CN115830739A - Monitoring and early warning method based on industrial internet - Google Patents
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Abstract
The invention relates to the technical field of monitoring and early warning, in particular to a monitoring and early warning method based on an industrial internet, which comprises the steps that an inspection task planning module sets daily inspection times of each inspection area according to the danger level of the inspection area, a central control module calculates the average maintenance times of each device, a daily inspection time adjusting parameter F is calculated according to the average maintenance times of each device to adjust the daily inspection times, and the daily inspection times of the inspection area are compensated according to the average maintenance times of each device in the inspection area; if the patrol of the corresponding patrol area is not completed within the patrol time, the early warning module sends out non-patrol early warning; if the patrolman is not the designated patrolman, the early warning module sends out unqualified patrolman early warning; the invention adjusts the patrol frequency of the patrol area in a targeted manner according to the danger level of the patrol area and the maintenance condition of equipment in the patrol area, thereby improving the efficiency of danger early warning.
Description
Technical Field
The invention relates to the technical field of monitoring and early warning, in particular to a monitoring and early warning method based on an industrial internet.
Background
In order to know and master the situation of a dangerous operation site in time, discover and eliminate accident potential, strengthen the safety management work of the work site, effectively prevent and reduce various accidents, realize purposeful and important inspection, and ensure that the inspection is thorough and non-omission.
Chinese patent application publication No.: CN113112732B discloses a mill control early warning system based on industry internet, belong to control early warning technical field, transmit the image information of intensity of a fire for the singlechip through temperature sensor and camera, singlechip control spraying equipment catches fire the department to the mill and carries out automatic alarm and the function of putting out a fire, the place of will catching a fire is transmitted to display device and is shown simultaneously, make things convenient for the staff to arrive at the place of catching a fire fast, avoid the intensity of a fire to linger, in addition, spraying equipment utilizes the inside copper dichloride of acetic acid of dissolving ball and the copper dichloride aqueous solution of acetic acid that water dissolved and produce to get rid of carbon monoxide and sulfur dioxide in the flue gas when putting out a fire, reduce the harm degree of flue gas to workman's health, when the shower hole on the shower head blocks up, under elastic film and anti-blocking plate's effect, can realize the automatic function of dredging to the shower hole.
In order to prevent and reduce various accidents, manual inspection of a dangerous area is indispensable, however, in the prior art, the inspection frequency of the inspection area is not adjusted in a targeted manner according to the dangerous level of the inspection area and the maintenance condition of equipment in the inspection area, so that the efficiency of dangerous early warning is low.
Disclosure of Invention
Therefore, the invention provides a monitoring and early warning method based on the industrial internet, which is used for overcoming the problem that the danger early warning efficiency is low because the inspection times of an inspection area are not regulated in a targeted manner according to the danger level of the inspection area and the maintenance condition of equipment in the inspection area in the prior art.
In order to achieve the above object, the present invention provides a monitoring and early warning method based on industrial internet, comprising:
s1, setting the daily inspection times of each inspection area and designating inspection personnel by an inspection task planning module according to the danger level of the inspection area;
s2, the central control module acquires the number of the equipment in any inspection area and the maintenance times of each equipment in the inspection area so as to calculate the average maintenance times of each equipment, and calculates a daily inspection time adjusting parameter F according to the average maintenance times of each equipment;
s3, the central control module adjusts the daily inspection times of the inspection area according to the comparison result of the daily inspection time adjusting parameter F and the preset daily inspection time comparison parameter, and compensates the daily inspection times of the inspection area according to the comparison result of the average maintenance times of each device in the inspection area and the preset average maintenance times;
s4, the patrol execution module calculates patrol interval time according to the compensated daily patrol times to determine patrol time, and if the patrol of the corresponding patrol area is not completed within the patrol time, the early warning module sends out early warning of no patrol;
s5, the patrol execution module collects face image information of the patrol personnel to judge whether the patrol personnel is the designated patrol personnel, and if not, the early warning module sends out unqualified patrol early warning;
and S6, monitoring the operation data of each device in real time by the monitoring module, and when the operation data of each device does not belong to the corresponding preset operation data threshold, sending out abnormal operation early warning by the early warning module.
Further, in the step S1, the risk levels of the patrol areas include a first risk level, a second risk level and a third risk level, where the risk level of the first risk level > the risk level of the second risk level > the risk level of the third risk level, and when the patrol task planning module sets the daily patrol times of each patrol area according to the risk levels of the patrol areas,
if the danger level of the patrol area is the first danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 3;
if the danger level of the patrol area is a second danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 2;
if the danger level of the patrol area is a third danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 1;
wherein N0 is a preset initial day patrol frequency, alpha 1 is a first preset day patrol frequency adjusting coefficient, alpha 2 is a second preset day patrol frequency adjusting coefficient, alpha 3 is a third preset day patrol frequency adjusting coefficient, and alpha 1 is more than 0 and less than 1 and alpha 2 is more than 2 and less than alpha 3.
Further, in the step S2, the central control module calculates an average maintenance frequency Bp of each device in any patrol area according to the following formula, and sets the average maintenance frequency Bp
Wherein Bi is the maintenance frequency of the ith equipment, and A is the number of the equipment in the inspection area;
the central control module calculates a daily inspection frequency regulating parameter F according to the following formula, and sets
Wherein A0 is the preset equipment number, and Bp0 is the preset average maintenance frequency.
Further, in the step S3, a first preset daily inspection frequency comparison parameter F1 and a second preset daily inspection frequency comparison parameter F2 are provided in the central control module, where F1 is smaller than F2, the central control module compares the daily inspection frequency adjustment parameter F with F1 and F2 respectively and adjusts the daily inspection frequency according to the comparison result, wherein,
if F is larger than or equal to F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1 xF/F2;
if F1 is not more than F and less than F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1;
if F is less than F1, the central control module adjusts the number of daily patrols to be N2, and sets N2= N1 xF/F1.
Further, in the step S3, the central control module compares the average maintenance frequency Bp of each device in the inspection area with a preset average maintenance frequency Bp0 and determines whether to compensate the daily inspection frequency of the inspection area according to the comparison result,
if Bp is less than Bp0, the central control module judges that the average maintenance frequency Bp of each device in the inspection area meets the standard, and daily inspection frequency of the inspection area does not need to be compensated;
and if Bp is larger than or equal to Bp0, the central control module judges that the average maintenance times Bp of each device in the inspection area do not meet the standard, and the daily inspection times of the inspection area need to be compensated.
Further, the central control module calculates a difference Δ Bp between Bp and Bp0 and compensates the daily inspection times of the inspection area according to Δ Bp, sets Δ Bp = Bp-Bp0, the central control module is provided with a first preset average maintenance time difference Δ Bp1 and a second preset average maintenance time difference Δ Bp2, Δ Bp1 is less than Δ Bp2, the central control module compares Δ Bp with Δ Bp1 and Δ Bp2 respectively and compensates the daily inspection times of the inspection area according to the comparison result,
if the delta Bp is more than or equal to the delta Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 3;
if Δ Bp1 is not less than Δ Bp < Δ Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 2;
if Δ Bp is less than Δ Bp1, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 1;
wherein N2 is the adjusted daily inspection frequency, beta 1 is a first preset daily inspection frequency compensation coefficient, beta 2 is a second preset daily inspection frequency compensation coefficient, beta 3 is a third preset daily inspection frequency compensation coefficient, and beta 1 is more than 1.3 and more than beta 2 and more than beta 3 and less than 1.8.
Further, in the step S4, the patrol execution module calculates patrol interval time T of each patrol area, sets T =24/N3, sets a patrol time point every interval time T with a zero point as a start time, sets a time period from T-0.5 to T +0.5 as a patrol time at any patrol time point T, and if the patrol of the patrol area is not completed within the patrol time, the early warning module sends out an early warning of no patrol.
Further, in the step S5, the patrol execution module prestores face image information of a designated patrol person, the patrol execution module collects the face image information of the patrol person and calculates a similarity S between the collected face image information and the prestored face image information of the designated patrol person when performing patrol checking, the patrol execution module compares the similarity S with a preset similarity S0 and determines whether the patrol person is the designated patrol person according to the comparison result,
if S is larger than or equal to S0, the inspection execution module judges that the inspection personnel is the designated inspection personnel and meets the requirements;
if S is less than S0, the patrol execution module judges that the patrol personnel is not the appointed patrol personnel and does not meet the requirement, and the early warning module sends out unqualified patrol early warning.
Further, in the step S6, the monitoring module monitors the operation data of each device in real time, the monitoring module is preset with an operation data threshold of each operation device, the monitoring module compares the operation data of each device with the corresponding operation data threshold,
if the operation data of each device belongs to the corresponding operation data threshold value, the monitoring module judges that the device operates normally;
and if the operation data of each device does not belong to the corresponding operation data threshold value, the monitoring module judges that the device is abnormal in operation, and the early warning module sends out early warning of abnormal operation of the device.
Further, when the early warning module sends out early warning, the early warning information is sent to a manager.
Compared with the prior art, the method has the advantages that the inspection frequency of the inspection area is adjusted in a targeted manner according to the danger level of the inspection area and the maintenance condition of equipment in the inspection area, so that the danger early warning efficiency of the method is improved, and accident potential is discovered and eliminated in time.
Furthermore, the patrol task planning module selects a corresponding daily patrol frequency adjusting coefficient to set the daily patrol frequency of each patrol area according to the danger level of the patrol area, and when the danger level of the patrol area is higher, the daily patrol frequency of the patrol area is more, so that the efficiency of the method for danger early warning is further improved, and accident hidden dangers are timely discovered and eliminated through the technical scheme.
Further, the daily inspection frequency adjusting parameter F is calculated according to the number of the devices in the inspection area and the average maintenance frequency of each device, the more the number of the devices in the inspection area is, the larger the average maintenance frequency of each device in the inspection area is, the larger the potential safety hazard possibly exists, the more the daily inspection frequency of the inspection area is, and the daily inspection frequency adjusting parameter F is a characteristic parameter of the daily inspection frequency.
Further, the larger the average maintenance frequency of each device in the inspection area is, the larger the potential safety hazard is, the control module in the invention compares the average maintenance frequency Bp of each device in the inspection area with the preset average maintenance frequency Bp0 and compensates the daily inspection frequency of the inspection area according to the comparison result, and by the technical scheme, the efficiency of the method for danger early warning is further improved, and the potential accident hazard is timely discovered and eliminated.
Furthermore, the patrol execution module calculates the patrol interval time according to the compensated daily patrol times to determine the patrol time, and if the patrol of the corresponding patrol area is not completed within the patrol time, the early warning module sends out the early warning of no patrol, so that the efficiency of the method for early warning of danger is further improved, and the accident potential is timely discovered and eliminated.
Furthermore, the inspection execution module acquires face image information of the inspector to judge whether the inspector is a designated inspector or not, and if not, the early warning module sends out unqualified inspection early warning.
Furthermore, the monitoring module monitors the operation data of each device in real time, and when the operation data of each device does not belong to the corresponding preset operation data threshold, the early warning module sends out abnormal operation early warning of the device.
Drawings
Fig. 1 is a block diagram of a monitoring and early warning system based on an industrial internet according to an embodiment of the present invention;
fig. 2 is a flowchart of a monitoring and early warning method based on the industrial internet according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, a block diagram of a monitoring and early warning system based on the industrial internet according to an embodiment of the present invention is shown, and the monitoring and early warning system based on the industrial internet includes:
the inspection task planning module is used for setting the daily inspection times of each inspection area according to the danger level of the inspection area and appointing inspection personnel;
the central control module is connected with the inspection task planning module and used for calculating the average maintenance times of each device, calculating a daily inspection time adjusting parameter F according to the average maintenance times of each device, adjusting the daily inspection times of the inspection area according to the daily inspection time adjusting parameter F, and compensating the daily inspection times of the inspection area according to the average maintenance times of each device in the inspection area;
the inspection execution module is respectively connected with the inspection task planning module and the central control module and is used for collecting face image information of an inspector to judge whether the inspector is a designated inspector or not and determining inspection time;
the early warning module is respectively connected with the patrol execution module and the monitoring module, and is used for sending out a non-patrol early warning when the patrol execution module judges that the patrol of the corresponding patrol area is not completed within the patrol time, sending out an unqualified patrol early warning when the patrol execution module judges that the patrol personnel is not appointed, and sending out an equipment operation abnormity early warning when the monitoring module judges that the equipment operates abnormally;
and the monitoring module is connected with the early warning module and is used for monitoring the operation data of each device in real time.
Referring to fig. 2, a flowchart of a monitoring and early warning method based on the industrial internet according to an embodiment of the present invention is shown, where the monitoring and early warning method based on the industrial internet includes:
s1, setting the daily inspection times of each inspection area and designating inspection personnel by an inspection task planning module according to the danger level of the inspection area;
s2, the central control module acquires the number of the equipment in any inspection area and the maintenance frequency of each equipment in the inspection area so as to calculate the average maintenance frequency of each equipment, and calculates a daily inspection frequency adjustment parameter F according to the average maintenance frequency of each equipment;
s3, the central control module adjusts the daily inspection times of the inspection area according to the comparison result of the daily inspection time adjusting parameter F and the preset daily inspection time comparison parameter, and compensates the daily inspection times of the inspection area according to the comparison result of the average maintenance times of each device in the inspection area and the preset average maintenance times;
s4, the patrol execution module calculates patrol interval time according to the compensated daily patrol times to determine patrol time, and if patrol of a corresponding patrol area is not completed within the patrol time, the early warning module sends out non-patrol early warning;
s5, the patrol execution module collects face image information of the patrol personnel to judge whether the patrol personnel is the designated patrol personnel, and if not, the early warning module sends out unqualified patrol early warning;
and S6, monitoring the operation data of each device in real time by the monitoring module, and when the operation data of each device does not belong to the corresponding preset operation data threshold, sending out abnormal operation early warning by the early warning module.
The invention adjusts the inspection times of the inspection area in a targeted manner according to the danger level of the inspection area and the maintenance condition of equipment in the inspection area, improves the efficiency of the method for early warning the danger, and timely discovers and eliminates accident potential.
Specifically, in step S1, the risk levels of the patrol area include a first risk level, a second risk level, and a third risk level, where the risk level of the first risk level > the risk level of the second risk level > the risk level of the third risk level, and when the patrol task planning module sets the number of daily patrol times of each patrol area according to the risk level of the patrol area,
if the danger level of the patrol area is the first danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 3;
if the danger level of the patrol area is a second danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 2;
if the danger level of the patrol area is a third danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 1;
wherein N0 is a preset initial day patrol frequency, alpha 1 is a first preset day patrol frequency adjusting coefficient, alpha 2 is a second preset day patrol frequency adjusting coefficient, alpha 3 is a third preset day patrol frequency adjusting coefficient, and alpha 1 is more than 0 and less than 1 and alpha 2 is more than 2 and less than alpha 3.
The invention provides a preferable embodiment scheme, wherein N0 is more than or equal to 1 and less than or equal to 2, N0 is a positive integer, a first preset day patrol frequency adjusting coefficient alpha 1 is set to be 0.5, a second preset day patrol frequency adjusting coefficient alpha 2 is set to be 1.5, a third preset day patrol frequency adjusting coefficient alpha 3 is set to be 2.5, and when the calculated N1 is not a positive integer, the value of N1 is set to be the minimum positive integer which is more than N1.
The patrol task planning module selects the corresponding daily patrol frequency adjusting coefficient according to the danger level of the patrol area to set the daily patrol frequency of each patrol area, when the danger level of the patrol area is higher, the daily patrol frequency of the patrol area is more, and through the technical scheme, the efficiency of the method for danger early warning is further improved, and accident potential is timely discovered and eliminated.
Specifically, in step S2, the central control module calculates an average maintenance frequency Bp of each device in any one of the inspection areas according to the following formula, and sets the average maintenance frequency Bp
Wherein Bi is the maintenance frequency of the ith equipment, and A is the number of the equipment in the inspection area;
the central control module calculates a daily inspection frequency regulating parameter F according to the following formula, and sets
Wherein A0 is the preset equipment number, and Bp0 is the preset average maintenance frequency.
In this example, 1 < A0 < 4,2 < Bp0 < 5, preferably, A0 is set to 2 and Bp0 is set to 3.
Specifically, in the step S3, a first preset daily inspection frequency comparison parameter F1 and a second preset daily inspection frequency comparison parameter F2 are set in the central control module, where F1 is less than F2, the central control module compares the daily inspection frequency adjustment parameter F with F1 and F2 respectively and adjusts the daily inspection frequency according to the comparison result, where,
if F is larger than or equal to F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1 xF/F2;
if F1 is not more than F and less than F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1;
if F is less than F1, the central control module adjusts the number of daily patrols to be N2, and sets N2= N1 xF/F1.
In this example, 1 < F1 < 2.5 < F2 < 4 is set, F1 is preferably set to 1.8, F2 is preferably set to 3.2, and when N2 is not calculated as a positive integer, the value of N is set to a minimum positive integer greater than N2.
The daily inspection frequency adjusting parameter F is calculated according to the number of the devices in the inspection area and the average maintenance frequency of each device, the more the number of the devices in the inspection area is, the larger the average maintenance frequency of each device in the inspection area is, the larger the potential safety hazard possibly exists, the more the daily inspection frequency of the inspection area is, and the daily inspection frequency adjusting parameter F is a characteristic parameter of the daily inspection frequency.
Specifically, in the step S3, the central control module compares the average maintenance frequency Bp of each device in the inspection area with a preset average maintenance frequency Bp0 and determines whether to compensate the daily inspection frequency of the inspection area according to the comparison result,
if Bp is less than Bp0, the central control module judges that the average maintenance frequency Bp of each device in the inspection area meets the standard, and the daily inspection frequency of the inspection area does not need to be compensated;
and if Bp is larger than or equal to Bp0, the central control module judges that the average maintenance times Bp of each device in the inspection area do not meet the standard, and the daily inspection times of the inspection area need to be compensated.
Specifically, the central control module calculates a difference Δ Bp between Bp and Bp0 and compensates the daily inspection times of the inspection area according to Δ Bp, sets Δ Bp = Bp-Bp0, the central control module is provided with a first preset average maintenance time difference Δ Bp1 and a second preset average maintenance time difference Δ Bp2, Δ Bp1 is less than Δ Bp2, the central control module compares Δ Bp with Δ Bp1 and Δ Bp2 respectively and compensates the daily inspection times of the inspection area according to the comparison result,
if the delta Bp is more than or equal to the delta Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 3;
if the delta Bp1 is not less than the delta Bp < delta Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 2;
if Δ Bp is less than Δ Bp1, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 1;
wherein N2 is the adjusted daily inspection frequency, beta 1 is a first preset daily inspection frequency compensation coefficient, beta 2 is a second preset daily inspection frequency compensation coefficient, beta 3 is a third preset daily inspection frequency compensation coefficient, and beta 1 is more than 1.3 and more than beta 2 and more than beta 3 and less than 1.8.
In this example, 2 < Δ Bp1 < 4 < Δ Bp2 < 6, it is preferable to set Δ Bp1 to 3, Δ Bp2 to 5, the first preset daily inspection count compensation coefficient β 1 to 1.4, the second preset daily inspection count compensation coefficient β 2 to 1.5, the third preset daily inspection count compensation coefficient β 3 to 1.6, and when N3 is not calculated as a positive integer, the value of N3 is set to a minimum positive integer larger than N3.
The larger the average maintenance frequency of each device in the inspection area is, the larger the potential safety hazard which may exist is, the control module compares the average maintenance frequency Bp of each device in the inspection area with the preset average maintenance frequency Bp0 and compensates the daily inspection frequency of the inspection area according to the comparison result.
Specifically, in step S4, the patrol execution module calculates a patrol interval time T of each patrol area, sets T =24/N3, sets a patrol time point every interval time T with a zero point as a start time, sets a time period from T-0.5 to T +0.5 as a patrol time at any patrol time point T, and if the patrol of the patrol area is not completed within the patrol time, the warning module issues a non-patrol warning.
The patrol execution module calculates the patrol interval time according to the compensated daily patrol times to determine the patrol time, and if the patrol of the corresponding patrol area is not completed within the patrol time, the early warning module sends out the early warning of no patrol, thereby further improving the efficiency of the method for early warning of danger and timely discovering and eliminating accident potential.
Specifically, in the step S5, the patrol execution module prestores face image information of a designated patrol person, the patrol execution module collects the face image information of the patrol person when patrolling and checking a card, and calculates a similarity S between the collected face image information and the prestored face image information of the designated patrol person, the patrol execution module compares the similarity S with a preset similarity S0 and determines whether the patrol person is the designated patrol person according to the comparison result,
if S is larger than or equal to S0, the inspection execution module judges that the inspection personnel is the designated inspection personnel and meets the requirements;
if S is less than S0, the patrol execution module judges that the patrol personnel is not the appointed patrol personnel and does not meet the requirement, and the early warning module sends out unqualified patrol early warning.
In this example, 95% < S0 < 100% is set, and S0 is preferably set to 96%.
The inspection execution module acquires face image information of an inspector to judge whether the inspector is a designated inspector or not, and if not, the early warning module sends out unqualified inspection early warning.
Specifically, in step S6, the monitoring module monitors the operation data of each device in real time, the monitoring module is preset with the operation data threshold of each device, the monitoring module compares the operation data of each device with the corresponding operation data threshold,
if the operation data of each device belongs to the corresponding operation data threshold value, the monitoring module judges that the device operates normally;
and if the operation data of each device does not belong to the corresponding operation data threshold value, the monitoring module judges that the device is abnormal in operation, and the early warning module sends out early warning of abnormal operation of the device.
The monitoring module monitors the operation data of each device in real time, and when the operation data of each device does not belong to the corresponding preset operation data threshold, the early warning module sends out abnormal early warning of device operation.
Specifically, when the early warning module sends out early warning, the early warning information is sent to the manager, so that the manager can master the early warning information in time, the efficiency of the method for early warning danger is further improved, and accident potential hazards are found and eliminated in time.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention; various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A monitoring and early warning method based on industrial Internet is characterized by comprising the following steps:
s1, setting the daily inspection times of each inspection area and designating inspection personnel by an inspection task planning module according to the danger level of the inspection area;
s2, the central control module acquires the number of the equipment in any inspection area and the maintenance times of each equipment in the inspection area so as to calculate the average maintenance times of each equipment, and calculates a daily inspection time adjusting parameter F according to the average maintenance times of each equipment;
s3, the central control module adjusts the daily inspection times of the inspection area according to the comparison result of the daily inspection time adjusting parameter F and the preset daily inspection time comparison parameter, and compensates the daily inspection times of the inspection area according to the comparison result of the average maintenance times of each device in the inspection area and the preset average maintenance times;
s4, the patrol execution module calculates patrol interval time according to the compensated daily patrol times to determine patrol time, and if the patrol of the corresponding patrol area is not completed within the patrol time, the early warning module sends out early warning of no patrol;
s5, the patrol execution module collects face image information of the patrol personnel to judge whether the patrol personnel is the designated patrol personnel, and if not, the early warning module sends out unqualified patrol early warning;
and S6, monitoring the operation data of each device in real time by the monitoring module, and when the operation data of each device does not belong to the corresponding preset operation data threshold, sending out abnormal operation early warning by the early warning module.
2. The industrial internet-based monitoring and early-warning method according to claim 1, wherein in the step S1, the risk levels of the patrol areas include a first risk level, a second risk level and a third risk level, wherein the risk level of the first risk level > the risk level of the second risk level > the risk level of the third risk level, and when the patrol task planning module sets the daily patrol times of each patrol area according to the risk levels of the patrol areas,
if the danger level of the patrol area is the first danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 3;
if the danger level of the patrol area is a second danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 2;
if the danger level of the patrol area is a third danger level, the central control module sets the daily patrol frequency to be N1, and sets N1= N0 × α 1;
wherein N0 is a preset initial day patrol frequency, alpha 1 is a first preset day patrol frequency adjusting coefficient, alpha 2 is a second preset day patrol frequency adjusting coefficient, alpha 3 is a third preset day patrol frequency adjusting coefficient, and alpha 1 is more than 0 and less than 1 and alpha 2 is more than 2 and less than alpha 3.
3. The industrial internet-based monitoring and early-warning method according to claim 2, wherein in the step S2, the central control module calculates the average maintenance times Bp of each device in any patrol area according to the following formula, and sets the average maintenance times Bp
Wherein Bi is the maintenance frequency of the ith equipment, and A is the number of the equipment in the inspection area;
the central control module calculates a daily inspection frequency adjusting parameter F according to the following formula, and sets
Wherein A0 is the preset equipment number, and Bp0 is the preset average maintenance frequency.
4. The monitoring and early-warning method based on the industrial internet as claimed in claim 3, wherein in the step S3, the central control module is provided with a first preset daily inspection frequency comparison parameter F1 and a second preset daily inspection frequency comparison parameter F2, wherein F1 is less than F2, the central control module compares the daily inspection frequency adjustment parameter F with F1 and F2 respectively and adjusts the daily inspection frequency according to the comparison result, wherein,
if F is larger than or equal to F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1 xF/F2;
if F1 is not more than F and less than F2, the central control module adjusts the daily inspection frequency to be N2, and sets N2= N1;
if F is less than F1, the central control module adjusts the number of daily patrols to be N2, and sets N2= N1 xF/F1.
5. The monitoring and early-warning method based on the industrial internet as claimed in claim 3, wherein in the step S3, the central control module compares the average maintenance times Bp of each device in the inspection area with the preset average maintenance times Bp0 and determines whether to compensate the daily inspection times of the inspection area according to the comparison result,
if Bp is less than Bp0, the central control module judges that the average maintenance frequency Bp of each device in the inspection area meets the standard, and the daily inspection frequency of the inspection area does not need to be compensated;
and if Bp is larger than or equal to Bp0, the central control module judges that the average maintenance times Bp of each device in the inspection area do not meet the standard, and the daily inspection times of the inspection area need to be compensated.
6. The monitoring and early-warning method based on the industrial internet as claimed in claim 3, wherein the central control module calculates a difference Δ Bp between Bp and Bp0 and compensates the daily inspection times of the inspection area according to Δ Bp, sets Δ Bp = Bp-Bp0, is provided with a first preset average maintenance time difference Δ Bp1 and a second preset average maintenance time difference Δ Bp2, Δ Bp1 is less than Δ Bp2, compares Δ Bp with Δ Bp1 and Δ Bp2 respectively and compensates the daily inspection times of the inspection area according to the comparison result,
if the delta Bp is more than or equal to the delta Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 3;
if Δ Bp1 is not less than Δ Bp < Δ Bp2, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 2;
if Δ Bp is less than Δ Bp1, the central control module compensates the daily patrol frequency of the patrol area to N3, and sets N3= N2 × β 1;
wherein N2 is the adjusted daily inspection frequency, beta 1 is a first preset daily inspection frequency compensation coefficient, beta 2 is a second preset daily inspection frequency compensation coefficient, beta 3 is a third preset daily inspection frequency compensation coefficient, and beta 1 is more than 1.3 and more than beta 2 and more than beta 3 and less than 1.8.
7. The monitoring and early-warning method based on the industrial internet as claimed in claim 6, wherein in the step S4, the patrol execution module calculates patrol interval time T of each patrol area, sets T =24/N3, sets a patrol time point every interval time T with zero as a starting time, sets a time period from T-0.5 to T +0.5 as a patrol time at any patrol time point T, and if the patrol of the patrol area is not completed within the patrol time, the early-warning module issues an early warning of no patrol.
8. The monitoring and early-warning method based on the industrial internet as claimed in claim 7, wherein in the step S5, the patrol execution module prestores face image information of a designated patrol person, when patrolling and checking a card, the patrol execution module collects the face image information of the patrol person and calculates a similarity S between the collected face image information and the prestored face image information of the designated patrol person, the patrol execution module compares the similarity S with a preset similarity S0 and judges whether the patrol person is the designated patrol person according to the comparison result,
if S is larger than or equal to S0, the inspection execution module judges that the inspection personnel is the designated inspection personnel and meets the requirements;
if S is less than S0, the patrol execution module judges that the patrol personnel is not the appointed patrol personnel and does not meet the requirement, and the early warning module sends out unqualified patrol early warning.
9. The monitoring and pre-warning method based on the industrial internet as claimed in claim 8, wherein in the step S6, the monitoring module monitors the operation data of each device in real time, the monitoring module is preset with the operation data threshold of each device, the monitoring module compares the operation data of each device with the corresponding operation data threshold,
if the operation data of each device belongs to the corresponding operation data threshold value, the monitoring module judges that the device operates normally;
and if the operation data of each device does not belong to the corresponding operation data threshold value, the monitoring module judges that the device is abnormal in operation, and the early warning module sends out early warning of abnormal operation of the device.
10. The monitoring and early-warning method based on the industrial internet as claimed in claim 1, wherein when the early-warning module sends out early warning, early-warning information is sent to a manager.
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