Early warning method, device and equipment for construction operation machinery and medium

Abstract

The invention discloses an early warning method, device and equipment for construction operation machinery and a medium, and belongs to the field of safety early warning of the construction operation machinery. The method comprises the following steps: acquiring a holographic microwave image of a construction operation machine and an operation area, a time-varying characteristic parameter variation, a vibration frequency, a vibration diffusion distance and humidity of the construction operation machine through a holographic microwave device; identifying a mechanical category and a motion trend based on the holographic microwave image; when a preset condition is met, a correction coefficient is calculated layer by layer by integrating multiple parameters; and finally generating and issuing early warning information according to the relation between the correction coefficient and the humidity. Therefore, the problems of low early warning precision, response lag and poor adaptive capacity in the prior art can be solved by implementing the early warning method and the early warning device.

Description

Technical Field

[0001] This invention relates to the field of early warning for construction machinery, and in particular to an early warning method, device, equipment and medium for construction machinery. Background Technology

[0002] In the field of construction machinery early warning, timely and accurate identification of abnormal machinery operation status and potential safety risks is crucial for ensuring the safety of personnel, the integrity of equipment, and the smooth operation of work processes at construction sites.

[0003] In existing technologies, traditional early warning methods mostly rely on single-dimensional monitoring data, such as alarms based solely on vibration sensor thresholds or simple visual recognition based on fixed image templates. These methods are applicable in static or idealized operating environments, but due to the complex and ever-changing environment of construction sites and the highly dynamic nature of machinery operation, a single data source often cannot comprehensively and accurately reflect the overall risk situation arising from the interaction between machinery and the surrounding environment.

[0004] Due to the aforementioned technical limitations, existing early warning systems generally suffer from inaccurate warnings, delayed responses, and poor adaptability in practical applications. This not only reduces the reliability and practicality of the early warning system but may also disrupt normal operations due to false alarms or delay emergency response due to missed alarms, ultimately posing a continuous threat to construction safety, operational efficiency, and equipment lifespan. Therefore, there is an urgent need for an intelligent early warning method that can integrate multi-dimensional real-time data and proactively assess risk trends to improve the initiative and reliability of construction safety management. Summary of the Invention

[0005] This invention provides an early warning method, device, equipment, and medium for construction machinery, which can solve the problem in the prior art of improving the accuracy of early warning while ensuring the timeliness of early warning response.

[0006] In a first aspect, embodiments of the present invention provide an early warning method for construction machinery, comprising: The current holographic microwave image of the construction machinery is obtained through a holographic microwave device, and the current construction area, current holographic time-varying characteristic parameter change, current vibration frequency, current vibration diffusion distance and current humidity of the construction machinery are also obtained. The type of construction machinery and its movement trend are determined based on the current holographic microwave image. If the current construction area is greater than or equal to the first preset area, and the type of the operating machinery is the first preset machinery type and the movement trend of the operating machinery is the first preset movement trend, then the correction coefficient is determined based on the change amount of the current holographic time-varying characteristic parameters, the first preset change amount, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance. Early warning information for the construction machinery is generated based on the correction coefficient, the first preset humidity, and the current humidity, and an early warning is issued based on the early warning information.

[0007] This application utilizes a holographic microwave device to acquire holographic microwave images of construction machinery and obtain multi-dimensional operational and environmental parameters. Then, based on the holographic microwave images, it accurately identifies the type and movement trend of the machinery. Next, through multi-condition filtering, it focuses on high-risk scenarios and determines correction coefficients by layering multiple parameters. Finally, based on the correction coefficients and humidity-related parameters, it generates and executes targeted early warning information. This effectively overcomes the limitations of traditional single-dimensional monitoring and achieves comprehensive perception and judgment of the operational status of construction machinery and the overall risks of the surrounding environment. Therefore, this application solves the problem in existing technologies of difficulty in improving the accuracy of early warnings while ensuring timely response.

[0008] As a preferred example of the first aspect, determining the correction coefficient based on the current change in the holographic time-varying characteristic parameter, the first preset change, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: The warning coefficient of the construction machinery is determined based on the current change in the holographic time-varying characteristic parameters and the first preset change. The warning parameters are determined based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency. The correction coefficient is determined based on the warning parameters, the current vibration diffusion distance, and the first preset vibration diffusion distance.

[0009] In this preferred example, the warning coefficient is first determined based on the change of the holographic time-varying characteristic parameter and the preset value. Then, the warning parameter is clarified by combining the coefficient with the vibration frequency related data. Finally, the correction coefficient is determined based on the relationship between the warning parameter and the vibration diffusion distance. This can fully integrate multi-dimensional mechanical operation information, avoid the bias of single-factor judgment, and make the correction coefficient more in line with the actual working conditions.

[0010] As a preferred example of the first aspect, determining the early warning coefficient of the construction machinery based on the current change in the holographic time-varying characteristic parameters and a first preset change includes: If the change in the current holographic time-varying feature parameter is less than or equal to the first preset change, then the warning coefficient is determined to be the first preset warning coefficient. If the change in the current holographic time-varying characteristic parameter is greater than the first preset change, then the warning coefficient is determined to be the second preset warning coefficient.

[0011] In this preferred example, different warning coefficients are determined according to the relationship between the change in the holographic time-varying characteristic parameters and the preset change. This classification judgment can accurately adapt to the different changing trends of mechanical characteristic parameters, avoid the judgment deviation caused by a single coefficient, make the warning coefficient more in line with the actual situation, and provide an accurate basis for the derivation of subsequent warning-related parameters.

[0012] As a preferred example of the first aspect, determining the warning parameters based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency includes: If the current vibration frequency is less than or equal to the first preset vibration frequency, then the warning parameter is determined to be the first warning parameter; wherein, the first warning parameter is determined based on the first preset warning coefficient and the first historical vibration frequency; If the current vibration frequency is greater than the first preset vibration frequency, then the warning parameter is determined to be the second warning parameter; wherein the second warning parameter is determined based on the second preset warning coefficient and the second historical vibration frequency.

[0013] In this preferred embodiment, based on the relationship between the current vibration frequency and the preset value, a warning parameter combining a corresponding preset warning coefficient and historical vibration frequencies is determined. This method adapts to different operating states of mechanical vibration frequencies and incorporates historical operating data as a reference, avoiding the one-sidedness of relying solely on current data and making the determination of the warning parameter more targeted and reliable. As a preferred example of the first aspect, determining the correction coefficient based on the warning parameter, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: If the current vibration diffusion distance is less than or equal to the first preset vibration diffusion distance, then the correction coefficient is determined to be the first correction coefficient; If the current vibration diffusion distance is greater than the first preset vibration diffusion distance, then the correction coefficient is determined to be the second correction coefficient.

[0014] In this preferred example, different correction coefficients are determined based on the relationship between the current vibration propagation distance and the preset value. This classification judgment can accurately adapt to different influence ranges of mechanical vibration propagation, avoiding adaptation deviations caused by a single coefficient, and making the correction coefficients more consistent with the actual vibration impact of the machinery, providing reliable support for the subsequent generation of accurate early warning information. As a preferred example of the first aspect, determining the type of construction machinery and the movement trend of the construction machinery based on the current holographic microwave image includes: The directional change area of ​​the construction machinery and the type of the machinery are determined based on the current holographic microwave image. If the direction change area is close to the first preset area, then the movement trend of the operating machinery is determined to be the first movement trend; If the direction change area is far from the first preset area, then the movement trend of the operating machinery is determined to be the second movement trend.

[0015] In this preferred example, the category and direction change area of ​​the construction machinery are accurately identified by holographic microwave images. Then, the movement trend is determined according to the positional relationship between the direction change area and the preset area. This avoids the limitations of a single judgment dimension and makes the determination of machinery category and movement trend more accurate and reliable.

[0016] As a preferred example of the first aspect, generating the early warning information for the construction machinery based on the correction coefficient, the first preset humidity, and the current humidity includes: The first preset humidity is corrected according to the correction coefficient to obtain the second preset humidity; If the current humidity is less than or equal to the second preset humidity, a first warning message is generated; wherein the first warning message includes a humidity warning message for the construction operation environment and a dust particulate matter warning message for the construction environment; if the current humidity is greater than the second preset humidity, a second warning message is generated; wherein the second warning message includes a transmission power warning message for the holographic microwave device.

[0017] In this preferred example, a second preset humidity is obtained by correcting the preset humidity with a correction coefficient to adapt to the actual working conditions. Then, based on the relationship between the current humidity and the preset humidity, targeted early warning information is generated, including humidity and dust particulate matter related to the construction operation environment, or early warning information related to the transmission power of the holographic microwave device. This makes the humidity judgment standard more in line with the actual working scenario, avoids the limitations of fixed thresholds, and achieves accurate differentiation and early warning of environmental risks and equipment operation risks, making the early warning information more targeted and practical.

[0018] Secondly, the present invention provides an early warning device for construction machinery, comprising: a data acquisition module, a first processing module, a second processing module, and an early warning module; The data acquisition module is used to acquire the current holographic microwave image of the construction machinery through the holographic microwave device, and to acquire the current construction area, current holographic time-varying characteristic parameter change, current vibration frequency, current vibration diffusion distance and current humidity of the construction machinery; The first processing module is used to determine the type of construction machinery and the movement trend of the construction machinery based on the current holographic microwave image; The second processing module is used to determine a correction coefficient based on the change amount of the current holographic time-varying characteristic parameters, the first preset change amount, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance if the current construction operation area is greater than or equal to the first preset area, the operation machinery category is the first preset machinery category, and the operation machinery movement trend is the first preset movement trend. The early warning module is used to generate early warning information for the construction machinery based on the correction coefficient, the first preset humidity and the current humidity, and to issue an early warning based on the early warning information.

[0019] As a preferred example of the second aspect, determining the correction coefficient based on the current change in the holographic time-varying characteristic parameters, the first preset change, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: The warning coefficient of the construction machinery is determined based on the current change in the holographic time-varying characteristic parameters and the first preset change. The warning parameters are determined based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency. The correction coefficient is determined based on the warning parameters, the current vibration diffusion distance, and the first preset vibration diffusion distance.

[0020] As a preferred example of the second aspect, determining the early warning coefficient of the construction machinery based on the current change in holographic time-varying characteristic parameters and a first preset change includes: If the change in the current holographic time-varying feature parameter is less than or equal to the first preset change, then the warning coefficient is determined to be the first preset warning coefficient. If the change in the current holographic time-varying characteristic parameter is greater than the first preset change, then the warning coefficient is determined to be the second preset warning coefficient.

[0021] As a preferred example of the second aspect, determining the warning parameters based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency includes: If the current vibration frequency is less than or equal to the first preset vibration frequency, then the warning parameter is determined to be the first warning parameter; wherein, the first warning parameter is determined based on the first preset warning coefficient and the first historical vibration frequency; If the current vibration frequency is greater than the first preset vibration frequency, then the warning parameter is determined to be the second warning parameter; wherein the second warning parameter is determined based on the second preset warning coefficient and the second historical vibration frequency.

[0022] As a preferred example of the second aspect, determining the correction coefficient based on the warning parameter, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: If the current vibration diffusion distance is less than or equal to the first preset vibration diffusion distance, then the correction coefficient is determined to be the first correction coefficient; If the current vibration diffusion distance is greater than the first preset vibration diffusion distance, then the correction coefficient is determined to be the second correction coefficient.

[0023] As a preferred example of the second aspect, determining the type of construction machinery and its movement trend based on the current holographic microwave image includes: The directional change area of ​​the construction machinery and the type of the machinery are determined based on the current holographic microwave image. If the direction change area is close to the first preset area, then the movement trend of the operating machinery is determined to be the first movement trend; If the direction change area is far from the first preset area, then the movement trend of the operating machinery is determined to be the second movement trend.

[0024] As a preferred example of the second aspect, generating the early warning information for the construction machinery based on the correction coefficient, the first preset humidity, and the current humidity includes: The first preset humidity is corrected according to the correction coefficient to obtain the second preset humidity; If the current humidity is less than or equal to the second preset humidity, a first warning message is generated; wherein the first warning message includes a humidity warning message for the construction operation environment and a dust particulate matter warning message for the construction environment; if the current humidity is greater than the second preset humidity, a second warning message is generated; wherein the second warning message includes a transmission power warning message for the holographic microwave device.

[0025] In summary, this application's embodiments utilize a holographic microwave device to acquire holographic microwave images of construction machinery and obtain multi-dimensional operational and environmental parameters. Then, based on the holographic microwave images, the type and movement trend of the machinery are accurately identified. High-risk scenarios are then focused on through multi-condition filtering, and correction coefficients are determined layer by layer by combining various parameters. Finally, targeted early warning information is generated and executed based on the correction coefficients and humidity-related parameters. This effectively overcomes the limitations of traditional single-dimensional monitoring and achieves comprehensive perception and judgment of the operational status of construction machinery and the overall risks of the surrounding environment. Therefore, this application can solve the problem in existing technologies that it is difficult to improve the accuracy of early warnings while ensuring timely response.

[0026] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the steps of the early warning method for construction machinery of the present invention.

[0027] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform steps such as the early warning method for construction machinery of the present invention. Attached Figure Description

[0028] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 This is a flowchart illustrating an embodiment of an early warning method for construction machinery provided by the present invention. Figure 2 A schematic diagram of a holographic microwave device for an embodiment of an early warning method for construction machinery provided by the present invention; Figure 3 This is a schematic diagram of the connection method of each component in a holographic microwave device, which is an embodiment of an early warning method for construction machinery provided by the present invention. Figure 4 This is a module structure diagram of one embodiment of an early warning device for construction machinery provided by the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0032] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0033] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0034] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0035] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0036] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0037] Example 1 See Figure 1 To address the problem in existing technologies of simultaneously ensuring timely early warning response and improving the accuracy of early warnings, an embodiment of the present invention provides an early warning method for construction machinery, comprising: S1. Obtain the current holographic microwave image of the construction machinery through the holographic microwave device, and obtain the current construction operation area, current holographic time-varying characteristic parameter change, current vibration frequency, current vibration diffusion distance and current humidity of the construction machinery.

[0038] Specifically, the acquisition of the current holographic microwave image of the construction machinery via a holographic microwave device, in practical applications, such as... Figure 2 As shown, the holographic microwave device includes a holographic microwave control unit 1, a holographic microwave generating unit 2, a holographic microwave transmitting unit 3, a scattering field 4, a signal receiving unit 5, and a signal conversion unit 6. The holographic microwave control unit 1 controls the holographic microwave generating unit 2 to generate microwave signals, which are emitted by the holographic microwave transmitting unit 3 and form a scattering field 4 after reaching the surface of the target object. The scattering field 4 is received by the signal receiving unit 5 and converted into a current holographic microwave image by the signal conversion unit 6.

[0039] Specifically, the connection method of each component in the holographic microwave device is as follows: Figure 3 As shown, the holographic microwave device adopts a distributed deployment strategy, that is, it is set up in the construction operation area and its surroundings according to functional requirements. It includes the holographic microwave control unit 1, the holographic microwave generating unit 2, the holographic microwave transmitting unit 3, the signal receiving unit 5, and the signal conversion unit 6. The holographic microwave control unit 1 is connected to the holographic microwave generating unit 2 and the signal conversion unit 6 respectively. The holographic microwave transmitting unit 3 is connected to the holographic microwave generating unit 2, and the signal receiving unit 5 is connected to the signal conversion unit 6.

[0040] S2. Determine the type of construction machinery and its movement trend based on the current holographic microwave image.

[0041] As a preferred embodiment, step S2, determining the type of construction machinery and its movement trend based on the current holographic microwave image, includes: The directional change area of ​​the construction machinery and the type of the machinery are determined based on the current holographic microwave image. If the direction change area is close to the first preset area, then the movement trend of the operating machinery is determined to be the first movement trend; If the direction change area is far from the first preset area, then the movement trend of the operating machinery is determined to be the second movement trend.

[0042] For example, the type of operating machinery can be a large excavator, and the direction change region is the direction change region in a holographic microwave image of the large excavator under time-series conditions.

[0043] S3. If the current construction area is greater than or equal to the first preset area and the type of the operating machinery is the first preset machinery type and the movement trend of the operating machinery is the first preset movement trend, then the correction coefficient is determined based on the change amount of the current holographic time-varying characteristic parameters, the first preset change amount, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance.

[0044] For example, when the current first preset machinery category is a large excavator, the current construction operation area is the reserved safety area determined based on the maximum turning radius of the large excavator during operation. When the construction operation machinery is a crane, the construction operation area is the reserved safety area determined based on the maximum turning radius of the crane boom. The first preset area is the area covered by extending outward by 1-5 meters based on the maximum turning radius of the large excavator during operation; preferably, it extends outward by 3 meters. For example, the first preset area is preferably 150 square meters.

[0045] As a preferred implementation, step S3, determining the correction coefficient based on the current change in holographic time-varying characteristic parameters, the first preset change, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance, includes: The warning coefficient of the construction machinery is determined based on the current change in the holographic time-varying characteristic parameters and the first preset change. The warning parameters are determined based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency. The correction coefficient is determined based on the warning parameters, the current vibration diffusion distance, and the first preset vibration diffusion distance.

[0046] In some preferred embodiments, determining the early warning coefficient of the construction machinery based on the current change in holographic time-varying characteristic parameters and a first preset change includes: If the change in the current holographic time-varying feature parameter is less than or equal to the first preset change, then the warning coefficient is determined to be the first preset warning coefficient. If the change in the current holographic time-varying characteristic parameter is greater than the first preset change, then the warning coefficient is determined to be the second preset warning coefficient.

[0047] It should be noted that the current holographic time-varying characteristic parameter change is a comprehensive quantitative indicator that integrates high-dimensional characteristic parameters of target electromagnetic scattering dynamics and physical structure vibration state, in order to sense the potential risk state of speed changes, abnormal vibrations, and structural loosening of large machinery.

[0048] For example, the preferred value of the first preset change amount is 10. The warning coefficient for large machinery is determined based on the comparison between the current change amount of the holographic time-varying feature parameter of the target object captured by holographic microwave and the first preset change amount. For example, if the current change amount of the holographic time-varying feature parameter is 8, it meets the condition that the current change amount of the holographic time-varying feature parameter is less than the first preset change amount. In this case, the warning coefficient for the construction machinery is determined to be the first preset warning coefficient. For example, if the current change amount of the holographic time-varying feature parameter is 12, it meets the condition that the current change amount of the holographic time-varying feature parameter is greater than the first preset change amount. In this case, the warning coefficient for the construction machinery is determined to be the second preset warning coefficient.

[0049] For example, the value range of the first preset warning coefficient is 0.3-0.7, and the preferred value in this embodiment is 0.4; the value range of the second preset warning coefficient is 0.5-0.9, and the preferred value in this embodiment is 0.8.

[0050] Furthermore, in some preferred embodiments, determining the warning parameters based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency includes: If the current vibration frequency is less than or equal to the first preset vibration frequency, then the warning parameter is determined to be the first warning parameter; wherein, the first warning parameter is determined based on the first preset warning coefficient and the first historical vibration frequency; If the current vibration frequency is greater than the first preset vibration frequency, then the warning parameter is determined to be the second warning parameter; wherein the second warning parameter is determined based on the second preset warning coefficient and the second historical vibration frequency.

[0051] It should be noted that the current vibration frequency is obtained by dividing the holographic microwave image signal of the construction machinery into several short time intervals, performing a short-time Fourier transform on each time interval, and obtaining the signal's spectral information at different time points. The vibration frequency can be obtained by analyzing the changes in the amplitude and phase of the spectrum over time.

[0052] For example, the preferred value of the first preset vibration frequency is 20Hz. A corresponding warning parameter is determined based on the comparison between the vibration frequency of the target object captured by the holographic microwave and the first preset vibration frequency. For instance, if the vibration frequency is 15Hz, it indicates that the vibration state of the construction machinery's surface is within a safe range during operation, and the corresponding warning parameter is determined as the first warning parameter. Conversely, if the vibration frequency is 25Hz, it indicates that the vibration state of the construction machinery's surface is exceeding a safe range, and the corresponding warning parameter is determined as the second warning parameter. The first warning parameter is the product of the current vibration frequency (when the current vibration frequency is less than the preset vibration frequency) and the first preset warning coefficient. The second warning parameter is the product of the current vibration frequency (when the current vibration frequency is greater than the preset vibration frequency) and the second preset warning coefficient.

[0053] Furthermore, in some preferred embodiments, determining the correction coefficient based on the warning parameter, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: If the current vibration diffusion distance is less than or equal to the first preset vibration diffusion distance, then the correction coefficient is determined to be the first correction coefficient; If the current vibration diffusion distance is greater than the first preset vibration diffusion distance, then the correction coefficient is determined to be the second correction coefficient.

[0054] Specifically, the current vibration propagation distance can be determined by setting up observation points around the construction machinery, installing vibration sensors at these observation points, and synchronously collecting data from each observation point. The vibration data collected by the vibration sensors is preprocessed using a filter to obtain a noise-removed vibration signal. The amplitude, phase, and frequency parameters of the vibration signal are extracted. Finally, based on the empirical formula for vibration propagation, combined with the vibration parameters of the machinery and the physical properties of the ground, the vibration propagation distance is estimated. The correction coefficient for the warning parameter in the out-of-range state is determined by the ratio of the current vibration propagation distance to the preset vibration propagation distance.

[0055] For example, the first preset vibration diffusion distance is preferably 13 meters.

[0056] S4. Generate early warning information for the construction machinery based on the correction coefficient, the first preset humidity and the current humidity, and issue an early warning based on the early warning information.

[0057] As a preferred embodiment, step S4, generating early warning information for the construction machinery based on the correction coefficient, the first preset humidity, and the current humidity, includes: The first preset humidity is corrected according to the correction coefficient to obtain the second preset humidity; If the current humidity is less than or equal to the second preset humidity, a first warning message is generated; wherein the first warning message includes a humidity warning message for the construction operation environment and a dust particulate matter warning message for the construction environment; if the current humidity is greater than the second preset humidity, a second warning message is generated; wherein the second warning message includes a transmission power warning message for the holographic microwave device.

[0058] It should be noted that the current humidity in the construction environment can be obtained through an electronic humidity sensor installed at the observation point, and the specific humidity in the construction environment can be observed directly from the electronic humidity sensor.

[0059] For example, the preferred value for the second preset humidity is 50%.

[0060] Specifically, the first warning information refers to the fact that when the humidity of the construction work environment is low, the microwave propagation speed in the air will be too fast, resulting in a decrease in the resolution of holographic microwave imaging. In a dry construction work environment, the amount of dust particles increases, affecting the scattering and absorption of microwaves, resulting in enhanced microwave signal attenuation. The corresponding first optimization strategy is to install a spray device in the construction work environment to increase the humidity of the construction work environment, reduce the amount of dust particles in the construction environment, reduce the scattering and absorption of microwaves by dust particles, and reduce the attenuation of microwave signals.

[0061] Specifically, the second warning information refers to the fact that when the humidity of the construction work environment is high, the propagation speed of microwaves in the air will be reduced, resulting in a decrease in the resolution of holographic microwave imaging. Excessive humidity will also enhance the attenuation of microwave signals, weakening the signal strength received by the signal receiving unit, thereby affecting the clarity and accuracy of the imaging. The corresponding second optimization strategy is to increase the transmission power to compensate for the impact of high humidity in the construction work environment on the propagation speed of microwave signals and the impact on microwave signal attenuation.

[0062] In summary, this application's embodiments utilize a holographic microwave device to acquire holographic microwave images of construction machinery and obtain multi-dimensional operational and environmental parameters. Then, based on the holographic microwave images, the type and movement trend of the machinery are accurately identified. High-risk scenarios are then focused on through multi-condition filtering, and correction coefficients are determined layer by layer by combining various parameters. Finally, targeted early warning information is generated and executed based on the correction coefficients and humidity-related parameters. This effectively overcomes the limitations of traditional single-dimensional monitoring and achieves comprehensive perception and judgment of the operational status of construction machinery and the overall risks of the surrounding environment. Therefore, this application can solve the problem in existing technologies that it is difficult to improve the accuracy of early warnings while ensuring timely response.

[0063] Example 2 like Figure 4 As shown, based on the above method embodiments, corresponding device embodiments are provided; An embodiment of the present invention provides an early warning device for construction machinery, comprising: a data acquisition module 41, a first processing module 42, a second processing module 43, and an early warning module 44; The data acquisition module 41 is used to acquire the current holographic microwave image of the construction machinery through the holographic microwave device, and to acquire the current construction area, current holographic time-varying characteristic parameter change, current vibration frequency, current vibration diffusion distance and current humidity of the construction machinery; The first processing module 42 is used to determine the type of construction machinery and the movement trend of the construction machinery based on the current holographic microwave image. The second processing module 43 is used to determine a correction coefficient based on the change amount of the current holographic time-varying characteristic parameters, the first preset change amount, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance if the current construction operation area is greater than or equal to the first preset area, the operation machinery category is the first preset machinery category, and the operation machinery movement trend is the first preset movement trend. The early warning module 44 is used to generate early warning information for the construction machinery based on the correction coefficient, the first preset humidity and the current humidity, and to issue an early warning based on the early warning information.

[0064] As a preferred embodiment, determining the correction coefficient based on the current change in holographic time-varying characteristic parameters, a first preset change, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: The warning coefficient of the construction machinery is determined based on the current change in the holographic time-varying characteristic parameters and the first preset change. The warning parameters are determined based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency. The correction coefficient is determined based on the warning parameters, the current vibration diffusion distance, and the first preset vibration diffusion distance.

[0065] As a preferred embodiment, determining the early warning coefficient of the construction machinery based on the current change in holographic time-varying characteristic parameters and a first preset change includes: If the change in the current holographic time-varying feature parameter is less than or equal to the first preset change, then the warning coefficient is determined to be the first preset warning coefficient. If the change in the current holographic time-varying characteristic parameter is greater than the first preset change, then the warning coefficient is determined to be the second preset warning coefficient.

[0066] In a preferred embodiment, determining the warning parameters based on the warning coefficient, the current vibration frequency, and the first preset vibration frequency includes: If the current vibration frequency is less than or equal to the first preset vibration frequency, then the warning parameter is determined to be the first warning parameter; wherein, the first warning parameter is determined based on the first preset warning coefficient and the first historical vibration frequency; If the current vibration frequency is greater than the first preset vibration frequency, then the warning parameter is determined to be the second warning parameter; wherein the second warning parameter is determined based on the second preset warning coefficient and the second historical vibration frequency.

[0067] As a preferred embodiment, determining the correction coefficient based on the warning parameter, the current vibration diffusion distance, and the first preset vibration diffusion distance includes: If the current vibration diffusion distance is less than or equal to the first preset vibration diffusion distance, then the correction coefficient is determined to be the first correction coefficient; If the current vibration diffusion distance is greater than the first preset vibration diffusion distance, then the correction coefficient is determined to be the second correction coefficient.

[0068] As a preferred embodiment, determining the type of construction machinery and its movement trend based on the current holographic microwave image includes: The directional change area of ​​the construction machinery and the type of the machinery are determined based on the current holographic microwave image. If the direction change area is close to the first preset area, then the movement trend of the operating machinery is determined to be the first movement trend; If the direction change area is far from the first preset area, then the movement trend of the operating machinery is determined to be the second movement trend.

[0069] As a preferred embodiment, generating early warning information for the construction machinery based on the correction coefficient, the first preset humidity, and the current humidity includes: The first preset humidity is corrected according to the correction coefficient to obtain the second preset humidity; If the current humidity is less than or equal to the second preset humidity, a first warning message is generated; wherein the first warning message includes a humidity warning message for the construction operation environment and a dust particulate matter warning message for the construction environment; if the current humidity is greater than the second preset humidity, a second warning message is generated; wherein the second warning message includes a transmission power warning message for the holographic microwave device.

[0070] For more detailed steps and working principles of this embodiment, please refer to the relevant description in Embodiment 1, but not limited to these descriptions.

[0071] In summary, this application's embodiments utilize a holographic microwave device to acquire holographic microwave images of construction machinery and obtain multi-dimensional operational and environmental parameters. Then, based on the holographic microwave images, the type and movement trend of the machinery are accurately identified. High-risk scenarios are then focused on through multi-condition filtering, and correction coefficients are determined layer by layer by combining various parameters. Finally, targeted early warning information is generated and executed based on the correction coefficients and humidity-related parameters. This effectively overcomes the limitations of traditional single-dimensional monitoring and achieves comprehensive perception and judgment of the operational status of construction machinery and the overall risks of the surrounding environment. Therefore, this application can solve the problem in existing technologies that it is difficult to improve the accuracy of early warnings while ensuring timely response.

[0072] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can realize the early warning method for construction machinery provided by any of the above-described method embodiments of the present invention.

[0073] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0074] Example 3 Based on the above embodiments of the early warning method for construction machinery, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the early warning method for construction machinery according to any embodiment of the present invention.

[0075] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0076] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0077] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0078] Example 4 Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the early warning method for construction machinery described in any of the above-described method embodiments of the present invention.

[0079] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0080] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for early warning of a work machine, characterized in that, The method comprises the following steps: acquiring a current holographic microwave image of the working machine by a holographic microwave device, and acquiring a current working area, a current holographic time-varying characteristic parameter variation, a current vibration frequency, a current vibration diffusion distance and a current humidity of the working machine; determining a working machine category and a working machine motion trend of the working machine according to the current holographic microwave image; if the current working area is greater than or equal to a first preset area, the working machine category is a first preset machine category, and the working machine motion trend is a first preset motion trend, then determining a correction coefficient according to the current holographic time-varying characteristic parameter variation, a first preset variation, the current vibration frequency, a first preset vibration frequency, the current vibration diffusion distance and a first preset vibration diffusion distance; generating a warning information of the working machine according to the correction coefficient, a first preset humidity and the current humidity, and performing a warning according to the warning information.

2. A pre-warning method for a work implement of a work machine according to claim 1, characterized in that, The method of determining the correction coefficient according to the current holographic time-varying characteristic parameter variation, the first preset variation, the current vibration frequency, the first preset vibration frequency, the current vibration diffusion distance and the first preset vibration diffusion distance comprises the following steps: determining a warning coefficient of the working machine according to the current holographic time-varying characteristic parameter variation and the first preset variation; determining a warning parameter according to the warning coefficient, the current vibration frequency and the first preset vibration frequency; determining the correction coefficient according to the warning parameter, the current vibration diffusion distance and the first preset vibration diffusion distance.

3. A pre-warning method for a work implement of a work machine according to claim 2, characterized in that, The method of determining the warning coefficient of the working machine according to the current holographic time-varying characteristic parameter variation and the first preset variation comprises the following steps: if the current holographic time-varying characteristic parameter variation is less than or equal to the first preset variation, then determining the warning coefficient as a first preset warning coefficient; if the current holographic time-varying characteristic parameter variation is greater than the first preset variation, then determining the warning coefficient as a second preset warning coefficient.

4. A pre-warning method for a work implement of a work machine according to claim 3, characterized in that, The method of determining the warning parameter according to the warning coefficient, the current vibration frequency and the first preset vibration frequency comprises the following steps: if the current vibration frequency is less than or equal to the first preset vibration frequency, then determining the warning parameter as a first warning parameter; wherein the first warning parameter is determined according to a first preset warning coefficient and a first historical vibration frequency; if the current vibration frequency is greater than the first preset vibration frequency, then determining the warning parameter as a second warning parameter; wherein the second warning parameter is determined according to a second preset warning coefficient and a second historical vibration frequency.

5. A pre-warning method for a work implement of a work machine according to claim 4, characterized in that, The method of determining the correction coefficient according to the warning parameter, the current vibration diffusion distance and the first preset vibration diffusion distance comprises the following steps: if the current vibration diffusion distance is less than or equal to the first preset vibration diffusion distance, then determining the correction coefficient as a first correction coefficient; if the current vibration diffusion distance is greater than the first preset vibration diffusion distance, then determining the correction coefficient as a second correction coefficient.

6. A pre-warning method for a work implement of a machine according to claim 1, characterized in that, The method of determining the working machine category and the working machine motion trend of the working machine according to the current holographic microwave image comprises the following steps: determining a direction change area of the working machine and the working machine category according to the current holographic microwave image; If the direction change region is close to the first preset region, the movement trend of the working machine is determined as a first movement trend. If the direction change region is far from the first preset region, the movement trend of the working machine is determined as a second movement trend.

7. A pre-warning method for a work implement of a machine according to any one of claims 1 to 6, characterized in that, The generating of the early warning information of the working machine according to the correction coefficient, the first preset humidity and the current humidity comprises: The first preset humidity is corrected according to the correction coefficient to obtain a second preset humidity; If the current humidity is less than or equal to the second preset humidity, a first early warning information is generated; wherein the first early warning information comprises working environment humidity early warning information and dust particle early warning information in the working environment; if the current humidity is greater than the second preset humidity, a second early warning information is generated; wherein the second early warning information comprises transmission power early warning information of the holographic microwave device.

8. A warning device for a work machine, characterized in that The method comprises: a data acquisition module, a first processing module, a second processing module and an early warning module; The data acquisition module is configured to acquire a current holographic microwave image of the working machine by the holographic microwave device, and acquire a current working area of the working machine, a current holographic time-varying characteristic parameter change amount, a current vibration frequency, a current vibration diffusion distance and a current humidity; The first processing module is configured to determine a working machine category and a working machine movement trend of the working machine according to the current holographic microwave image; The second processing module is configured to, if the current working area is greater than or equal to a first preset area, the working machine category is a first preset machine category and the working machine movement trend is a first preset movement trend, determine a correction coefficient according to the current holographic time-varying characteristic parameter change amount, a first preset change amount, the current vibration frequency, a first preset vibration frequency, the current vibration diffusion distance and a first preset vibration diffusion distance; The early warning module is configured to generate early warning information of the working machine according to the correction coefficient, the first preset humidity and the current humidity, and perform early warning according to the early warning information.

9. A terminal device, comprising: The method comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, when the computer program is executed by the processor, the method for early warning of the working machine is realized.

10. A computer-readable storage medium, characterized in that, The method comprises: a stored computer program, wherein when the computer program is running, the device where the computer readable storage medium is located is controlled to execute the method for early warning of the working machine.

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