CN111667201A - Information processing method and device for intelligent monitoring of industrial internet - Google Patents
Information processing method and device for intelligent monitoring of industrial internet Download PDFInfo
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Abstract
The invention provides an information processing method and a device for industrial internet intelligent monitoring, wherein the method is applied to an industrial internet intelligent monitoring device and comprises the following steps: acquiring first image information according to an industrial internet intelligent monitoring device; inputting the first image information into a supervised training model; obtaining output information of the supervised training model, wherein the output information comprises second image information; obtaining first staff information at a first time; obtaining face brushing information of the first worker in first time; judging whether the first worker information is consistent with the face brushing information of the first worker in the first time; if the information of the first staff is consistent with the face brushing information of the first staff in the first time, a first early warning instruction is obtained and used for reminding the first staff that the second image has a safety problem. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an information processing method and device for intelligent monitoring of an industrial internet.
Background
In industrial production enterprises, large-scale mechanical equipment, special equipment or products produced by the equipment have the characteristics of flammability, explosiveness and the like, so that potential safety hazards existing in the production process of the enterprises are large, the physical health of workers is damaged if the potential safety hazards are light, and the workers pay for lives if the safety accidents are more serious, so that the safety is the most important of the industrial production enterprises, and the safety is emphasized all the time.
However, in the process of implementing the technical solution in the embodiment of the present application, the inventor of the present application finds that the above prior art has at least the following technical problems:
the prior art has the technical problems that the intelligent degree of industrial production is low, the safety accident rate is high, and the safety management difficulty is increased.
Disclosure of Invention
The embodiment of the invention provides an information processing method and device for industrial internet intelligent monitoring, which are used for solving the technical problems that the intelligent degree of industrial production is low, the safety accident rate is high and the safety management difficulty is increased in the prior art. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are achieved.
In view of the above problems, the embodiments of the present application are provided to provide an information processing method and apparatus for industrial internet intelligent monitoring.
In a first aspect, the present invention provides an information processing method for industrial internet intelligent monitoring, where the method is applied to an industrial internet intelligent monitoring device, and the method includes: acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
Preferably, the method comprises: if the first worker information is inconsistent with the face brushing information of the first worker within the first time, obtaining a second early warning instruction, wherein the second early warning instruction is used for reminding a second worker that the second image has a safety problem and the first worker is not normally on duty; the second staff member is a superior manager of the first staff member.
Preferably, the method comprises: obtaining weather information for the first time; obtaining a first predetermined weather condition; judging whether the weather information meets the first preset weather condition or not; and if the weather information does not accord with the first preset weather condition, obtaining a third early warning instruction, wherein the third early warning instruction is used for reminding a first worker of real-time defense measures.
Preferably, before the determining whether the weather information meets the first predetermined weather condition, the method includes: obtaining weather forecast information for the first time; obtaining a weather forecast error rate; obtaining a first correction parameter according to the weather forecast error rate; and obtaining the weather information of the first time according to the weather forecast information and the first correction parameter.
Preferably, the method comprises: inputting the first image information into an efficiency training model, wherein the efficiency training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: the first image information and the working efficiency grade standard of the machine in the plant are obtained; obtaining output information of the efficiency training model, wherein the output information comprises third image information, and the third image information comprises working efficiency grade information of the machines in the plant; obtaining the information of the demand condition of downstream enterprises; and adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information.
Preferably, the adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information includes: obtaining initial demand condition information of the downstream enterprise; acquiring real-time demand condition information of the downstream enterprise; acquiring real-time demand condition information of the downstream enterprise and a first variable quantity of the initial demand condition information; and adjusting the working efficiency of the plant according to the first variable quantity and the third image information.
Preferably, the method comprises: obtaining initial production progress condition information of an upstream enterprise; obtaining real-time production progress condition information of the upstream enterprise; obtaining real-time production progress condition information of the upstream enterprise and a second variable quantity of the initial production progress condition information; and adjusting the working efficiency of the plant according to the second variable quantity and the third image information.
In a second aspect, the present invention provides an information processing apparatus for intelligent monitoring of industrial internet, the apparatus comprising:
the first obtaining unit is used for obtaining first image information according to the industrial internet intelligent monitoring device, and the first image information is plant image information in a first time;
a first input unit, configured to input the first image information into a supervised training model, where the supervised training model is obtained through training of multiple sets of training data, and each set of training data in the multiple sets includes: the first image information and a safety supervision standard;
a second obtaining unit, configured to obtain output information of the supervised training model, where the output information includes second image information, where the second image information includes image information that does not meet the safety supervision standard;
a third obtaining unit, configured to obtain first staff information at the first time;
a fourth obtaining unit, configured to obtain face brushing information of the first worker at the first time;
the first judging unit is used for judging whether the first staff information is consistent with the face brushing information of the first staff within the first time;
and the fifth obtaining unit is used for obtaining a first early warning instruction if the first worker information is consistent with the face brushing information of the first worker in the first time, and the first early warning instruction is used for reminding the first worker that the second image has a safety problem.
Preferably, the apparatus comprises:
a sixth obtaining unit, configured to obtain a second warning instruction if the first staff information is inconsistent with the face brushing information of the first staff within the first time, where the second warning instruction is used to remind a second staff that a safety problem occurs in the second image and the first staff is not normally on duty; the second staff member is a superior manager of the first staff member.
Preferably, the apparatus comprises:
a seventh obtaining unit, configured to obtain weather information of the first time;
an eighth obtaining unit configured to obtain a first predetermined weather condition;
a second judging unit, configured to judge whether the weather information meets the first predetermined weather condition;
a ninth obtaining unit, configured to obtain a third early warning instruction if the weather information does not meet the first predetermined weather condition, where the third early warning instruction is used to remind a first worker of a real-time defense measure.
Preferably, the apparatus comprises:
a tenth obtaining unit configured to obtain weather forecast information at the first time;
an eleventh obtaining unit configured to obtain a weather forecast error rate;
a twelfth obtaining unit, configured to obtain a first correction parameter according to the weather forecast error rate;
and the thirteenth obtaining unit is used for obtaining the weather information of the first time according to the weather forecast information and the first correction parameter.
Preferably, the apparatus comprises:
a second input unit, configured to input the first image information into an efficiency training model, where the efficiency training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the first image information and the working efficiency grade standard of the machine in the plant are obtained;
a fourteenth obtaining unit, configured to obtain output information of the efficiency training model, where the output information includes third image information, where the third image information includes work efficiency level information of the machine in the plant;
a fifteenth obtaining unit, configured to obtain downstream enterprise demand situation information;
and the first adjusting unit is used for adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information.
Preferably, the first adjusting unit includes:
a sixteenth obtaining unit, configured to obtain initial demand situation information of the downstream enterprise;
a seventeenth obtaining unit, configured to obtain real-time demand situation information of the downstream enterprise;
an eighteenth obtaining unit, configured to obtain real-time demand situation information of the downstream enterprise and a first variation of the initial demand situation information;
and the second adjusting unit is used for adjusting the working efficiency of the plant according to the first variable quantity and the third image information.
Preferably, the apparatus comprises:
a nineteenth obtaining unit, configured to obtain initial production progress situation information of an upstream enterprise;
a twentieth obtaining unit, configured to obtain real-time production progress status information of the upstream enterprise;
a twenty-first obtaining unit, configured to obtain real-time production progress information of the upstream enterprise and a second variation of the initial production progress information;
and the third adjusting unit is used for adjusting the working efficiency of the plant according to the second variable quantity and the third image information.
In a third aspect, the present invention provides an information processing apparatus for intelligent monitoring of industrial internet, including a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements the following steps when executing the program:
acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
the embodiment of the invention provides an information processing method and a device for industrial internet intelligent monitoring, wherein the method is applied to an industrial internet intelligent monitoring device and comprises the following steps: acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image. The method is used for solving the technical problems that the industrial production intelligence degree is low, the safety accident rate is high and the safety management difficulty is increased in the prior art. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are achieved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart of an information processing method for intelligent monitoring of an industrial Internet according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an information processing apparatus for intelligent monitoring of industrial Internet according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another information processing apparatus for intelligent monitoring of industrial internet according to an embodiment of the present invention.
Description of reference numerals: a first obtaining unit 11, a first input unit 12, a second obtaining unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a first judging unit 16, a fifth obtaining unit 17, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 306.
Detailed Description
The embodiment of the invention provides an information processing method and device for industrial internet intelligent monitoring, which are used for solving the technical problems that the intelligent degree of industrial production is low, the safety accident rate is high and the safety management difficulty is increased in the prior art.
The technical scheme provided by the invention has the following general idea: acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are achieved.
The technical solutions of the present invention are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present invention are described in detail in the technical solutions of the present application, and are not limited to the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Example one
Fig. 1 is a schematic flow chart of an information processing method for intelligent monitoring of an industrial internet according to an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides an information processing method for industrial internet intelligent monitoring, where the method is applied to an industrial internet intelligent monitoring apparatus, and the method includes:
step 110: acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time;
particularly, industry internet intelligent monitoring device installs inside the factory building, has the real time monitoring function to mechanical equipment and staff in the factory building, through industry internet intelligent monitoring device obtains first image information, first image information is the image information in the factory building of a certain time, wherein, first image information is image information in a plurality of factory buildings, contains all mechanical equipment's in the factory building running state, and wherein, mechanical equipment's in the factory building running condition includes whether mechanical equipment's normal operating condition and abnormal conditions and mechanical equipment's state accords with information such as safety supervision standard. Therefore, the technical effect of acquiring the running state of the mechanical equipment of the plant in real time is achieved.
Step 120: inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard;
step 130: obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard;
specifically, the supervised training model is a deep learning-based neural network model, and a Neural Network (NN) is a complex network system formed by widely interconnecting a large number of simple processing units (called neurons), reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. The neural network has the capabilities of large-scale parallel, distributed storage and processing, self-organization, self-adaptation and self-learning, and is particularly suitable for processing inaccurate and fuzzy information processing problems which need to consider many factors and conditions simultaneously. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (ANNs), a description of the first-order characteristics of the human brain system, are used. Briefly, it is a mathematical model. The neural network model is represented by a network topology, node characteristics, and learning rules. Specifically, in the embodiment of the present application, a large amount of image information of the operating states of all mechanical devices in a plant are divided into a plurality of sets of training data, wherein the training data may include the operating states of the mechanical devices which are operating normally or not operating normally. Each group of training data comprises the first image information and a safety supervision standard so as to form a training data set sample, then the training data set sample is used for training the constructed neural network model to obtain a supervision training model, then the first image information is used as input data and is input into the supervision training model, the supervision training model trains the first image information to obtain output information, namely second image information, and the second image information is image information which does not accord with the safety supervision standard so as to determine that the second image information does not accord with the safety supervision standard, namely image information of safety fault problems of mechanical equipment in a factory building in the first time. The technical effect of detecting the faults of the plant mechanical equipment in real time is further achieved.
Step 140: obtaining first staff information at the first time;
step 150: obtaining face brushing information of the first worker in the first time;
step 160: judging whether the first worker information and the face brushing information of the first worker are consistent in the first time;
step 170: if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
Specifically, after detecting that a plant mechanical device has a fault, a detection result needs to be timely notified to relevant workers, so that first worker information of a first time needs to be acquired through the industrial internet intelligent monitoring device, that is, worker information located in the plant or beside the mechanical device at the same time when the first image information is acquired, since other personnel such as a safety manager or a master of the plant can be present in the plant, face brushing information of the first worker in the first time needs to be simultaneously acquired, that is, face brushing information of workers who should be on duty in the first time according to a personnel position schedule is judged whether the first worker information is consistent with the face brushing information of the first worker in the first time, if the first worker information is consistent with the face brushing information of the first worker in the first time, explaining in the first time the information of the staff who should be on duty in first staff and this time is identical, namely first staff is the responsible person of mechanical equipment in the factory building in the first time, later industry internet intelligent monitoring device obtains first early warning instruction, wherein, first early warning instruction is used for reminding first staff the safety problem appears in the second image, should take measures in time to the equipment trouble in the second image information, and then play the purpose of in time telling direct responsible person with mechanical equipment trouble problem. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are further achieved.
Further, the method comprises: if the first worker information is inconsistent with the face brushing information of the first worker within the first time, obtaining a second early warning instruction, wherein the second early warning instruction is used for reminding a second worker that the second image has a safety problem and the first worker is not normally on duty; the second staff member is a superior manager of the first staff member.
Particularly, judge in the first time first staff information with whether first staff's the information of brushing the face is unanimous, if in the first time first staff information with first staff's the information of brushing the face is inconsistent, explains in the first time first staff should be in the staff information phase-mismatch of working on duty in with this time, promptly first staff is not normally on duty, has the phenomenon of looking for people and pushing away on duty or swift current post, off duty, obtains the second early warning instruction this moment, wherein, the second early warning instruction is used for reminding the second staff the safety problem has appeared in the second image, should the equipment trouble in the second image information in time takes solution. And inform that first staff normally goes out of office, wherein, the second staff is first staff's higher level managers, has further reached and has in time informed higher level person in charge's of mechanical equipment trouble problem technical effect.
Further, the method comprises: according to the second early warning instruction, obtaining attendance information of the first worker; and obtaining a punishment result of the first worker according to the attendance information of the first worker.
Specifically, according to the second early warning instruction, the second worker can obtain attendance information of the first worker in the current month, wherein the attendance information is a statistical condition that the first worker does not normally work in the current month, so that the first worker is examined, and when the current-month wage bonus is calculated, the first worker is correspondingly rewarded and punished according to an examination result. Thereby achieving the technical effect of carrying out remote assessment on the staff.
Further, the method comprises: obtaining weather information for the first time; obtaining a first predetermined weather condition; judging whether the weather information meets the first preset weather condition or not; and if the weather information does not accord with the first preset weather condition, obtaining a third early warning instruction, wherein the third early warning instruction is used for reminding a first worker of real-time defense measures.
Specifically, if the weather environment requirements of products produced in a factory building or plants growing in the factory building are harsh, the weather information of the first time is obtained through the industrial internet intelligent monitoring device, the weather information of the first time refers to the weather information of the place of the factory building in a certain time in the future, the weather information comprises the illumination, temperature, humidity, wind direction and other environment information of the place of the factory building in the first time, meanwhile, the required illumination, temperature, humidity and other environment information of the products produced in the factory building or the plants growing in the factory building are obtained, namely, the first preset weather condition is obtained, then whether the weather information accords with the first preset weather condition is judged, if the weather information does not accord with the first preset weather condition, a third early warning instruction is obtained, wherein the third early warning instruction is used for reminding a first worker to perform real-time weather prevention on the factory building according to the weather information of the first time Taking precautions. And then the technical effect of reminding the user of taking a defensive measure according to the weather condition is achieved.
Further, before the determining whether the weather information meets the first predetermined weather condition, the method includes: obtaining weather forecast information for the first time; obtaining a weather forecast error rate; obtaining a first correction parameter according to the weather forecast error rate; and obtaining the weather information of the first time according to the weather forecast information and the first correction parameter.
Specifically, the weather forecast information of the location of the factory building at the first time is acquired through the industrial internet intelligent monitoring device, a local weather forecast error rate is determined by combining past experience, a correction parameter of the weather forecast information at the first time, namely the first correction parameter, is calculated according to the weather forecast error rate, and finally the weather forecast information at the first time is corrected according to the first correction parameter, so that the weather information at the first time, namely the actual weather information of the location of the factory building at the first time is obtained, and the technical effect of obtaining the actual weather information is achieved.
Further, the method comprises: inputting the first image information into an efficiency training model, wherein the efficiency training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: the first image information and the working efficiency grade standard of the machine in the plant are obtained; obtaining output information of the efficiency training model, wherein the output information comprises third image information, and the third image information comprises working efficiency grade information of the machines in the plant; obtaining the information of the demand condition of downstream enterprises; and adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information.
Specifically, the efficiency training model is a neural network model based on deep learning, which is the same as the supervised training model, in the embodiment of the present application, a large amount of image information including the working efficiency level standard of the machine in the plant and the first image information are divided into a plurality of sets of training data to form a training data set sample, then the training data set sample is used to train the constructed neural network model to obtain the efficiency training model, then the first image information is used as input data to be input into the efficiency training model, the efficiency training model trains the first image information to obtain output information, i.e., third image information, where the third image information includes the working efficiency level information of the machine in the plant, that is, the working efficiency level information of the machine in the plant in the third image information is determined, the workshop machining product can flow into the market after being processed by a downstream enterprise, so that the requirement condition information of the downstream enterprise on the workshop machining product is required to be acquired, and the working efficiency of the workshop is adjusted according to the requirement condition information of the downstream enterprise and the third image information. For example, if the demand of the downstream enterprise for the product is not large, that is, the supply of the product machined by the plant is greater than the demand, the work efficiency of the plant is reduced; if the demand of the downstream enterprise on the product is large, namely the supply of the product machined by the factory building is short, the working efficiency of the factory building is improved so as to adapt to the market demand. And then reached according to market demand, the technical effect of adjustment work efficiency.
Further, according to the downstream enterprise demand condition information and the third image information, adjusting the work efficiency of the plant includes: obtaining initial demand condition information of the downstream enterprise; acquiring real-time demand condition information of the downstream enterprise; acquiring real-time demand condition information of the downstream enterprise and a first variable quantity of the initial demand condition information; and adjusting the working efficiency of the plant according to the first variable quantity and the third image information.
Specifically, the specific method for adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information comprises the following steps: the method comprises the steps of respectively obtaining initial demand condition information and real-time demand condition information of a downstream enterprise, namely order demand signed when the downstream enterprise cooperates for the first time, after a period of time, increasing or decreasing the order demand of the downstream enterprise, calculating a first variable quantity by comparing the real-time demand condition information and the initial demand condition information of the downstream enterprise, and finally improving or reducing the working efficiency of the plant according to the first variable quantity and the current working efficiency grade information of machinery in the plant to avoid the phenomenon of capacity reduction or excess so as to adapt to the demand of the downstream enterprise. Therefore, the technical effect of adjusting the working efficiency according to the requirements of downstream enterprises is achieved.
Further, the method comprises: obtaining initial production progress condition information of an upstream enterprise; obtaining real-time production progress condition information of the upstream enterprise; obtaining real-time production progress condition information of the upstream enterprise and a second variable quantity of the initial production progress condition information; and adjusting the working efficiency of the plant according to the second variable quantity and the third image information.
Specifically, the specific method for adjusting the work efficiency of the plant according to the initial production progress condition information of the upstream enterprise and the third image information comprises the following steps: the method comprises the steps of respectively obtaining initial production progress condition information and real-time production progress condition information of an upstream enterprise, namely, a product purchase amount signed when the upstream enterprise cooperates for the first time, after a period of time, the upstream enterprise probably has the condition that the productivity is increased or reduced, calculating a second variable quantity by comparing the real-time production progress condition information and the initial production progress condition information of the upstream enterprise, and finally, improving or reducing the working efficiency of the plant according to the second variable quantity and the current working efficiency grade information of machinery in the plant so that the working efficiency of the plant is consistent with the production progress condition of the upstream enterprise, and avoiding the phenomenon that the plant machinery stops production midway to wait for raw materials or finishes task amount on duty. Therefore, the technical effect of adjusting the working efficiency according to the production progress of upstream enterprises is achieved.
Example two
Based on the same inventive concept as the information processing method for industrial internet intelligent monitoring in the foregoing embodiment, the present invention further provides an information processing apparatus for industrial internet intelligent monitoring, the apparatus including:
the first obtaining unit 11 is configured to obtain first image information according to the industrial internet intelligent monitoring device, where the first image information is plant image information in a first time;
a first input unit 12, where the first input unit 12 is configured to input the first image information into a supervised training model, where the supervised training model is obtained through training of multiple sets of training data, and each set of training data in the multiple sets includes: the first image information and a safety supervision standard;
a second obtaining unit 13, configured to obtain output information of the supervised training model, where the output information includes second image information, where the second image information includes image information that does not meet the safety supervision standard;
a third obtaining unit 14, where the third obtaining unit 14 is configured to obtain first staff information at the first time;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain face brushing information of the first worker at the first time;
a first judging unit 16, where the first judging unit 16 is configured to judge whether the first staff information and the face brushing information of the first staff are consistent within the first time;
a fifth obtaining unit 17, where the fifth obtaining unit 17 is configured to obtain a first warning instruction if the first staff information is consistent with the face brushing information of the first staff in the first time, and the first warning instruction is used to remind the first staff that a safety problem occurs in the second image.
Preferably, the apparatus comprises:
a sixth obtaining unit, configured to obtain a second warning instruction if the first staff information is inconsistent with the face brushing information of the first staff within the first time, where the second warning instruction is used to remind a second staff that a safety problem occurs in the second image and the first staff is not normally on duty; the second staff member is a superior manager of the first staff member.
Preferably, the apparatus comprises:
a seventh obtaining unit, configured to obtain weather information of the first time;
an eighth obtaining unit configured to obtain a first predetermined weather condition;
a second judging unit, configured to judge whether the weather information meets the first predetermined weather condition;
a ninth obtaining unit, configured to obtain a third early warning instruction if the weather information does not meet the first predetermined weather condition, where the third early warning instruction is used to remind a first worker of a real-time defense measure.
Preferably, the apparatus comprises:
a tenth obtaining unit configured to obtain weather forecast information at the first time;
an eleventh obtaining unit configured to obtain a weather forecast error rate;
a twelfth obtaining unit, configured to obtain a first correction parameter according to the weather forecast error rate;
and the thirteenth obtaining unit is used for obtaining the weather information of the first time according to the weather forecast information and the first correction parameter.
Preferably, the apparatus comprises:
a second input unit, configured to input the first image information into an efficiency training model, where the efficiency training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: the first image information and the working efficiency grade standard of the machine in the plant are obtained;
a fourteenth obtaining unit, configured to obtain output information of the efficiency training model, where the output information includes third image information, where the third image information includes work efficiency level information of the machine in the plant;
a fifteenth obtaining unit, configured to obtain downstream enterprise demand situation information;
and the first adjusting unit is used for adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information.
Preferably, the first adjusting unit includes:
a sixteenth obtaining unit, configured to obtain initial demand situation information of the downstream enterprise;
a seventeenth obtaining unit, configured to obtain real-time demand situation information of the downstream enterprise;
an eighteenth obtaining unit, configured to obtain real-time demand situation information of the downstream enterprise and a first variation of the initial demand situation information;
and the second adjusting unit is used for adjusting the working efficiency of the plant according to the first variable quantity and the third image information.
Preferably, the apparatus comprises:
a nineteenth obtaining unit, configured to obtain initial production progress situation information of an upstream enterprise;
a twentieth obtaining unit, configured to obtain real-time production progress status information of the upstream enterprise;
a twenty-first obtaining unit, configured to obtain real-time production progress information of the upstream enterprise and a second variation of the initial production progress information;
and the third adjusting unit is used for adjusting the working efficiency of the plant according to the second variable quantity and the third image information.
Various changes and specific examples of the information processing method for intelligent monitoring of the industrial internet in the first embodiment of fig. 1 are also applicable to the information processing device for intelligent monitoring of the industrial internet in the present embodiment, and through the foregoing detailed description of the information processing method for intelligent monitoring of the industrial internet, those skilled in the art can clearly know the implementation method of the information processing device for intelligent monitoring of the industrial internet in the present embodiment, so for the brevity of the description, detailed descriptions are omitted here.
EXAMPLE III
Based on the same inventive concept as the information processing method for industrial internet intelligent monitoring in the foregoing embodiments, the present invention also provides an information processing apparatus for industrial internet intelligent monitoring, on which a computer program is stored, which, when executed by a processor, implements the steps of any one of the aforementioned information processing methods for industrial internet intelligent monitoring.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
Example four
Based on the same inventive concept as the information processing method for industrial internet intelligent monitoring in the foregoing embodiments, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor, implements the steps of:
acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
the embodiment of the invention provides an information processing method and a device for industrial internet intelligent monitoring, wherein the method is applied to an industrial internet intelligent monitoring device and comprises the following steps: acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time; inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard; obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard; obtaining first staff information at the first time; obtaining face brushing information of the first worker in the first time; judging whether the first worker information and the face brushing information of the first worker are consistent in the first time; if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image. The method is used for solving the technical problems that the industrial production intelligence degree is low, the safety accident rate is high and the safety management difficulty is increased in the prior art. The technical effects of real-time monitoring, high intelligent degree and great improvement of industrial production safety management level are achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An information processing method for industrial internet intelligent monitoring is applied to an industrial internet intelligent monitoring device, and comprises the following steps:
acquiring first image information according to the industrial internet intelligent monitoring device, wherein the first image information is plant image information in a first time;
inputting the first image information into a supervised training model, wherein the supervised training model is obtained by training a plurality of groups of training data, and each group of training data in the plurality of groups comprises: the first image information and a safety supervision standard;
obtaining output information of the supervised training model, wherein the output information comprises second image information, and the second image information contains image information which does not meet the safety supervision standard;
obtaining first staff information at the first time;
obtaining face brushing information of the first worker in the first time;
judging whether the first worker information and the face brushing information of the first worker are consistent in the first time;
if in the first time, the first worker information is consistent with the face brushing information of the first worker, a first early warning instruction is obtained, and the first early warning instruction is used for reminding the first worker that a safety problem occurs in the second image.
2. The method of claim 1, wherein the method comprises:
if the first worker information is inconsistent with the face brushing information of the first worker within the first time, obtaining a second early warning instruction, wherein the second early warning instruction is used for reminding a second worker that the second image has a safety problem and the first worker is not normally on duty; the second staff member is a superior manager of the first staff member.
3. The method of claim 1, wherein the method comprises:
obtaining weather information for the first time;
obtaining a first predetermined weather condition;
judging whether the weather information meets the first preset weather condition or not;
and if the weather information does not accord with the first preset weather condition, obtaining a third early warning instruction, wherein the third early warning instruction is used for reminding a first worker of real-time defense measures.
4. The method of claim 3, wherein said determining whether the weather information meets the first predetermined weather condition comprises:
obtaining weather forecast information for the first time;
obtaining a weather forecast error rate;
obtaining a first correction parameter according to the weather forecast error rate;
and obtaining the weather information of the first time according to the weather forecast information and the first correction parameter.
5. The method of claim 1, wherein the method comprises:
inputting the first image information into an efficiency training model, wherein the efficiency training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: the first image information and the working efficiency grade standard of the machine in the plant are obtained;
obtaining output information of the efficiency training model, wherein the output information comprises third image information, and the third image information comprises working efficiency grade information of the machines in the plant;
obtaining the information of the demand condition of downstream enterprises;
and adjusting the work efficiency of the plant according to the downstream enterprise demand condition information and the third image information.
6. The method of claim 5, wherein said adjusting said plant operating efficiency based on said downstream enterprise demand condition information and said third image information comprises:
obtaining initial demand condition information of the downstream enterprise;
acquiring real-time demand condition information of the downstream enterprise;
acquiring real-time demand condition information of the downstream enterprise and a first variable quantity of the initial demand condition information;
and adjusting the working efficiency of the plant according to the first variable quantity and the third image information.
7. The method of claim 5, wherein the method comprises:
obtaining initial production progress condition information of an upstream enterprise;
obtaining real-time production progress condition information of the upstream enterprise;
obtaining real-time production progress condition information of the upstream enterprise and a second variable quantity of the initial production progress condition information;
and adjusting the working efficiency of the plant according to the second variable quantity and the third image information.
8. An information processing apparatus for industrial internet intelligent monitoring, wherein the apparatus comprises:
the first obtaining unit is used for obtaining first image information according to the industrial internet intelligent monitoring device, and the first image information is plant image information in a first time;
a first input unit, configured to input the first image information into a supervised training model, where the supervised training model is obtained through training of multiple sets of training data, and each set of training data in the multiple sets includes: the first image information and a safety supervision standard;
a second obtaining unit, configured to obtain output information of the supervised training model, where the output information includes second image information, where the second image information includes image information that does not meet the safety supervision standard;
a third obtaining unit, configured to obtain first staff information at the first time;
a fourth obtaining unit, configured to obtain face brushing information of the first worker at the first time;
the first judging unit is used for judging whether the first staff information is consistent with the face brushing information of the first staff within the first time;
and the fifth obtaining unit is used for obtaining a first early warning instruction if the first worker information is consistent with the face brushing information of the first worker in the first time, and the first early warning instruction is used for reminding the first worker that the second image has a safety problem.
9. An information processing apparatus for intelligent monitoring of industrial internet, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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