CN112465478A - Person on duty reminding method and system, monitoring host and readable storage medium - Google Patents
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Abstract
The invention relates to a method and a system for reminding a person on duty, a monitoring host and a readable storage medium, wherein the method comprises the steps of responding to a first instruction input by the person on duty, entering a first reminding mode, and acquiring an upper body image of the person on duty in a monitoring room; inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty, and outputting the mental state analysis result of the operator on duty; responding to the mental state analysis result to be normal, and not performing any operation; responding to the abnormal mental state analysis result, generating a first reminding instruction, and outputting the first reminding instruction to a first reminding execution mechanism arranged on an operator on duty so as to control the first reminding execution mechanism to remind the operator on duty; the technical problems that due to the reason of night duty, a person on duty in a power system monitoring room cannot timely know the fault event of the power system because of distraction or even sleeping and processes the fault event of the power system are solved.
Description
Technical Field
The invention relates to the technical field of power system monitoring, in particular to a method and a system for reminding an on-duty person in a power system monitoring room, a monitoring host and a computer readable storage medium.
Background
The electric power system is an electric energy production and consumption system which consists of links such as a power plant, a power transmission and transformation line, a power supply and distribution station, power utilization and the like. The power system has the function of converting natural primary energy into electric energy through a power generation power device, and then supplying the electric energy to each user through power transmission, power transformation and power distribution. The power system is also provided with corresponding information and control systems in each link and different levels, and the production process of the electric energy is measured, regulated, controlled, protected, communicated and scheduled so as to ensure that users obtain safe and high-quality electric energy. In order to achieve the above object, one important aspect is to monitor the real-time status of each link of the power system, so as to eliminate the fault in time when the power system fails, and recover the normal operation of the power system. Since the power system is operated continuously for 24 hours to provide the user with power continuously, the monitoring operation also needs to be performed continuously for 24 hours.
The monitoring work is generally to set up a monitoring room, a monitoring system is arranged in the monitoring room, the monitoring system is a device combining software and hardware, the monitoring system at least has the functions of acquiring and displaying real-time state information of the power system in real time and giving an alarm when the power system fails, and a person on duty in the monitoring room observes information content displayed by the monitoring system through naked eyes to achieve the purpose of monitoring. Because the monitoring work needs to be carried out continuously for 24 hours, at night, the person on duty is easy to feel tired when staying up night, and the person on duty is distracted during the duty process and even falls asleep, which greatly affects the monitoring work of the power system.
In addition, during the duty process, the duty personnel may leave the duty seat for a short time due to something, and if the power system fails during the period of leaving the duty seat, the duty personnel is not in the monitoring room at the moment, and cannot timely know the occurrence of the fault event, so that the fault event is eliminated, and serious consequences are also caused.
Therefore, a technical solution is needed to be provided to solve the technical problem that due to night duty, a power system monitoring room duty worker cannot timely acquire a power system fault event and process the power system fault event because the power system monitoring room duty worker is distracted or even falls asleep or leaves a duty seat.
Disclosure of Invention
The invention aims to provide a method and a system for reminding an operator on duty in a monitoring room of a power system, a monitoring host and a computer readable storage medium, which are used for solving the technical problems that the operator on duty in the monitoring room of the power system cannot timely acquire a fault event of the power system and process the fault event of the power system because of being distracted or even sleeping or leaving an operator on duty due to night on duty.
In order to achieve the above object, a first aspect of the present invention provides a method for reminding an attendant in a power system monitoring room, the method comprising:
responding to a first instruction input by a person on duty, and entering a first reminding mode;
under a first reminding mode, acquiring upper body images of staff in a monitoring room in real time;
inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode, and outputting the mental state analysis result of the operator on duty;
in a first reminding mode, responding to the normal state of the mental state analysis result, and not performing any operation;
in a first reminding mode, in response to the fact that the mental state analysis result is abnormal, a first reminding instruction is generated and output to a first reminding execution mechanism installed on an attendant seat, and the first reminding execution mechanism is controlled to remind the attendant.
Optionally, the training process of the neural network model is as follows:
collecting a plurality of sample images of a person on duty in various sitting postures at a position of a seat in a monitoring room;
marking the plurality of sample images according to the mental state of a person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
Optionally, the method specifically includes:
responding to a first instruction input by a person on duty, determining the number of the person on duty of the input first instruction according to the first instruction, and determining that the corresponding person on duty enters a first reminding mode according to the number of the person on duty;
under a first reminding mode, acquiring the upper half body image of the corresponding person on duty in the monitoring room in real time;
under a first reminding mode, inputting the upper half body image into a pre-trained neural network model for mental state analysis of an attendant, and outputting a mental state analysis result of the corresponding attendant;
in a first reminding mode, responding to the normal state of the mental state analysis result, and not performing any operation;
and in a first reminding mode, in response to the fact that the mental state analysis result is abnormal, generating a first reminding instruction, and outputting the first reminding instruction to a first reminding execution mechanism installed on the corresponding operator on duty to control the first reminding execution mechanism to remind the operator on duty.
Optionally, the method further comprises:
entering a second reminding mode in response to receiving a second instruction input by the attendant;
in a second reminding mode, acquiring monitoring state information of the power system in real time, and judging whether the power system fails according to the monitoring state information;
in a second reminding mode, in response to the judgment result that a fault occurs, generating a second reminding instruction, and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty to control the second reminding execution mechanism to carry out fault event reminding on the person on duty;
and under the second reminding mode, responding to the judgment result that no fault occurs, and not performing any operation.
Optionally, the method further comprises:
responding to a second instruction input by the operator on duty, determining the number of the operator on duty of the input second instruction according to the second instruction, and determining that the corresponding operator on duty enters a second reminding mode according to the number of the operator on duty;
in a second reminding mode, acquiring monitoring state information of the power system in real time, and judging whether the power system fails according to the monitoring state information;
in a second reminding mode, in response to the judgment result that a fault occurs, generating a second reminding instruction, and outputting the second reminding instruction to a second reminding execution mechanism worn by the corresponding person on duty so as to control the second reminding execution mechanism to carry out fault event reminding on the corresponding person on duty;
and under the second reminding mode, responding to the judgment result that no fault occurs, and not performing any operation.
The invention provides a person on duty reminding system for a power system monitoring room, which comprises:
the mode selection unit is used for responding to a first instruction input by a person on duty and entering a first reminding mode;
the image acquisition unit is used for acquiring the upper body image of a person on duty in the monitoring room in real time in a first reminding mode;
the mental state analysis unit is used for inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode and outputting a mental state analysis result of the operator on duty;
and the first reminding unit is used for generating a first reminding instruction in response to the fact that the mental state analysis result is abnormal in a first reminding mode, and outputting the first reminding instruction to a first reminding execution mechanism arranged on an attendant seat so as to control the first reminding execution mechanism to remind the attendant.
Optionally, the training process of the neural network model is as follows:
collecting a plurality of sample images of a person on duty in various sitting postures at a position of a seat in a monitoring room;
marking the plurality of sample images according to the mental state of a person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
Optionally, the system further comprises a fault judgment unit and a second reminding unit;
the mode selection unit is also used for responding to a second instruction input by the attendant and entering a second reminding mode;
the fault judging unit is used for acquiring monitoring state information of the power system in real time in a second reminding mode and judging whether the power system has faults or not according to the monitoring state information;
and the second reminding unit is used for responding to the judgment result of the fault judgment unit that a fault occurs, generating a second reminding instruction and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty so as to control the second reminding execution mechanism to carry out fault event reminding on the person on duty.
A third aspect of the present invention provides a monitoring host, including: the person on duty reminding system for the power monitoring room according to the second aspect; alternatively, a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the method for on-duty personnel reminder for a power monitoring room according to the first aspect.
A fourth aspect of the present invention proposes a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for on-duty person reminder for a power monitoring room according to the first aspect.
To sum up, the invention provides a method and a system for reminding an operator on duty in a monitoring room of an electric power system, a monitoring host and a computer-readable storage medium, which have at least the following beneficial effects:
the monitoring system at least has a first reminding mode, responds to a first instruction input by a person on duty, enters the first reminding mode, and acquires an upper body image of the person on duty in a monitoring room in real time; inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode, and outputting the mental state analysis result of the operator on duty; responding to the mental state analysis result to be normal, and not performing any operation; responding to the abnormal mental state analysis result, generating a first reminding instruction, and outputting the first reminding instruction to a first reminding execution mechanism arranged on an operator on duty so as to control the first reminding execution mechanism to remind the operator on duty; the mental state of the person on duty is judged by acquiring and identifying images in real time, and when the person on duty is in an abnormal state, namely a fatigue state, the mental state is reminded.
Additional features and advantages of the invention will be set forth in the description which follows.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for reminding an on-duty person in a monitoring room of an electrical power system according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for reminding an on-duty person in a monitoring room of an electric power system according to another embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a fatigue reminding system for monitoring personnel in a monitoring room of an electrical power system according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a monitoring host according to an embodiment of the present invention.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In addition, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present invention. It will be understood by those skilled in the art that the present invention may be practiced without some of these specific details. In some instances, well known means have not been described in detail so as not to obscure the present invention.
An embodiment of the present invention provides a method for reminding an attendant in a monitoring room of an electrical power system, which can be implemented based on a monitoring host, referring to fig. 1, the method at least includes the following steps S11-S15:
step S11, responding to a first instruction input by a person on duty, and entering a first reminding mode;
specifically, a plurality of on-duty seats are arranged in a power system monitoring room and are respectively used for seating on-duty personnel to perform monitoring related operations; the first instruction can be any set instruction content and is used for indicating a first reminding mode, and the first reminding mode corresponds to a scene that an attendant sits on the attendant;
the reminding modes of different operators on duty in the monitoring room may be different, when the operator on duty sits on the seat and starts to work on duty, the operator on duty needs to input a first instruction to the monitoring host through the corresponding input unit, and the specific form of the input unit is not limited;
preferably, in this embodiment, each agent is configured with a computer device, each attendant is configured with a corresponding attendant number, the computer device of each agent is configured with a corresponding computer number, the attendant operates the computer device, inputs the attendant number and selects a first mode by clicking a mouse, and the computer device generates the first instruction according to the computer number, the attendant number and the mode selection information, and sends the first instruction to the monitoring host.
Step S12, acquiring the upper body image of the person on duty in the monitoring room in real time in a first reminding mode;
specifically, in this embodiment, a plurality of image capturing devices may be arranged in the monitoring room, and the plurality of image capturing devices are respectively used for acquiring the upper half body images of the person on duty at each seat position;
step S13, in a first reminding mode, inputting the upper half body image into a pre-trained neural network model for mental state analysis of an attendant, and outputting a mental state analysis result of the attendant;
optionally, the training process of the neural network model comprises the following steps S01-S03:
s01, collecting a plurality of sample images of an operator on duty in various sitting postures at a seat position in a monitoring room;
step S02, marking the plurality of sample images according to the mental state of the person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and step S03, providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
Specifically, in the embodiment, the upper body image of the person on duty is selected as the input quantity of the neural network model to judge and recognize the mental state, and the upper body of the person on duty can accurately represent the mental state, more specifically, the principle of the neural network model is to extract human face features and body posture features in the image, recognize the human face features and the body posture features, wherein the human face features are preferably left and right eye features, judge whether the eyes are closed, normally open and squint through the left and right eye features, and judge that the mental state is abnormal if the eyes are continuously closed or squint for a certain time, for example, 10 seconds; the body posture characteristics can also accurately represent the mental state, for example, when a person on duty lies on a desk for sleeping, the face characteristics of the person cannot be detected, but at the moment, the person can be determined to lie on the desk for sleeping according to the body posture characteristics, so that the mental state is judged to be abnormal.
Based on the content of the present embodiment, other determination and identification methods can be used for reference to implement step S13 of the present embodiment.
Step S14, in the first reminding mode, in response to the result of the mental state analysis being normal, no operation is performed;
step S15, in the first reminding mode, in response to the result of the mental state analysis being abnormal, generating a first reminding instruction, and outputting the first reminding instruction to a first reminding execution mechanism installed on an attendant seat to control the first reminding execution mechanism to remind the attendant.
Specifically, in response to that the mental state analysis result is abnormal, a first reminding instruction is generated and output to a first reminding execution mechanism installed on the corresponding attendant seat according to a computer number, so that the first reminding execution mechanism is controlled to remind the attendant.
Preferably, the first reminding executing mechanism is a vibrating mechanism installed on the seat chair, and in this embodiment, the vibrating mechanism is used for reminding instead of a conventional voice reminding manner, so as to avoid interference on the work of other operators on duty.
It can be understood that the specific structural form of the vibration mechanism is not limited, as long as the vibration mechanism can receive the control instruction and achieve a certain degree of vibration effect according to the control instruction. For example in the form of a massage chair.
Referring to FIG. 2, the method further includes the following steps S21-S24:
step S21, responding to a second instruction input by the attendant, and entering a second reminding mode;
specifically, the second instruction may be any instruction content set for instructing to perform a second reminding mode, where the second reminding mode corresponds to a scene where an operator on duty leaves an operator on duty in a monitoring room, and at this time, the upper body image of the operator on duty cannot be shot;
preferably, in this embodiment, each agent is configured with a computer device, each attendant is configured with a corresponding attendant number, the computer device of each agent is configured with a corresponding computer number, the attendant operates the computer device, inputs the attendant number and selects the second mode by clicking a mouse, and the computer device generates the second instruction according to the computer number, the attendant number and the mode selection information, and sends the second instruction to the monitoring host.
Step S22, in a second reminding mode, acquiring monitoring state information of the power system in real time, and judging whether the power system fails according to the monitoring state information;
specifically, a monitoring system in a monitoring room can acquire and display monitoring state information of the power system in real time, and in practical application, the monitoring state information generally comprises fault event information, so that whether the power system has faults or not can be quickly judged according to the monitoring state information;
step S23, in a second reminding mode, in response to the judgment result that a fault occurs, generating a second reminding instruction, and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty to control the second reminding execution mechanism to carry out fault event reminding on the person on duty;
specifically, the second reminding executing mechanism is preferably a portable wearable device with a voice reminding function, such as a wireless earphone; as another example, a smart bracelet; when the fault event is reminded, the content of the fault event is played in a voice broadcasting mode;
specifically, in this embodiment, the second reminding instruction is sent to the second reminding executing mechanism worn by the corresponding person on duty according to the number of the person on duty.
And step S24, in the second reminding mode, in response to the determination result that no fault occurs, not performing any operation.
Referring to fig. 3, another embodiment of the present invention provides an attendant reminding system for a power system monitoring room, which can be used for implementing the method of the above embodiment, the system comprising:
the mode selection unit 1 is used for responding to a first instruction input by a person on duty and entering a first reminding mode;
the image acquisition unit 2 is used for acquiring the upper body image of a person on duty in the monitoring room in real time in a first reminding mode;
the mental state analysis unit 3 is used for inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode and outputting a mental state analysis result of the operator on duty;
and the first reminding unit 4 is used for generating a first reminding instruction in response to the fact that the mental state analysis result is abnormal in a first reminding mode, and outputting the first reminding instruction to a first reminding execution mechanism arranged on an attendant seat so as to control the first reminding execution mechanism to remind the attendant.
Optionally, the training process of the neural network model is as follows:
collecting a plurality of sample images of a person on duty in various sitting postures at a position of a seat in a monitoring room;
marking the plurality of sample images according to the mental state of a person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
Optionally, the system further includes a failure determination unit 5 and a second reminding unit 6;
the mode selection unit 1 is further configured to enter a second reminding mode in response to receiving a second instruction input by the attendant;
the fault judging unit 5 is configured to, in the second prompting mode, obtain monitoring state information of the power system in real time, and judge whether the power system has a fault according to the monitoring state information;
and the second reminding unit 6 is used for generating a second reminding instruction in response to the fact that the judgment result of the fault judgment unit is that a fault occurs, and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty so as to control the second reminding execution mechanism to carry out fault event reminding on the person on duty.
Moreover, if the attendant reminding system for the power monitoring room according to the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, the software functional unit may be stored in a computer-readable storage medium.
It should be noted that the system in the above embodiment corresponds to the method in the above embodiment, and therefore, relevant contents that are not described in detail in the system in the above embodiment can be obtained by referring to the contents of the method in the above embodiment, and are not described herein again.
Referring to fig. 4, another embodiment of the present invention further provides a monitoring host, including: the on-duty personnel reminding system for the power monitoring room according to the embodiment; or, a memory 10 and a processor 20, wherein the memory 10 stores therein computer readable instructions 101, and when the computer readable instructions 101 are executed by the processor 20, the processor 20 executes the steps of the attendant reminding method for a power monitoring room according to the above embodiment.
Of course, the monitoring host may also have components such as a wired or wireless network interface, a keyboard, and an input/output interface, so as to perform input/output, and the monitoring host may also include other components for implementing the functions of the device, which is not described herein again.
Illustratively, the computer program may be divided into one or more units, which are stored in the memory and executed by the processor to accomplish the present invention. The one or more units may be a series of instruction segments of the computer program capable of performing specific functions, and the instruction segments are used for describing the execution process of the computer program in the monitoring host.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor is the control center of the monitoring host, and various interfaces and lines are used to connect various parts of the whole monitoring host.
The memory may be used for storing the computer program and/or unit, and the processor may implement various functions of the monitoring host by executing or executing the computer program and/or unit stored in the memory and calling data stored in the memory. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Another embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for reminding an on-duty person for a power monitoring room described in the above embodiment.
Specifically, the computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A method for reminding an on-duty person in a power system monitoring room, which is characterized by comprising the following steps:
responding to a first instruction input by a person on duty, and entering a first reminding mode;
under a first reminding mode, acquiring upper body images of staff in a monitoring room in real time;
inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode, and outputting the mental state analysis result of the operator on duty;
in a first reminding mode, responding to the normal state of the mental state analysis result, and not performing any operation;
in a first reminding mode, in response to the fact that the mental state analysis result is abnormal, a first reminding instruction is generated and output to a first reminding execution mechanism installed on an attendant seat, and the first reminding execution mechanism is controlled to remind the attendant.
2. The fatigue reminding method for the on-duty personnel in the power system monitoring room as claimed in claim 1, wherein the training process of the neural network model is as follows:
collecting a plurality of sample images of a person on duty in various sitting postures at a position of a seat in a monitoring room;
marking the plurality of sample images according to the mental state of a person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
3. The fatigue reminding method for the on-duty personnel in the power system monitoring room as claimed in claim 1 or 2, wherein the method specifically comprises:
responding to a first instruction input by a person on duty, determining the number of the person on duty of the input first instruction according to the first instruction, and determining that the corresponding person on duty enters a first reminding mode according to the number of the person on duty;
under a first reminding mode, acquiring the upper half body image of the corresponding person on duty in the monitoring room in real time;
under a first reminding mode, inputting the upper half body image into a pre-trained neural network model for mental state analysis of an attendant, and outputting a mental state analysis result of the corresponding attendant;
in a first reminding mode, responding to the normal state of the mental state analysis result, and not performing any operation;
and in a first reminding mode, in response to the fact that the mental state analysis result is abnormal, generating a first reminding instruction, and outputting the first reminding instruction to a first reminding execution mechanism installed on the corresponding operator on duty to control the first reminding execution mechanism to remind the operator on duty.
4. A staff alerting method for a power system monitoring room as claimed in any one of claims 1-3, characterized in that said method further comprises:
entering a second reminding mode in response to receiving a second instruction input by the attendant;
in a second reminding mode, acquiring monitoring state information of the power system in real time, and judging whether the power system fails according to the monitoring state information;
in a second reminding mode, in response to the judgment result that a fault occurs, generating a second reminding instruction, and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty to control the second reminding execution mechanism to carry out fault event reminding on the person on duty;
and under the second reminding mode, responding to the judgment result that no fault occurs, and not performing any operation.
5. The method of claim 4, further comprising:
responding to a second instruction input by the operator on duty, determining the number of the operator on duty of the input second instruction according to the second instruction, and determining that the corresponding operator on duty enters a second reminding mode according to the number of the operator on duty;
in a second reminding mode, acquiring monitoring state information of the power system in real time, and judging whether the power system fails according to the monitoring state information;
in a second reminding mode, in response to the judgment result that a fault occurs, generating a second reminding instruction, and outputting the second reminding instruction to a second reminding execution mechanism worn by the corresponding person on duty so as to control the second reminding execution mechanism to carry out fault event reminding on the corresponding person on duty;
and under the second reminding mode, responding to the judgment result that no fault occurs, and not performing any operation.
6. An attendant reminder system for a power system monitoring room, the system comprising:
the mode selection unit is used for responding to a first instruction input by a person on duty and entering a first reminding mode;
the image acquisition unit is used for acquiring the upper body image of a person on duty in the monitoring room in real time in a first reminding mode;
the mental state analysis unit is used for inputting the upper half body image into a pre-trained neural network model to analyze the mental state of an operator on duty in a first reminding mode and outputting a mental state analysis result of the operator on duty;
and the first reminding unit is used for generating a first reminding instruction in response to the fact that the mental state analysis result is abnormal in a first reminding mode, and outputting the first reminding instruction to a first reminding execution mechanism arranged on an attendant seat so as to control the first reminding execution mechanism to remind the attendant.
7. The system for reminding a person on duty of a power system monitoring room of claim 6, wherein the training process of the neural network model is as follows:
collecting a plurality of sample images of a person on duty in various sitting postures at a position of a seat in a monitoring room;
marking the plurality of sample images according to the mental state of a person on duty in the plurality of sample images; wherein the marked results of the plurality of sample images are normal or abnormal;
and providing a neural network basic model, and training the neural network basic model by using the plurality of sample images and the marks thereof to obtain the neural network model.
8. The person on duty reminding system for a power system monitoring room as claimed in claim 7, wherein the system further comprises a failure judgment unit and a second reminding unit;
the mode selection unit is also used for responding to a second instruction input by the attendant and entering a second reminding mode;
the fault judging unit is used for acquiring monitoring state information of the power system in real time in a second reminding mode and judging whether the power system has faults or not according to the monitoring state information;
and the second reminding unit is used for responding to the judgment result of the fault judgment unit that a fault occurs, generating a second reminding instruction and outputting the second reminding instruction to a second reminding execution mechanism worn by the person on duty so as to control the second reminding execution mechanism to carry out fault event reminding on the person on duty.
9. A monitoring host, comprising: an attendant alerting system for a power monitoring room as claimed in any one of claims 6 to 8; or, a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the method for on duty personnel reminder for a power monitoring room according to any one of claims 1-5.
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 for on-duty personnel alerting for a power monitoring room according to any one of claims 1-4.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114596532A (en) * | 2021-07-23 | 2022-06-07 | 平安科技（深圳）有限公司 | Behavior detection method, behavior detection device, behavior detection equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204332008U (en) * | 2015-01-15 | 2015-05-13 | 无锡北斗星通信息科技有限公司 | Boats and ships operator on duty condition detecting system |
| CN206210018U (en) * | 2016-12-02 | 2017-05-31 | 四川亚润科技有限公司 | Electric power system dispatching control alarm system for prompting |
| CN107508375A (en) * | 2016-12-05 | 2017-12-22 | 国网山东省电力公司烟台供电公司 | A kind of grid equipment tripping operation voice vibration prompting system and reminding method |
| CN108022411A (en) * | 2017-11-30 | 2018-05-11 | 西安科锐盛创新科技有限公司 | Monitoring system based on image procossing |
| CN109145789A (en) * | 2018-08-09 | 2019-01-04 | 炜呈智能电力科技（杭州）有限公司 | Power supply system safety work support method and system |
| CN109635631A (en) * | 2018-10-25 | 2019-04-16 | 安徽新浩信息科技有限公司 | A kind of fire watch room personnel recognition methods on duty based on artificial intelligence |
| CN212064217U (en) * | 2020-05-12 | 2020-12-01 | 时代云英(重庆)科技有限公司 | Security on-duty monitoring system |
-
2020
- 2020-12-21 CN CN202011516034.8A patent/CN112465478A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN204332008U (en) * | 2015-01-15 | 2015-05-13 | 无锡北斗星通信息科技有限公司 | Boats and ships operator on duty condition detecting system |
| CN206210018U (en) * | 2016-12-02 | 2017-05-31 | 四川亚润科技有限公司 | Electric power system dispatching control alarm system for prompting |
| CN107508375A (en) * | 2016-12-05 | 2017-12-22 | 国网山东省电力公司烟台供电公司 | A kind of grid equipment tripping operation voice vibration prompting system and reminding method |
| CN108022411A (en) * | 2017-11-30 | 2018-05-11 | 西安科锐盛创新科技有限公司 | Monitoring system based on image procossing |
| CN109145789A (en) * | 2018-08-09 | 2019-01-04 | 炜呈智能电力科技（杭州）有限公司 | Power supply system safety work support method and system |
| CN109635631A (en) * | 2018-10-25 | 2019-04-16 | 安徽新浩信息科技有限公司 | A kind of fire watch room personnel recognition methods on duty based on artificial intelligence |
| CN212064217U (en) * | 2020-05-12 | 2020-12-01 | 时代云英(重庆)科技有限公司 | Security on-duty monitoring system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114596532A (en) * | 2021-07-23 | 2022-06-07 | 平安科技（深圳）有限公司 | Behavior detection method, behavior detection device, behavior detection equipment and storage medium |
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