Monitoring signal processing method and device, inspection operation and maintenance equipment, storage medium and program product

Abstract

The invention discloses a monitoring signal processing method and device, routing inspection operation and maintenance equipment, a storage medium and a program product, and relates to the technical field of routing inspection operation and maintenance, and the method comprises the steps: when a routing inspection operation and maintenance worker wears an intelligent safety helmet and VR glasses at the same time for routing inspection operation and maintenance, if the intelligent safety helmet sends a first alarm signal and the VR glasses sends a second alarm signal, the routing inspection operation and maintenance worker carries out routing inspection operation and maintenance; if yes, adjusting the first alarm signal and / or the second alarm signal when it is determined or predicted that the inspection operation and maintenance personnel have alarm cognition overload on the two alarm signals in real time. In this way, the risk of alarm cognition overload existing in multiple massive alarm signals is reduced or even eliminated, and the efficiency and accuracy of inspection operation and maintenance are further guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of patrol inspection and operation and maintenance, and in particular to a method for processing monitoring signals, an apparatus for monitoring signals, patrol inspection and operation and maintenance equipment, a storage medium, and a computer program product. Background Art

[0002] Currently, in scenarios where inspection and maintenance tasks are required, such as power plants and factories, the implementation of inspection and maintenance by combining smart helmets and VR glasses has been widely used. However, in this combined inspection and maintenance implementation, although the smart helmets and VR glasses can each send alarm signals, which seems to increase the efficiency and accuracy of inspection and maintenance, it actually ignores the demanding requirements that the multiple and massive alarm signals place on the inspection and maintenance personnel's tolerance and information processing capabilities, which are almost impossible to achieve manually. In other words, the existing technology only considers the mechanical stacking of hardware and the addition of alarm signals, but does not consider the alarm cognitive overload that inspection and maintenance personnel may experience from the multiple and massive alarm signals, and the subsequent significant decline in the efficiency and accuracy of inspection and maintenance when inspection and maintenance personnel are overloaded with alarm cognitive overload.

[0003] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of this application is to provide a monitoring signal processing method, a monitoring signal device, inspection and operation and maintenance equipment, a storage medium and a computer program product, aiming to solve the technical problem that there is a risk of alarm recognition overload caused by multiple massive alarm signals, which further leads to reduced efficiency and accuracy of inspection and operation and maintenance.

[0005] To achieve the above objectives, the present application proposes a monitoring signal processing method, which includes: Obtaining a first alarm signal emitted by a smart helmet and a second alarm signal emitted by VR glasses, wherein an inspection and maintenance personnel simultaneously wears the smart helmet and the VR glasses for inspection and maintenance; When it is determined or predicted in real time that the inspection and maintenance personnel have an alarm cognitive overload for the first alarm signal and the second alarm signal, the first alarm signal and / or the second alarm signal are adjusted.

[0006] In one embodiment, the step of determining or predicting in real time that the inspection and operation maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal includes: Collecting attention distraction indicators of the inspection and operation maintenance personnel; Based on the attention distraction index, it is determined or predicted in real time that the inspection and maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal.

[0007] In one embodiment, the step of adjusting the first alarm signal includes: Adjusting the optical signal in the first alarm signal to a wavelength and light intensity corresponding to the current alarm level; and / or, The sound signal in the first alarm signal is adjusted to the sound source direction corresponding to the current alarm type.

[0008] In one embodiment, the step of adjusting the second alarm signal includes: compressing the amount of information on the display interface of the VR glasses in the second alarm signal; and / or, Projecting the key alarm parameters in the second alarm signal to the fovea area of ​​the retina, and projecting the auxiliary alarm parameters in the second alarm signal to the peripheral visual field area of ​​the retina; In one embodiment, the step of adjusting the first alarm signal and / or the second alarm signal further includes: An attenuation operation of the alarm information carried in the first alarm signal and / or the second alarm signal is performed, and / or a delayed push operation of non-critical information is performed.

[0009] In one embodiment, the method further comprises: When it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload in response to the first alarm signal and the second alarm signal, the complexity of the current operation scenario is analyzed in real time, and the historical operation scenario complexity of the inspection and operation maintenance personnel in historical inspection and operation maintenance tasks is obtained; When it is determined that the inspection and operation personnel is not adapted to the current operation scenario based on the complexity of the current operation scenario and the complexity of the historical operation scenarios, the current inspection and operation tasks of the inspection and operation personnel are offloaded to other inspection and operation personnel who are adapted to the current operation scenario and are closest to the current operation scenario.

[0010] In addition, to achieve the above-mentioned purpose, the present application also proposes a monitoring signal processing device, the monitoring signal processing device comprising: an acquisition module, configured to acquire a first alarm signal emitted by the smart helmet and a second alarm signal emitted by the VR glasses, wherein the inspection and maintenance personnel wear the smart helmet and the VR glasses simultaneously for inspection and maintenance; The adjustment module is used to adjust the first alarm signal and / or the second alarm signal when it is determined or predicted in real time that the inspection and maintenance personnel have alarm cognitive overload for the first alarm signal and the second alarm signal.

[0011] In addition, to achieve the above-mentioned purpose, the present application also proposes a patrol and operation and maintenance device, which includes: a smart safety helmet, VR glasses, a memory, a processor, and a computer program stored on the memory and runnable on the processor, and the computer program is configured to implement the steps of the monitoring signal processing method as described above.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the monitoring signal processing method described above are implemented.

[0013] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the monitoring signal processing method as described above.

[0014] One or more technical solutions proposed in this application have at least the following technical effects: In this application, when an inspection and maintenance personnel is simultaneously wearing a smart helmet and VR glasses while conducting inspections and maintenance, if the smart helmet issues a first alarm signal and the VR glasses issue a second alarm signal, the first alarm signal and / or the second alarm signal are adjusted upon real-time determination or prediction that the inspection and maintenance personnel are experiencing an alarm cognitive overload due to these two alarm signals. This reduces or even eliminates the risk of alarm cognitive overload due to multiple and massive alarm signals, further ensuring the efficiency and accuracy of inspection and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A flowchart of the first embodiment of the method for processing monitoring signals of the present application is provided; Figure 2 An application diagram provided for Example 1 of the method for processing monitoring signals of this application; Figure 3 A flowchart of the second embodiment of the method for processing monitoring signals of the present application is provided; Figure 4This is a schematic diagram of the module structure of the monitoring signal processing device according to an embodiment of the present application; Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the monitoring signal processing method in the embodiment of the present application.

[0018] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0020] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0021] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device or inspection and maintenance equipment capable of performing the above functions. The following uses inspection and maintenance equipment as an example to illustrate this embodiment and the following embodiments.

[0022] Based on this, the embodiment of the present application provides a method for processing a monitoring signal, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the monitoring signal processing method of the present application.

[0023] In this embodiment, the monitoring signal processing method includes steps S10 to S20: Step S10: obtaining a first alarm signal emitted by the smart helmet and a second alarm signal emitted by the VR glasses, wherein the inspection and maintenance personnel wear both the smart helmet and the VR glasses for inspection and maintenance; Step S20: When it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload for the first alarm signal and the second alarm signal, the first alarm signal and / or the second alarm signal are adjusted.

[0024] In this embodiment, the proposed detection signal processing method can be applied to scenarios such as power stations and factories where there are inspection and maintenance tasks and where smart helmets and VR glasses need to be combined for inspection and maintenance.

[0025] In one embodiment, referring to Figure 2 The inspection and maintenance equipment consists of a smart helmet 1 and VR glasses 2. Various smart hardware and sensors can be installed on the smart helmet ( Figure 2(not shown), the accessories that can be installed on the smart helmet include but are not limited to lighting, indicator lights, cameras, batteries, SIM cards, TF cards, headphones, microphones, PCB boards and their supporting software and hardware, etc., and the functions that can be realized include but are not limited to environmental monitoring, three-dimensional positioning, height detection, voiceprint detection, life monitoring, electronic fences, various alarm management, hat removal alarm, fall alarm, audio and video calls, etc. In this embodiment, there is no limit to the accessories that can be installed on the smart helmet and the functions that can be realized. Among them, various smart hardware and sensors can also be installed on VR glasses ( Figure 2 (not shown), which is similar to the smart helmet and will not be described here.

[0026] In one embodiment, when inspection and maintenance personnel wear inspection and maintenance equipment while performing inspection and maintenance tasks, a first alarm signal can be issued by a smart helmet and a second alarm signal can be issued by VR glasses. The smart helmet and VR glasses can each independently implement intelligent recognition and issue their own alarm signals based on their respective software and hardware, or they can work together to implement intelligent recognition and issue their own alarm signals. In this embodiment, the methods for implementing the first alarm signal issued by the smart helmet and the second alarm signal issued by the VR glasses are not limited. For example, AI video intelligent recognition services can be implemented on the smart helmet: using the smart helmet's real-time video monitoring to proactively identify illegal work behaviors, abnormal worker conditions (e.g., not wearing a helmet, working at height without a safety rope, electric shock), fire alarms, and other AI intelligent services, and promptly issue a first alarm signal. Another example is that AI video intelligent recognition services can be implemented on VR glasses: using the VR glasses' real-time video monitoring and the smart helmet's environmental monitoring function to identify hazards, generate a comprehensive judgment result, and promptly issue a second alarm signal.

[0027] The smart helmet and VR glasses can respectively issue a first warning signal and a second warning signal based on their respective hardware devices. In this embodiment, the implementation method of issuing the first warning signal and the second warning signal is not limited, for example, it can be based on various human-perceptible warning implementation methods such as sound, light, force, electricity, and smell.

[0028] When inspection and maintenance personnel wear inspection and maintenance equipment to perform inspection and maintenance tasks, they may receive the first alarm signal from the smart helmet and the second alarm signal from the VR glasses at the same time when an emergency alarm occurs. This causes the inspection and maintenance personnel to receive multiple and massive alarm signals in a short period of time, causing them to be overloaded with alarm cognition. In other words, when an emergency alarm occurs, for smart helmets and VR glasses, giving multiple and massive alarm signals is in line with the original intention of the functional design. However, at this time, the inspection and maintenance personnel will be overloaded with thoughts and cognitive saturation due to the flood of information, and their attention will be distracted, making them unable to handle emergency alarm events. In serious cases, accidents may occur due to the difficulty in handling emergency alarm events in a timely manner. This poses a huge safety hazard when facing emergency alarm events that need to be handled quickly in a short period of time.

[0029] In one embodiment, based on relevant physiological signals and / or alarm signals of the inspection and maintenance personnel collected by the smart helmet and / or VR glasses, it is possible to determine or predict in real time whether the inspection and maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal.

[0030] When determining in real time whether there is an alarm cognitive overload, it can be determined based on preset judgment rules, wherein the preset judgment rules can be whether the relevant physiological signals meet and conform to the typical physiological signals of typical cognitive overload, and / or whether the number of alarms and the alarm frequency of the first alarm signal and the second alarm signal are too large, etc.

[0031] When predicting whether there is alarm cognitive overload, it can be determined based on a pre-trained prediction model, wherein a prediction model is trained based on relevant historical physiological signals and / or historical alarm signals of historical inspection and maintenance personnel in historical cognitive overload events, wherein the historical alarm signals include the historical alarm number and historical alarm frequency of the first alarm signal and the second alarm signal in the historical cognitive overload events, and during the current inspection and maintenance process of the current inspection and maintenance personnel, the prediction model is used to predict whether the current inspection and maintenance personnel has alarm cognitive overload based on the relevant real-time physiological signals and / or real-time alarm signals of the current inspection and maintenance personnel.

[0032] In one embodiment, a comprehensive determination can be made as to whether the current inspection and maintenance personnel are experiencing alarm cognitive overload based on a first judgment result determined based on a preset judgment rule and a second judgment result determined based on a prediction model. For example, a first confidence weight is assigned to the preset judgment rule, and a corresponding scoring rule is set for the preset judgment rule to obtain a first score for the first judgment result; a second confidence weight is assigned to the prediction model, and a corresponding scoring rule is set for the prediction model to obtain a second score for the second judgment result; a weighted score of the first confidence weight, the first score, the second confidence weight, and the second score is compared with a preset score threshold; if the weighted score is greater than the preset score threshold, it is determined that alarm cognitive overload exists; otherwise, it is determined that alarm cognitive overload does not exist.

[0033] Furthermore, when the inspection and maintenance personnel have alarm cognitive overload for the first alarm signal and the second alarm signal, the first alarm signal and / or the second alarm signal can be adjusted to reduce or eliminate the alarm cognitive overload of the inspection and maintenance personnel, without violating the original functional design intention of the smart safety helmet and VR glasses, namely the alarm function.

[0034] In a feasible implementation, step S20 includes: Collect attention distraction indicators of inspection and maintenance personnel; Based on the attention distraction index, it is determined or predicted in real time that the inspection and operation maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal.

[0035] In this embodiment, the attention distraction indicator used to determine whether the inspection and maintenance personnel experience cognitive overload in response to the first and second alarm signals is not limited. In one embodiment, the attention distraction indicator for inspection and maintenance personnel, i.e., a physiological indicator that can be used to determine whether the inspection and maintenance personnel are experiencing cognitive overload or cognitive saturation, primarily includes: 1. EEG signals. Changes in theta waves (4-8 Hz) and beta waves (12-30 Hz) in EEG activity are closely related to cognitive load. For example, increased theta wave power in the frontal lobe is often associated with focused attention and cognitive effort, while beta wave activity may reflect information processing intensity. 2. HRV (heart rate variability). When sympathetic nervous system activity increases (e.g., cognitive overload), heart rate variability decreases. HRV time-domain and frequency-domain indicators (e.g., low-frequency / high-frequency power ratio) can quantify the autonomic nervous system's response to cognitive stress. 3. Electrodermal activity (EDA). Transient increases in skin conductivity are associated with emotional arousal and cognitive stress. For example, when performing a challenging task, skin conductance level (SCL) and skin conductance response (SCR) increase significantly. 4. Changes in pupil diameter. The degree of pupil dilation is positively correlated with cognitive effort. Eye tracking or continuous image analysis can monitor that when information processing demands exceed an individual's cognitive resources, pupil diameter will continue to expand. 5. Functional near-infrared spectroscopy. Changes in blood oxygen levels in the prefrontal cortex can reflect cognitive resource depletion. For example, blood oxygenated hemoglobin concentration may reach a plateau or decline during cognitive saturation, indicating depletion of metabolic resources in this brain region.

[0036] In addition, a comprehensive assessment can be made of whether the inspection and maintenance personnel are currently at risk of cognitive overload based on one or more of the following: task processing speed, i.e., the average time it takes for inspection and maintenance personnel to process alarm signals; task completion rate, i.e., the ratio of completed tasks to total tasks; the aforementioned degree of distraction; and emotional state, such as analyzing the emotional state of the inspection and maintenance personnel (e.g., tension, fatigue) through voice tone or facial expressions.

[0037] In another feasible implementation, step S20 includes: Adjusting the optical signal in the first alarm signal to a wavelength and light intensity corresponding to the current alarm level; and / or, The sound signal in the first alarm signal is adjusted to the sound source direction corresponding to the current alarm type.

[0038] When adjusting the first alarm signal, the optical signal within it can be adjusted to the wavelength and intensity corresponding to the current alarm severity. For example, the LED alarm light signal in a smart helmet can be replaced with a wavelength-tunable laser, using 589nm yellow light (the wavelength sensitive to the human eye) for a Level 1 alarm and 635nm red light for a Level 2 alarm. The light intensity can also be dynamically adapted to the ambient illumination during inspection and maintenance. 3D sound field technology can also be deployed to localize different alarm sound sources to specific quadrants of the virtual sound field (e.g., equipment noise alarms at 3 o'clock and personnel call alarms at 9 o'clock). This can also be combined with head tracking to achieve audio and video stabilization.

[0039] In another feasible implementation, step S20 includes: Compressing the amount of information on the display interface of the VR glasses in the second alarm signal; and / or, The key alarm parameters in the second alarm signal are projected onto the fovea area of ​​the retina, and the auxiliary alarm parameters in the second alarm signal are projected onto the peripheral visual field area of ​​the retina.

[0040] When adjusting the second alarm signal, visual field optimization based on iris tracking can be performed. The VR glasses' built-in micro-camera tracks iris constriction at a preset frequency. When the pupil diameter is detected to be smaller than the diameter corresponding to a cognitive overload sign, such as 2.8 mm, the VR glasses' AR interface information volume is automatically compressed to 40% of the baseline value. Furthermore, based on the eccentricity-decreasing characteristic of human vision, regional retinal projection display enhancement can be performed. Using micro-projection technology, key alarm parameters from the second alarm signal are projected onto the fovea (e.g., within a 5° visual angle) and auxiliary alarm information from the second alarm signal is displayed in the peripheral visual field. In this embodiment, the definition and determination methods of the key alarm parameters and auxiliary alarm parameters in the second alarm information are not limited.

[0041] In another feasible implementation, step S20 further includes: An attenuation operation of the alarm information carried in the first alarm signal and / or the second alarm signal is performed, and / or a delayed push operation of non-critical information is performed.

[0042] When adjusting the first alarm signal and / or the second alarm signal, the alarm priority classification method can also be used to achieve the attenuation of the alarm information carried in the signal. By distinguishing between early warnings and serious alarms, low-priority alarms can be limited or discarded. For example, by setting a threshold, only alarms that exceed the set threshold are retained. In addition, the attenuation of the alarm information carried in the signal can be achieved by dynamic redundancy suppression. Repeated alarms generated by the same alarm event can be merged, for example, by using a sliding time window algorithm to report only once within a specified time, or by using a hash table to record alarm features to avoid repeated processing.

[0043] In one embodiment, the smart helmet integrates a dry electrode EEG module. When the theta wave power is detected to be greater than 18μV² / Hz (an indicator of distraction), the AR interface of the VR glasses is triggered to switch to emergency mode, retaining only the display of path guidance and emergency braking controls.

[0044] When adjusting the first alarm signal and / or the second alarm signal, the push of non-critical information can also be delayed. For example, when the conductivity change rate used to characterize the sympathetic nerve excitability is monitored to be greater than 0.5μS / s (attention distraction indicator), the push of non-critical information is automatically delayed.

[0045] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 3 , the method further includes steps T10 to T20: Step T10: When it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload in response to the first alarm signal and the second alarm signal, the complexity of the current operation scenario is analyzed in real time, and the historical operation scenario complexity of the inspection and operation maintenance personnel in historical inspection and operation maintenance tasks is obtained; Step T20: When it is determined that the inspection and operation personnel are not adapted to the current operation scenario based on the complexity of the current operation scenario and the complexity of the historical operation scenarios, the current inspection and operation tasks of the inspection and operation personnel are offloaded to other inspection and operation personnel who are adapted to the current operation scenario and are closest to the current operation scenario.

[0046] When it is confirmed that the inspection and maintenance personnel are experiencing alarm cognitive overload, the complexity of the current operation scenario can be analyzed in real time based on the following formula: Ccurrent = w1×Nalarms+w2×Tcritical+w3×Euncertainty, where Nalarms is the total number of current alarm signals, including the total number of first alarm signals and second alarm signals; Tcritical is the urgency of the alarm signal (such as the proportion of alarms of each emergency category); Euncertainty is the uncertainty of the alarm signal (such as the proportion of alarms with unclear causes); and w1, w2, and w3 are weight coefficients that can be adjusted according to the actual scenario.

[0047] Furthermore, we can extract data on the complexity of operational scenarios performed by inspection and maintenance personnel in historical inspection and maintenance tasks from the historical database. The calculation formula for historical complexity is similar to that for current complexity, but is based on historical alarm signals and task completion. This historical complexity data can be used to construct a capability model for inspection and maintenance personnel and analyze their performance in scenarios of varying complexity.

[0048] Next, the complexity of the current operation scenario, Ccurrent, is compared with the complexity of the inspection and maintenance personnel's historical operation scenarios, Chistory. For example, if Ccurrent is significantly higher than Chistory or higher than the average value of Chistory, the inspection and maintenance personnel are considered unsuitable for the current scenario and need to be offloaded.

[0049] Next, available inspection and maintenance personnel are screened for those suited to the current operational scenario. For example, the replacement personnel's historical operational scenario complexity, Chistory, is examined to determine whether it is close to or higher than the current complexity, Ccurrent. Simultaneously, the replacement personnel's real-time location is obtained through the positioning system, and their distance to the current operational scenario is calculated (e.g., straight-line distance or estimated time of arrival). Furthermore, the replacement personnel whose historical operational scenario complexity is close to or higher than the current complexity, Ccurrent, and who are closest to the replacement personnel are selected.

[0050] Offload tasks from the current inspection and maintenance personnel to a selected replacement. This can be done by, for example, updating task assignment information in the task management system, notifying the replacement of new tasks via instant messaging or mobile devices, or adjusting the inspection and maintenance personnel's real-time monitoring interface to ensure transparency and continuity of task handover. Furthermore, a record of the task offload operation is saved in the system log, including the reason for offload, time, personnel involved, and task details.

[0051] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the processing method of the monitoring signal of the present application. More forms of simple transformations based on this technical concept are all within the scope of protection of the present application.

[0052] This application also provides a monitoring signal processing device, please refer to Figure 4 , the monitoring signal processing device includes: An acquisition module 10 is configured to acquire a first alarm signal emitted by the smart helmet and a second alarm signal emitted by the VR glasses, wherein the inspection and maintenance personnel wear both the smart helmet and the VR glasses for inspection and maintenance; The adjustment module 20 is used to adjust the first alarm signal and / or the second alarm signal when it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload for the first alarm signal and the second alarm signal.

[0053] In one embodiment, the adjustment module is further configured to: Collect attention distraction indicators of inspection and maintenance personnel; Based on the attention distraction index, it is determined or predicted in real time that the inspection and operation maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal.

[0054] In one embodiment, the adjustment module is further configured to: Adjusting the optical signal in the first alarm signal to a wavelength and light intensity corresponding to the current alarm level; and / or, The sound signal in the first alarm signal is adjusted to the sound source direction corresponding to the current alarm type.

[0055] In one embodiment, the adjustment module is further configured to: Compressing the amount of information on the display interface of the VR glasses in the second alarm signal; and / or, The key alarm parameters in the second alarm signal are projected onto the fovea area of ​​the retina, and the auxiliary alarm parameters in the second alarm signal are projected onto the peripheral visual field area of ​​the retina.

[0056] In one embodiment, the adjustment module is further configured to: An attenuation operation of the alarm information carried in the first alarm signal and / or the second alarm signal is performed, and / or a delayed push operation of non-critical information is performed.

[0057] In one embodiment, the monitoring signal processing device further includes an unloading module, configured to: When it is determined or predicted in real time that the inspection and operation personnel have an alarm cognitive overload in response to the first alarm signal and the second alarm signal, the complexity of the current operation scenario is analyzed in real time, and the complexity of the historical operation scenarios of the inspection and operation personnel in historical inspection and operation tasks is obtained; When it is determined that the inspection and maintenance personnel are not adapted to the current operation scenario based on the complexity of the current operation scenario and the complexity of the historical operation scenarios, the current inspection and maintenance tasks of the inspection and maintenance personnel are offloaded to other inspection and maintenance personnel who are adapted to the current operation scenario and are closest to the current operation scenario.

[0058] The monitoring signal processing device provided in this application adopts the monitoring signal processing method in the above-mentioned embodiment, which can solve the technical problem that there is a risk of alarm recognition overload due to multiple massive alarm signals, which further leads to reduced efficiency and accuracy of inspection and maintenance. Compared with the prior art, the beneficial effects of the monitoring signal processing device provided in this application are the same as the beneficial effects of the monitoring signal processing method provided in the above-mentioned embodiment, and the other technical features of the monitoring signal processing device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0059] The present application provides an inspection and operation and maintenance device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the monitoring signal processing method in the above-mentioned embodiment one.

[0060] Reference below Figure 5 , which shows a schematic diagram of the structure of inspection and operation equipment suitable for implementing the embodiments of the present application. The inspection and operation equipment in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The inspection and operation and maintenance equipment shown is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

[0061] like Figure 5As shown, the inspection and maintenance equipment may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in read-only memory 1002 or programs loaded from storage device 1003 into random access memory 1004. Random access memory 1004 also stores various programs and data required for the operation of the inspection and maintenance equipment. Processing device 1001, read-only memory 1002, and random access memory 1004 are interconnected via bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to input / output interface 1006: input device 1007, such as a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 1008, such as a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 1003, such as a magnetic tape or hard disk; and communication device 1009. The communication device 1009 can allow the inspection and operation maintenance equipment to communicate with other equipment wirelessly or wired to exchange data. Although the figure shows the inspection and operation maintenance equipment with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0062] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0063] The inspection and operation and maintenance equipment provided by this application, using the monitoring signal processing method of the above-mentioned embodiment, can solve the technical problem that the risk of alarm recognition overload exists due to multiple massive alarm signals, which further leads to reduced efficiency and accuracy of inspection and operation. Compared with the existing technology, the beneficial effects of the inspection and operation and maintenance equipment provided by this application are the same as the beneficial effects of the monitoring signal processing method provided by the above-mentioned embodiment, and the other technical features of the inspection and operation and maintenance equipment are the same as the features disclosed in the method of the previous embodiment, and are not further described here.

[0064] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0065] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0066] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, and the computer-readable program instructions are used to execute the monitoring signal processing method in the above-mentioned embodiment.

[0067] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0068] The computer-readable storage medium may be included in the inspection and operation and maintenance equipment; or it may exist independently without being assembled into the inspection and operation and maintenance equipment.

[0069] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the inspection and operation and maintenance equipment, the inspection and operation and maintenance equipment: obtains a first alarm signal emitted by a smart safety helmet and a second alarm signal emitted by VR glasses, wherein the inspection and operation and maintenance personnel wear both the smart safety helmet and VR glasses for inspection and operation and maintenance; when it is determined or predicted in real time that the inspection and operation and maintenance personnel have an alarm cognitive overload for the first alarm signal and the second alarm signal, the first alarm signal and / or the second alarm signal are adjusted.

[0070] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0071] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0072] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0073] The computer-readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned monitoring signal processing method. This computer-readable storage medium can address the technical issue of multiple, massive alarm signals presenting a risk of alarm cognitive overload, which further reduces the efficiency and accuracy of inspection and maintenance. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the monitoring signal processing method provided in the aforementioned embodiment, and are not further elaborated here.

[0074] The present application also provides a computer program product, comprising a computer program, which implements the steps of the above-mentioned monitoring signal processing method when executed by a processor.

[0075] The computer program product provided in this application can address the technical problem of the risk of alarm cognitive overload caused by numerous and numerous alarm signals, which further reduces the efficiency and accuracy of inspection and maintenance. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the monitoring signal processing method provided in the above-mentioned embodiment, and will not be elaborated here.

[0076] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for processing a monitoring signal, characterized in that: The monitoring signal processing method includes: Obtaining a first alarm signal emitted by a smart helmet and a second alarm signal emitted by VR glasses, wherein an inspection and maintenance personnel simultaneously wears the smart helmet and the VR glasses for inspection and maintenance; When it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload for the first alarm signal and the second alarm signal, the first alarm signal and / or the second alarm signal are adjusted.

2. The method for processing monitoring signals according to claim 1, wherein: The step of determining or predicting in real time that the inspection and operation maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal includes: Collecting attention distraction indicators of the inspection and operation maintenance personnel; Based on the attention distraction index, it is determined or predicted in real time that the inspection and maintenance personnel have alarm cognitive overload in response to the first alarm signal and the second alarm signal.

3. The method for processing monitoring signals according to claim 1, wherein: The step of adjusting the first alarm signal includes: Adjusting the optical signal in the first alarm signal to a wavelength and light intensity corresponding to the current alarm level; and / or, The sound signal in the first alarm signal is adjusted to the sound source direction corresponding to the current alarm type.

4. The method for processing monitoring signals according to claim 1, wherein: The step of adjusting the second alarm signal includes: compressing the amount of information on the display interface of the VR glasses in the second alarm signal; and / or, The key alarm parameters in the second alarm signal are projected to the fovea area of ​​the retina, and the auxiliary alarm parameters in the second alarm signal are projected to the peripheral visual field area of ​​the retina.

5. The method for processing monitoring signals according to claim 1, wherein: The step of adjusting the first alarm signal and / or the second alarm signal further includes: An attenuation operation of the alarm information carried in the first alarm signal and / or the second alarm signal is performed, and / or a delayed push operation of non-critical information is performed.

6. The method for processing monitoring signals according to claim 1, wherein: The method further comprises: When it is determined or predicted in real time that the inspection and operation maintenance personnel have an alarm cognitive overload in response to the first alarm signal and the second alarm signal, the complexity of the current operation scenario is analyzed in real time, and the historical operation scenario complexity of the inspection and operation maintenance personnel in historical inspection and operation maintenance tasks is obtained; When it is determined that the inspection and operation personnel is not adapted to the current operation scenario based on the complexity of the current operation scenario and the complexity of the historical operation scenarios, the current inspection and operation tasks of the inspection and operation personnel are offloaded to other inspection and operation personnel who are adapted to the current operation scenario and are closest to the current operation scenario.

7. A monitoring signal processing device, characterized in that: The monitoring signal processing device includes: an acquisition module, configured to acquire a first alarm signal emitted by the smart helmet and a second alarm signal emitted by the VR glasses, wherein the inspection and maintenance personnel wear the smart helmet and the VR glasses simultaneously for inspection and maintenance; The adjustment module is used to adjust the first alarm signal and / or the second alarm signal when it is determined or predicted in real time that the inspection and maintenance personnel have alarm cognitive overload for the first alarm signal and the second alarm signal.

8. A patrol inspection and maintenance equipment, characterized in that: The device includes: a smart helmet, VR glasses, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the monitoring signal processing method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the monitoring signal processing method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method for processing a monitoring signal according to any one of claims 1 to 6 are implemented.

Images