module for determining equipment to be inspected, used to obtain the current status of each production equipment in the workshop, and determine the equipment to be inspected from the production equipment according to the current status;

[0049] An inspection sub-area determination module, used to obtain dust concentration data of the workshop, and determine at least one inspection sub-area according to the dust concentration data and the equipment to be inspected;

[0050] A distribution density determination module is used to obtain, for each inspection sub-area, a sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area, and determine the distribution density according to the sub-area area and the number of devices;

[0051] An inspection parameter determination module, configured to determine, for each inspection sub-area, a representative value of dust concentration of the inspection sub-area according to the dust concentration data, and determine an inspection parameter of the inspection sub-area according to the representative value of dust concentration and the distribution density;

[0052] The inspection control module is used to generate an inspection control instruction according to the inspection parameters to control the inspection robot to inspect the at least one inspection sub-area.

[0053] In a third aspect, the present application also provides a computer device, which adopts the following technical solution:

[0054] A computer device comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method described in the first aspect when executing the computer program.

[0055] In a fourth aspect, the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0056] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the method described in the first aspect.

[0057] To summarize, the present application includes at least the following beneficial technical effects: first, the current status of each production equipment in the workshop is obtained, and the equipment to be inspected is determined from the production equipment according to the current status; then, the dust concentration data of the workshop is obtained, and at least one inspection sub-area is determined according to the dust concentration data and the equipment to be inspected; then, for each inspection sub-area, the sub-area area corresponding to the inspection sub-area and the number of equipment to be inspected in the inspection sub-area are obtained, and the distribution density is determined according to the sub-area area and the number of equipment; then, for each inspection sub-area, a representative value of the dust concentration of the inspection sub-area is determined according to the dust concentration data, and the inspection parameters of the inspection sub-area are determined according to the representative value of the dust concentration and the distribution density; finally, an inspection control instruction is generated according to the inspection parameters to control the inspection robot to inspect at least one inspection sub-area. Compared with manual inspection in the workshop or scheduled inspection by inspection robots, the reliability and accuracy of workshop inspection are improved, and the current intelligent and complex inspection requirements of workshops can be better met. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present application.

[0059] Figure 2 It is a structural diagram of one of the application scenarios of the embodiment of the present application.

[0060] Figure 3 It is a structural diagram of another application scenario of an embodiment of the present application.

[0061] Figure 4 It is a structural block diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-4 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] The embodiment of the present application discloses a workshop inspection method based on industrial Internet of Things.

[0064] Reference Figure 1 The workshop inspection method based on the industrial Internet of Things is applied to the industrial Internet of Things system. The industrial Internet of Things system includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication. The method is executed by the management platform and includes:

[0065] Step S11, obtaining the current status of each production equipment in the workshop, and determining the equipment to be inspected from the production equipment according to the current status.

[0066] Step S12: acquiring dust concentration data of the workshop, and determining at least one inspection sub-area according to the dust concentration data and the equipment to be inspected.

[0067] Step S13: for each inspection sub-area, the sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area are obtained, and the distribution density is determined according to the sub-area area and the number of devices.

[0068] It can be understood that the calculation formula for distribution density is , where D represents the number of devices to be inspected per unit area, that is, the distribution density, N represents the number of devices to be inspected in the inspection sub-area, and A represents the area of ​​the inspection sub-area.

[0069] Step S14: for each inspection sub-area, determine a representative value of dust concentration of the inspection sub-area according to the dust concentration data, and determine an inspection parameter of the inspection sub-area according to the representative value of dust concentration and distribution density.

[0070] Step S15, generating an inspection control instruction according to the inspection parameters to control the inspection robot to inspect at least one inspection sub-area.

[0071] In the above implementation, the current status of each production equipment in the workshop is first obtained, and the equipment to be inspected is determined from the production equipment according to the current status, and then the dust concentration data of the workshop is obtained, and at least one inspection sub-area is determined according to the dust concentration data and the equipment to be inspected, and then for each inspection sub-area, the sub-area area corresponding to the inspection sub-area and the number of equipment to be inspected in the inspection sub-area are obtained, and the distribution density is determined according to the sub-area area and the number of equipment, and then for each inspection sub-area, the representative value of the dust concentration of the inspection sub-area is determined according to the dust concentration data, and the inspection parameters of the inspection sub-area are determined according to the representative value of the dust concentration and the distribution density, and finally, an inspection control instruction is generated according to the inspection parameters to control the inspection robot to inspect at least one inspection sub-area. Compared with manual inspection or scheduled inspection by inspection robots in workshops, the reliability and accuracy of workshop inspections are improved, and the current intelligent and complex inspection requirements of workshops can be better met.

[0072] As a further implementation method of the workshop inspection method, the steps of obtaining the current status of each production equipment in the workshop and determining the equipment to be inspected from the production equipment according to the current status include:

[0073] Step S21, obtaining the current status of each production equipment in the workshop, the current status includes working status, waiting status and shutdown status.

[0074] Step S22, taking the production equipment in the working state and the waiting state as the equipment to be inspected.

[0075] In the above implementation, the current status of each production equipment in the workshop is first obtained, the current status includes working status, waiting status and shutdown status, and then the production equipment in the working status and waiting status is taken as the equipment to be inspected.

[0076] As a further implementation of the workshop inspection method, the step of determining at least one inspection sub-area according to the dust concentration data and the equipment to be inspected includes:

[0077] Step S31, obtaining the position data of the equipment to be inspected, and determining the estimated value of the dust concentration at the location of the equipment to be inspected according to the position data and the dust concentration data.

[0078] Step S32, obtaining wind speed data in the workshop, and determining the estimated wind speed value at the location of the equipment to be inspected based on the wind speed data.

[0079] Specifically, for each device to be inspected, coordinate data of the device to be inspected is obtained according to the position data; the coordinate data is input into a pre-generated wind speed estimation model to obtain a wind speed estimation value at the location of the device to be inspected.

[0080] Step S33, constructing a feature vector corresponding to the equipment to be inspected according to the dust concentration estimation value, the wind speed estimation value and the position data, and dividing the workshop into at least one inspection sub-area based on a preset clustering algorithm and the feature vector.

[0081] It should be noted that, in this embodiment, the location data of each device to be inspected includes its corresponding specific coordinates. For each device to be inspected, the dust concentration estimate is represented by D (µg / m³), the wind speed estimate is represented by W (m / s or km / h), and the location data is represented by coordinates (X, Y). Then the feature vector X i =[D i W i X i Y i ]express.

[0082] It should be further explained that after the feature vectors corresponding to the equipment to be inspected are constructed, a feature vector matrix is ​​constructed based on the feature vectors corresponding to all the equipment to be inspected, and then a suitable clustering algorithm (K-means, DBSCAN, hierarchical clustering, etc.) is selected to process the feature vector matrix to obtain the corresponding clustering results, and the workshop is divided into at least one inspection sub-area according to the clustering results.

[0083] In the above embodiment, in order to determine at least one inspection sub-area, the location data of the equipment to be inspected is first obtained, and the estimated dust concentration value of the location of the equipment to be inspected is determined based on the location data and the dust concentration data. Then, the wind speed data in the workshop is obtained, and the estimated wind speed value of the location of the equipment to be inspected is determined based on the wind speed data. Then, a feature vector corresponding to the equipment to be inspected is constructed based on the dust concentration estimate, the wind speed estimate and the location data, and the workshop is divided into at least one inspection sub-area based on the preset clustering algorithm and the feature vector.

[0084] As a further implementation method of the workshop inspection method, the step of determining the dust concentration estimation value at the location of the equipment to be inspected according to the location data and the dust concentration data includes:

[0085] Step S41 : extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data.

[0086] Step S42: for each device to be inspected, the coordinate data of each dust concentration monitoring point is obtained, and the monitoring distance from each dust concentration monitoring point to the device to be inspected is determined according to the position data and the coordinate data.

[0087] Step S43, screening the monitoring distance according to the preset distance range to obtain the corresponding effective monitoring distance.

[0088] It can be understood that the effective monitoring distance is a monitoring distance within a preset distance range.

[0089] Step S44, obtaining the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance according to the effective monitoring distance, and taking the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance as the effective dust concentration.

[0090] Step S45, calculating the estimated value of the dust concentration at the location of the equipment to be inspected according to the effective monitoring distance and the effective dust concentration.

[0091] It should be noted that, in this embodiment, the calculation formula for the dust concentration estimation value is:

[0092]

[0093] Among them, d i Indicates the effective monitoring distance, C i Indicates effective dust concentration.

[0094] In the above embodiment, in order to determine the estimated dust concentration value, the dust concentration monitoring value corresponding to each dust concentration monitoring point is extracted from the dust concentration data according to the dust concentration data, and then for each equipment to be inspected, the coordinate data of each dust concentration monitoring point is obtained, and the monitoring distance from each dust concentration monitoring point to the equipment to be inspected is determined according to the position data and the coordinate data, and then the monitoring distance is screened according to the preset distance range to obtain the corresponding effective monitoring distance, and then the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance is obtained according to the effective monitoring distance, and the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance is used as the effective dust concentration, and finally the dust concentration estimate of the location of the equipment to be inspected is calculated according to the effective monitoring distance and the effective dust concentration.

[0095] As a further implementation of the workshop inspection method, the step of determining the representative value of the dust concentration of the inspection sub-area according to the dust concentration data includes:

[0096] Step S51 : extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data.

[0097] Step S52, obtaining a spatial model of the workshop, and determining the effective coverage space corresponding to the dust concentration monitoring point according to the spatial model.

[0098] Step S53, determining the dust amount representative value corresponding to the inspection sub-area according to the dust concentration monitoring value corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and determining the corresponding coverage space range according to the effective coverage space corresponding to the dust concentration monitoring point.

[0099] Step S54, determining the representative value of dust concentration in the inspection sub-area according to the representative value of dust amount and the coverage space range.

[0100] In the above embodiment, in order to determine the representative value of dust concentration in the inspection sub-area, the dust concentration monitoring values ​​corresponding to each dust concentration monitoring point are first extracted from the dust concentration data based on the dust concentration data, and then the spatial model of the workshop is obtained, and the effective coverage space corresponding to the dust concentration monitoring point is determined based on the spatial model. Then, the representative value of dust amount corresponding to the inspection sub-area is determined based on the dust concentration monitoring values ​​corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and the corresponding coverage space range is determined based on the effective coverage space corresponding to the dust concentration monitoring point. Finally, the representative value of dust concentration in the inspection sub-area is determined based on the dust amount representative value and the coverage space range.

[0101] As a further implementation method of the workshop inspection method, the inspection parameters include the optimal number of inspection robots, and the step of determining the inspection parameters of the inspection sub-area according to the representative value of dust concentration and the distribution density includes:

[0102] Step S61, obtaining the number of sub-areas corresponding to the inspection sub-area, and determining the average value of dust concentration according to the representative value of dust concentration and the number of sub-areas, and determining the average value of distribution density according to the distribution density and the number of sub-areas.

[0103] Step S62, determining the weight corresponding to each inspection sub-area according to the average dust concentration, the average distribution density, the representative value of dust concentration and the distribution density, and determining the corresponding inspection robot ratio according to the weight corresponding to each inspection sub-area.

[0104] It should be noted that, in step S62, the weight calculation formula is:

[0105]

[0106] Among them, W i represents the weight corresponding to the i-th inspection sub-area; C i represents the representative value of dust concentration corresponding to the i-th inspection sub-area; D i represents the distribution density representative value corresponding to the i-th inspection sub-area; C avg Indicates the average dust concentration; D avg It represents the average value of distribution density; c is the weight index of dust concentration, which controls the influence of dust concentration on weight; d is the weight index of distribution density, which controls the influence of distribution density on weight; a is the weight index of the average value of dust concentration, which controls the influence of average value on weight; b is the weight index of the average value of distribution density, which controls the influence of average value on weight.

[0107] Step S63, obtaining the total number of inspection robots in the workshop, and determining the optimal number of inspection robots corresponding to each inspection sub-area according to the ratio of the inspection robots and the total number of robots.

[0108] In the above embodiment, in order to determine the optimal number of inspection robots corresponding to each inspection sub-area, the number of sub-areas corresponding to the inspection sub-area is obtained, and the average dust concentration value is determined based on the representative value of the dust concentration and the number of sub-areas, and the average distribution density value is determined based on the distribution density and the number of sub-areas. Then, the weight corresponding to each inspection sub-area is determined based on the average dust concentration value, the average distribution density value, the representative value of the dust concentration and the distribution density, and the corresponding ratio of inspection robots is determined based on the weight corresponding to each inspection sub-area. Then, the total number of inspection robots in the workshop is obtained, and the optimal number of inspection robots corresponding to each inspection sub-area is determined based on the ratio of inspection robots and the total number of robots.

[0109] As a further implementation of the workshop inspection method, the method further includes:

[0110] Step S71, during the inspection process of the inspection robot, the inspection robot obtains the current working parameters of the equipment to be inspected, and determines whether the current working parameters are within a preset range based on the current working parameters.

[0111] Step S72: if not, abnormal operation information is generated according to the current working parameters, and the abnormal operation information is sent to the inspection terminal of the inspection personnel.

[0112] Specifically, if the current working parameter is not within the preset range, abnormal operation information is generated according to the current working parameter, and the abnormal operation information is sent to the inspection terminal of the inspection personnel.

[0113] Step S73: If yes, normal operation information is generated according to the current working parameters, and the normal operation information is sent to the inspection terminal of the inspection personnel.

[0114] Specifically, if the current working parameters are within a preset range, normal operating information is generated according to the current working parameters, and the normal operating information is sent to the inspection terminal of the inspection personnel.

[0115] In the above-mentioned embodiment, during the inspection process of the inspection robot, the current working parameters of the equipment to be inspected are obtained by the inspection robot, and whether the current working parameters are within the preset range is determined based on the current working parameters. If the current working parameters are not within the preset range, abnormal operation information is generated based on the current working parameters, and the abnormal operation information is sent to the inspection terminal of the inspection personnel. If the current working parameters are within the preset range, normal operation information is generated based on the current working parameters, and the normal operation information is sent to the inspection terminal of the inspection personnel.

[0116] The embodiment of the present application also discloses a workshop inspection system based on the industrial Internet of Things.

[0117] refer to Figure 2 The workshop inspection system based on the industrial Internet of Things includes a management platform, a sensor network platform and an object platform which are connected in sequence. The management platform is configured with:

[0118] The module for determining the equipment to be inspected is used to obtain the current status of each production equipment in the workshop and determine the equipment to be inspected from the production equipment according to the current status;

[0119] An inspection sub-area determination module is used to obtain dust concentration data of the workshop and determine at least one inspection sub-area based on the dust concentration data and the equipment to be inspected;

[0120] A distribution density determination module is used to obtain, for each inspection sub-area, the sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area, and determine the distribution density according to the sub-area area and the number of devices;

[0121] An inspection parameter determination module is used to determine, for each inspection sub-area, a representative value of dust concentration in the inspection sub-area according to dust concentration data, and to determine an inspection parameter of the inspection sub-area according to the representative value of dust concentration and distribution density;

[0122] The inspection control module is used to generate inspection control instructions according to the inspection parameters to control the inspection robot to inspect at least one inspection sub-area.

[0123] The overall framework of another application scenario of the production line management system based on the industrial Internet of Things of this application is as follows Figure 3 As shown, it may include a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in sequence, forming a five-platform architecture based on the industrial Internet of Things. Among them, the service platform is composed of a service general database, multiple service sub-platforms and multiple service sub-databases; the management platform includes a module for determining equipment to be inspected, a module for determining inspection sub-areas, a module for determining distribution density, a module for determining inspection parameters and an inspection control module; the management platform can interact with the sensor network platform and the service platform; the sensor network platform can interact with the object platform.

[0124] Specifically, in another application scenario mentioned above, the production line management system based on the industrial Internet of Things includes a management platform, which is configured to: obtain the current status of each production equipment in the workshop, and determine the equipment to be inspected from the production equipment according to the current status; obtain the dust concentration data of the workshop, and determine at least one inspection sub-area based on the dust concentration data and the equipment to be inspected; for each inspection sub-area, obtain the sub-area area corresponding to the inspection sub-area and the number of equipment to be inspected in the inspection sub-area, and determine the distribution density based on the sub-area area and the number of equipment; for each inspection sub-area, determine the dust concentration representative value of the inspection sub-area based on the dust concentration data, and determine the inspection parameters of the inspection sub-area based on the dust concentration representative value and the distribution density; generate inspection control instructions based on the inspection parameters to control the inspection robot to inspect at least one inspection sub-area.

[0125] Through the interaction between the various functional platforms of the production line management system based on the industrial Internet of Things based on the above three platforms or five platforms, a complete closed-loop information operation logic is established, ensuring the orderly operation of perception information and control information and realizing intelligent equipment management.

[0126] The workshop inspection system based on industrial Internet of Things of the present invention can implement any one of the workshop inspection methods based on industrial Internet of Things, and the specific working process of the workshop inspection system based on industrial Internet of Things of the present invention can refer to the corresponding process in the above-mentioned workshop inspection method based on industrial Internet of Things.

[0127] The embodiment of the present application also discloses a computer device.

[0128] refer to Figure 4 A computer device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, any one of the above-mentioned workshop inspection methods based on industrial Internet of Things is implemented.

[0129] The embodiment of the present application also discloses a computer-readable storage medium.

[0130] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above-mentioned workshop inspection methods based on industrial Internet of Things.

[0131] Among them, computer-readable storage media can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0132] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A workshop inspection method based on industrial Internet of Things, characterized in that: Applied to an industrial Internet of Things system, the industrial Internet of Things system includes a management platform, a sensor network platform and an object platform that are sequentially connected in communication, and the method is executed by the management platform, including: Obtain the current status of each production equipment in the workshop, and determine the equipment to be inspected from the production equipment according to the current status; Acquire dust concentration data of the workshop, and determine at least one inspection sub-area according to the dust concentration data and the equipment to be inspected; For each inspection sub-area, obtaining the sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area, and determining the distribution density according to the sub-area area and the number of devices; For each inspection sub-area, determining a representative value of dust concentration of the inspection sub-area according to the dust concentration data, and determining an inspection parameter of the inspection sub-area according to the representative value of dust concentration and the distribution density; Generating an inspection control instruction according to the inspection parameter to control the inspection robot to inspect the at least one inspection sub-area; The step of determining the representative value of the dust concentration of the inspection sub-area according to the dust concentration data comprises: extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data; Obtaining a spatial model of the workshop, and determining an effective coverage space corresponding to the dust concentration monitoring point according to the spatial model; Determine the dust amount representative value corresponding to the inspection sub-area according to the dust concentration monitoring value corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and determine the corresponding coverage space range according to the effective coverage space corresponding to the dust concentration monitoring point; Determine a representative value of dust concentration in the inspection sub-area according to the representative value of dust amount and the coverage space range; The inspection parameters include the optimal number of inspection robots; the step of determining the inspection parameters of the inspection sub-area according to the representative value of dust concentration and the distribution density includes: Obtaining the number of sub-areas corresponding to the inspection sub-area, and determining the average value of dust concentration according to the representative value of dust concentration and the number of sub-areas, and determining the average value of distribution density according to the distribution density and the number of sub-areas; Determine the weight corresponding to each inspection sub-area according to the dust concentration average value, the distribution density average value, the dust concentration representative value and the distribution density, and determine the corresponding inspection robot ratio according to the weight corresponding to each inspection sub-area; Obtaining the total number of inspection robots in the workshop, and determining the optimal number of inspection robots corresponding to each inspection sub-area according to the inspection robot ratio and the total number of robots; The calculation formula of the weight is: Among them, W i represents the weight corresponding to the i-th inspection sub-area, C i represents the representative value of the dust concentration corresponding to the i-th inspection sub-area, D i represents the representative value of the distribution density corresponding to the i-th inspection sub-area, C avg Denotes the average dust concentration, D avg represents the average value of the distribution density, c is the weight index of the average value of the dust concentration, d is the weight index of the distribution density, a is the weight index of the average value of the dust concentration, and b is the weight index of the average value of the distribution density.

2. The workshop inspection method based on industrial Internet of Things according to claim 1 is characterized in that: The step of obtaining the current status of each production equipment in the workshop and determining the equipment to be inspected from the production equipment according to the current status includes: Acquire the current status of each production equipment in the workshop, wherein the current status includes working status, waiting status and shutdown status; The production equipment in the working state and the waiting state is used as equipment to be inspected.

3. The workshop inspection method based on industrial Internet of Things according to claim 1 is characterized in that: The step of determining at least one inspection sub-area according to the dust concentration data and the equipment to be inspected comprises: Acquire the location data of the equipment to be inspected, and determine the estimated value of the dust concentration at the location of the equipment to be inspected according to the location data and the dust concentration data; Acquire wind speed data in the workshop, and determine an estimated wind speed value at the location of the equipment to be inspected based on the wind speed data; A feature vector corresponding to the equipment to be inspected is constructed according to the dust concentration estimate value, the wind speed estimate value and the position data, and the workshop is divided into at least one inspection sub-area based on a preset clustering algorithm and the feature vector.

4. The workshop inspection method based on industrial Internet of Things according to claim 3 is characterized in that: The step of determining the estimated value of dust concentration at the location of the equipment to be inspected according to the location data and the dust concentration data comprises: extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data; For each device to be inspected, the coordinate data of each dust concentration monitoring point is obtained, and the monitoring distance from each dust concentration monitoring point to the device to be inspected is determined according to the position data and the coordinate data; The monitoring distance is screened according to a preset distance range to obtain a corresponding effective monitoring distance; According to the effective monitoring distance, a dust concentration monitoring value of a dust concentration monitoring point corresponding to the effective monitoring distance is obtained, and the dust concentration monitoring value of the dust concentration monitoring point corresponding to the effective monitoring distance is used as the effective dust concentration; The dust concentration estimation value at the location of the equipment to be inspected is calculated according to the effective monitoring distance and the effective dust concentration; the calculation formula of the dust concentration estimation value is: Among them, d i Indicates the effective monitoring distance, C i Indicates the effective dust concentration.

5. The workshop inspection method based on industrial Internet of Things according to claim 1 is characterized in that: Also includes: During the inspection by the inspection robot, the inspection robot obtains the current working parameters of the device to be inspected, and determines whether the current working parameters are within a preset range according to the current working parameters; If not, abnormal operation information is generated according to the current working parameters, and the abnormal operation information is sent to the inspection terminal of the inspection personnel; If so, normal operation information is generated according to the current working parameters, and the normal operation information is sent to the inspection terminal of the inspection personnel.

6. The workshop inspection system based on industrial Internet of Things is characterized by: It includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication, and the management platform is configured with: A module for determining equipment to be inspected, used to obtain the current status of each production equipment in the workshop, and determine the equipment to be inspected from the production equipment according to the current status; An inspection sub-area determination module, used to obtain dust concentration data of the workshop, and determine at least one inspection sub-area according to the dust concentration data and the equipment to be inspected; A distribution density determination module is used to obtain, for each inspection sub-area, a sub-area area corresponding to the inspection sub-area and the number of devices to be inspected in the inspection sub-area, and determine the distribution density according to the sub-area area and the number of devices; An inspection parameter determination module, configured to determine, for each inspection sub-area, a representative value of dust concentration of the inspection sub-area according to the dust concentration data, and determine an inspection parameter of the inspection sub-area according to the representative value of dust concentration and the distribution density; An inspection control module, used to generate an inspection control instruction according to the inspection parameters, so as to control the inspection robot to inspect the at least one inspection sub-area; The step of determining the representative value of the dust concentration of the inspection sub-area according to the dust concentration data comprises: extracting dust concentration monitoring values ​​corresponding to each dust concentration monitoring point from the dust concentration data according to the dust concentration data; Obtaining a spatial model of the workshop, and determining an effective coverage space corresponding to the dust concentration monitoring point according to the spatial model; Determine the dust amount representative value corresponding to the inspection sub-area according to the dust concentration monitoring value corresponding to each dust concentration monitoring point and the corresponding effective coverage space, and determine the corresponding coverage space range according to the effective coverage space corresponding to the dust concentration monitoring point; Determine a representative value of dust concentration in the inspection sub-area according to the representative value of dust amount and the coverage space range; The inspection parameters include the optimal number of inspection robots; the step of determining the inspection parameters of the inspection sub-area according to the representative value of dust concentration and the distribution density includes: Obtaining the number of sub-areas corresponding to the inspection sub-area, and determining the average value of dust concentration according to the representative value of dust concentration and the number of sub-areas, and determining the average value of distribution density according to the distribution density and the number of sub-areas; Determine the weight corresponding to each inspection sub-area according to the dust concentration average value, the distribution density average value, the dust concentration representative value and the distribution density, and determine the corresponding inspection robot ratio according to the weight corresponding to each inspection sub-area; Obtaining the total number of inspection robots in the workshop, and determining the optimal number of inspection robots corresponding to each inspection sub-area according to the inspection robot ratio and the total number of robots; The calculation formula of the weight is: Among them, W i represents the weight corresponding to the i-th inspection sub-area, C i represents the representative value of the dust concentration corresponding to the i-th inspection sub-area, D i represents the representative value of the distribution density corresponding to the i-th inspection sub-area, C avg Denotes the average dust concentration, D avg represents the average value of the distribution density, c is the weight index of the average value of the dust concentration, d is the weight index of the distribution density, a is the weight index of the average value of the dust concentration, and b is the weight index of the average value of the distribution density.

7. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 5.

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