CN115430917A

CN115430917A - Pulse laser rust removal method, equipment, storage medium and device

Info

Publication number: CN115430917A
Application number: CN202210914034.6A
Authority: CN
Inventors: 胡元峰; 何艳青; 隗会军; 杨飞翔
Original assignee: Haibo Heavy Engineering Sciece and Technology Co Ltd
Current assignee: Haibo Heavy Engineering Sciece and Technology Co Ltd
Priority date: 2022-08-01
Filing date: 2022-08-01
Publication date: 2022-12-06

Abstract

The invention discloses a pulse laser rust removal method, equipment, a storage medium and a device, wherein a preset type of steel plate image to be subjected to rust removal is obtained; carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information; determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter; acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the rust removing process consumes a large amount of manpower and material resources, the rust removing efficiency is low, the production period is prolonged, automatic rust removing is realized, damage caused by irradiation of pulse laser to a workpiece is avoided, the rust removing efficiency is improved, and the production period is shortened.

Description

Pulse laser rust removal method, equipment, storage medium and device

Technical Field

The invention relates to the technical field of laser rust removal, in particular to a pulse laser rust removal method, pulse laser rust removal equipment, a pulse laser rust removal storage medium and a pulse laser rust removal device.

Background

With the development of the mechanical industry and shipbuilding application, in the processing engineering of a plurality of metal products, because the metal products are exposed in the air for a long time or because the metal products are collided, the situation that the workpieces are difficult to rust is avoided, the traditional workpiece rust removing method needs to manually use an iron brush or a chemical reagent to remove the rust, the rust removing process consumes a large amount of manpower and material resources, the rust removing efficiency is low, and the production period is prolonged.

The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.

Disclosure of Invention

The invention mainly aims to provide a pulse laser rust removal method, equipment, a storage medium and a device, and aims to solve the technical problems that in the prior art, an iron brush or a chemical reagent is manually used for removing rust, a large amount of manpower and material resources are consumed in the rust removal process, the rust removal efficiency is low, and the production period is prolonged.

In order to achieve the purpose, the invention provides a pulse laser rust removal method, which comprises the following steps:

acquiring a preset type of steel plate image to be derusted;

carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information;

determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter;

acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time;

and adjusting the laser pulse parameters according to the target image until the obtained target image meets the preset derusting condition.

Optionally, the step of performing rust recognition on the to-be-derusted steel plate image based on a preset rust recognition model to obtain rust parameter information includes:

framing a rust image in the steel plate image to be derusted based on a rust preselection frame in a preset rust recognition model to obtain a rust area to be recognized;

segmenting the rust region to be identified based on a deep learning algorithm to obtain segmented region units;

and carrying out rust identification on the area unit to obtain rust parameter information.

Optionally, the rust parameter information comprises rust coordinates, a rust type, and a rust thickness; the step of performing rust identification on the area unit to obtain rust parameter information comprises the following steps:

counting the characteristic pixel points of the preset coordinate positions in the area units to obtain rust coordinates corresponding to each area unit;

performing rust recognition on the characteristic pixel points according to a preset form recognition algorithm to obtain a rust type;

and performing Fourier transform on the laser reflection signal based on an FFT algorithm, and determining the rust thickness corresponding to the steel plate to be derusted according to the obtained amplitude parameter information.

Optionally, the step of determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy and removing rust from the steel plate to be subjected to rust removal according to the laser pulse parameter includes:

determining laser pulse parameters according to the rust type, the rust thickness and a preset rust removal strategy;

planning a pulse laser path according to the rust coordinates to obtain a target path;

and derusting the steel plate to be derusted according to the target path and the laser pulse parameters.

Optionally, the step of determining laser pulse parameters according to the rust type, the rust thickness, and a preset rust removal strategy includes:

determining a rust grade according to a rust type and the rust thickness in the rust types;

matching a target rust removal strategy from preset rust removal strategies according to the rust grade;

and determining laser pulse parameters according to the laser energy corresponding to the target rust removal strategy.

Optionally, before the step of adjusting the pulse parameter according to the target image until the target image meets a preset derusting condition, the method further includes:

acquiring a pulse signal of a laser in real time;

determining the change degree of the thickness of the rust in the preset dot matrix area according to the frequency change value corresponding to the pulse signal;

and when the change degree reaches a preset threshold value, executing the step of adjusting the pulse parameters according to the target image until the target image meets a preset derusting condition.

Optionally, the step of adjusting the laser pulse parameter according to the target image until the obtained target image meets a preset derusting condition includes:

judging whether the current laser pulse parameter is lower than an ablation threshold corresponding to a rust layer or not according to the rust state in the target image;

and when the current laser pulse parameter is lower than an ablation threshold value corresponding to a rust layer, adjusting the pulse parameter until the obtained target image meets a preset rust removal condition.

In addition, in order to achieve the above object, the present invention also provides a pulsed laser rust removal apparatus including a memory, a processor, and a pulsed laser rust removal program stored on the memory and operable on the processor, the pulsed laser rust removal program being configured to implement the steps of pulsed laser rust removal as described above.

In addition, to achieve the above object, the present invention also provides a storage medium having a pulse laser derusting program stored thereon, which when executed by a processor, implements the steps of the pulse laser derusting method as described above.

In addition, in order to achieve the above object, the present invention also provides a pulse laser rust removing apparatus, including:

the image acquisition module is used for acquiring a preset type of steel plate image to be derusted;

the rust recognition module is used for carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information;

the laser derusting module is used for determining a laser pulse parameter according to the rust parameter information and a preset derusting strategy and derusting the steel plate to be derusted according to the laser pulse parameter;

the image acquisition module is also used for acquiring a target image irradiated by the laser pulse in a preset dot matrix area in real time;

the laser derusting module is further used for adjusting the laser pulse parameters according to the target image until the obtained target image meets a preset derusting condition.

The method comprises the steps of obtaining a preset type of steel plate image to be derusted; carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information; determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter; acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the rust removing process consumes a large amount of manpower and material resources, the rust removing efficiency is low, the production period is prolonged, automatic rust removing is realized, damage caused by irradiation of pulse laser to a workpiece is avoided, the rust removing efficiency is improved, and the production period is shortened.

Drawings

FIG. 1 is a schematic structural diagram of a pulsed laser rust removal device in a hardware operating environment according to an embodiment of the invention;

FIG. 2 is a schematic flow chart of a first embodiment of the pulse laser rust removal method of the invention;

FIG. 3 is a schematic flow chart of a pulse laser derusting method according to a second embodiment of the invention;

FIG. 4 is a schematic flow chart of a pulse laser derusting method according to a third embodiment of the invention;

fig. 5 is a block diagram showing the structure of the first embodiment of the pulse laser rust removing apparatus according to the present invention.

The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a pulsed laser rust removal device in a hardware operating environment according to an embodiment of the present invention.

As shown in fig. 1, the pulse laser rust removing apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), and the optional user interface 1003 may further include a standard wired interface and a wireless interface, and the wired interface for the user interface 1003 may be a USB interface in the present invention. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001 described previously.

Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the pulsed laser descaling apparatus, and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

As shown in FIG. 1, a memory 1005, identified as one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a pulsed laser descaling program.

In the pulsed laser rust removal device shown in fig. 1, the network interface 1004 is mainly used for connecting a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting user equipment; the pulse laser rust removing equipment calls a pulse laser rust removing program stored in a memory 1005 through a processor 1001 and executes the pulse laser rust removing method provided by the embodiment of the invention.

Based on the hardware structure, the embodiment of the pulse laser rust removal method is provided.

Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the pulse laser rust removal method, and the first embodiment of the pulse laser rust removal method is provided.

In this embodiment, the pulse laser derusting method includes the steps of:

step S10: and acquiring a preset type of steel plate image to be derusted.

It should be noted that the execution main body of this embodiment may be an apparatus including a pulse laser rust removal system, and the apparatus is configured with a fiber laser, a high-speed camera, and a laser sensor, where the high-speed camera is used to collect an image of a steel plate to be subjected to rust removal, and the laser sensor is used to receive a signal change rule in a laser rust removal process, so as to determine a rust change according to the signal change rule. The present embodiment takes a pulsed laser rust removal apparatus as an execution subject to perform the following description of the embodiment.

The method can be used for determining the type of the steel plate to be derusted in the steel plate image to be derusted. The types of uses include, but are not limited to, bridge steel, boiler steel, shipbuilding steel, and the like, and the surface features include, but are not limited to, galvanized steel, tin-plated steel, clad steel, and color-coated steel. And determining the type of the steel plate in the image of the steel plate to be derusted according to the application type and the surface characteristic type so as to adjust the parameters of the pulse laser in the later period.

In the concrete implementation, a steel plate image to be derusted is acquired through a high-speed camera, the type of a steel plate in the steel plate image to be derusted is identified according to a preset steel plate identification model, and the steel plate image to be derusted of a preset type is determined.

Step S20: and carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information.

It should be noted that the preset rust recognition model may be a preset model for recognizing rust, and the model may be a model trained based on a deep learning algorithm.

The method can be understood that after the type of the steel plate in the steel plate image to be derusted is determined, the preset rust recognition model is used for recognizing the rust of the steel plate in the steel plate image to be derusted, and the rust parameter information is obtained.

Step S30: and determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter.

It should be noted that the preset rust removal strategy can be a preset rust removal strategy corresponding to different rust parameters so as to meet the rust removal in various scenes.

Step S40: and acquiring a target image irradiated by the laser pulse in the preset dot matrix area in real time.

It should be noted that, in order to ensure the rust removal effect, while the pulse laser rust removal, a target image irradiated by laser pulses in a preset dot matrix area is collected in real time, where the preset dot matrix area may be a preset laser pulse dot matrix area, and the target image is a steel plate image irradiated by laser in the preset dot matrix area.

Step S50: and adjusting the laser pulse parameters according to the target image until the obtained target image meets the preset derusting condition.

It should be noted that, while the rust removal effect is ensured, damage to the bottom layer of the steel plate caused by laser rust removal is avoided, and pulse laser parameters need to be accurately regulated and controlled until the obtained target image meets preset rust removal conditions.

It is understood that the preset rust removing condition refers to a condition where a preset rust mark reaches a threshold index, which includes a rust size, a thickness, and a smoothness.

The method comprises the steps of obtaining a preset type of steel plate image to be derusted; carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information; determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter; acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; according to the method, the laser pulse parameters are adjusted according to the target image until the obtained target image meets the preset derusting condition, compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the derusting process consumes a large amount of manpower and material resources, the derusting efficiency is low, the production period is prolonged, automatic derusting is achieved, damage caused by irradiation of pulse laser to a workpiece is avoided, the derusting efficiency is improved, and the production period is shortened.

Referring to fig. 3, fig. 3 is a schematic flow chart of a second embodiment of the pulse laser rust removing method, and the second embodiment of the pulse laser rust removing method is provided based on the first embodiment shown in fig. 2.

In this embodiment, the step S20 includes:

step S201: and framing the rust image in the steel plate image to be derusted based on a rust preselection frame in a preset rust recognition model to obtain a rust area to be recognized.

The rust pre-selection frame is used for framing a rust area by a fixed size according to coordinates corresponding to rust characteristics in a steel plate image to be derusted, and removing redundant pre-selection frames with the overlapping degree of the pre-selection frames being larger than a preset overlapping threshold value so as to reduce the processing load of the model.

Step S202: and segmenting the rust region to be identified based on a deep learning algorithm to obtain segmented region units.

It should be noted that, in order to improve the rust recognition accuracy, the rust region to be recognized framed by the preselected frame is segmented by a deep learning algorithm, wherein the segmentation step may be to segment the region framed by the preselected frame into n × n units as a candidate region.

Step S203: and carrying out rust identification on the area unit to obtain rust parameter information.

Note that, the rust parameter information is determined from the recognition result by performing rust recognition on the n × n cells.

Further, the rust parameter information includes rust coordinates, a rust type, and a rust thickness, and the step S203 further includes: counting the characteristic pixel points of the preset coordinate positions in the area units to obtain rust coordinates corresponding to each area unit; performing rust recognition on the characteristic pixel points according to a preset form recognition algorithm to obtain rust types; and performing Fourier transform on the laser reflection signal based on an FFT algorithm, and determining the rust thickness corresponding to the steel plate to be derusted according to the obtained amplitude parameter information.

It should be noted that the preset coordinate position may be a coordinate position corresponding to a preset boundary position, for example: and (3) identifying coordinates of four corner positions corresponding to the n x n units, obtaining area units containing rust characteristic points by identifying the rust characteristic points corresponding to the n x n units, and counting the coordinates corresponding to the units containing the rust characteristic points, thereby accurately determining the coordinates of the rust on the steel plate to be derusted.

It can be understood that the preset morphological algorithm may be a preset algorithm for identifying the type of the rust, the algorithm may be a binary image morphological algorithm, and the type of the rust can be identified through the algorithm, the type of the rust includes chemical corrosion, electrochemical corrosion and the like, the chemical corrosion refers to corrosion generated by a direct chemical reaction between a steel surface and a surrounding medium, and the electrochemical corrosion refers to ferrous hydroxide which forms reddish brown due to uneven surface composition or stress of the steel in a humid environment.

It should be understood that the FFT algorithm is an efficient algorithm of DFT, and compared with a general fourier transform algorithm, the FFT algorithm in this embodiment can implement more efficient and accurate signal transformation, in this embodiment, in order to calculate the rust thickness, a laser reflection signal of a spot array area hit by laser is sampled, a complex sequence is obtained by the FFT algorithm for the obtained sampling signal, the complex sequence is subjected to spectrum analysis, and phase detection of a laser signal transmission signal and a reflection signal is implemented according to the obtained amplitude parameter information, so as to determine the rust thickness; the amplitude parameter information comprises phase information and frequency spectrum parameter value information. The method comprises the steps of synchronously acquiring a transmitting signal and a reflecting signal, carrying out Fourier transform on the transmitting signal and the reflecting signal to obtain a frequency spectrum, calculating an initial phase between the transmitting signal and the reflecting signal, and determining a phase difference, so that the rust thickness is determined according to the phase difference.

In this embodiment, the step S30 includes:

step S301: and determining laser pulse parameters according to the rust type, the rust thickness and a preset rust removal strategy.

It should be noted that the preset rust removal strategy includes the corresponding relationship among the rust types, the rust thicknesses, and the laser pulse parameters, and in order to ensure the rust removal efficiency, different pulse lasers need to be selected for removing rust according to different rust types and different rust thicknesses.

The preset rust removal strategy comprises thermoplastic expansion rust removal, melting type rust removal and gasification type rust removal, and the three different rust removal modes correspond to different laser pulse parameters.

Further, the step S301 further includes: determining a rust grade according to a rust type in the rust types and the rust thickness; matching a target rust removal strategy from preset rust removal strategies according to the rust grade; and determining laser pulse parameters according to the laser energy corresponding to the target rust removal strategy.

The rust types comprise chemical rust and electrochemical rust, and the rust grade is determined according to the thicknesses of the rust corresponding to the two types, so that one of thermoplastic expansion rust removal, molten rust removal and gasification rust removal is matched in the rust grade to serve as a target rust removal strategy.

It can be understood that due to the fact that different types and thicknesses of rust need different pulse laser parameters to ensure removal efficiency, rust grades are determined according to the types and thicknesses of the rust, and rust removal requirements are met by matching with a rust removal method included in a preset rust removal strategy.

In the concrete implementation, different pulse laser energies have different rust treatment time and rust removal degree, so that the selection of proper laser energy is particularly important, and the rust states under different laser energies are different, so that laser pulse parameters are determined by matching the rust type and the rust thickness with the laser energy corresponding to the target rust removal strategy, and the damage of the laser pulse to the steel body can be effectively avoided while the rust removal rate is improved.

Step S302: and planning a pulse laser path according to the rust coordinates to obtain a target path.

It should be noted that, because the positions and thicknesses of the rusts generated are not completely consistent, in the prior art, the position of the pulse laser can only be adjusted by manually controlling the laser dot matrix area, in order to improve convenience, the scheme adjusts the pulse laser path by the rusts coordinate, and the pulse laser path refers to that when the laser removes rust on a steel plate, the optimal moving path of the laser is planned as a target path according to the rusts position coordinate on the steel plate, so that the moving burden of the laser is reduced, and the time is saved.

Step S303: and derusting the steel plate to be derusted according to the target path and the laser pulse parameters.

It should be noted that the time can be effectively saved by derusting the steel plate to be derusted through the target path and the laser pulse parameters corresponding to the target derusting strategy.

In the embodiment, a rust area to be identified is obtained by obtaining a preset type of steel plate image to be derusted and framing a rust image in the steel plate image to be derusted based on a rust preselection frame in a preset rust identification model; segmenting the rust area to be identified based on a deep learning algorithm to obtain segmented area units; performing rust identification on the area unit to obtain rust parameter information, and determining a laser pulse parameter according to the rust type, the rust thickness and a preset rust removal strategy; planning a pulse laser path according to the rust coordinates to obtain a target path; derusting the steel plate to be derusted according to the target path and the laser pulse parameters, and acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; according to the method, the laser pulse parameters are adjusted according to the target image until the obtained target image meets the preset derusting condition, compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the derusting process consumes a large amount of manpower and material resources, the derusting efficiency is low, the production period is prolonged, automatic derusting is achieved, damage caused by irradiation of pulse laser to a workpiece is avoided, the derusting efficiency is improved, and the production period is shortened.

Referring to fig. 4, fig. 4 is a schematic flow chart of a third embodiment of the pulse laser rust removing method, and the third embodiment of the pulse laser rust removing method is provided based on the second embodiment shown in fig. 3.

In this embodiment, before the step S50, the method further includes: acquiring a pulse signal of a laser in real time; determining the change degree of the thickness of the rust in the preset dot matrix area according to the frequency change value corresponding to the pulse signal; and when the change degree reaches a preset threshold value, executing the step of adjusting the pulse parameters according to the target image until the target image meets a preset derusting condition.

It should be noted that the preset threshold is a parameter value at which the preset pulse signal peak value variation degree reaches the contact steel plate body.

In the concrete implementation, in order to avoid damage to the steel plate body by the pulse laser, a dynamic process of removing a rust layer under the action of laser energy needs to be obtained in real time, so that a pulse signal of a laser needs to be obtained in real time, and a frequency change value corresponding to an emission signal and a reflection signal in the pulse signal determines the change of the thickness of the rust in a preset dot matrix area.

In this embodiment, the step S50 includes:

step S501: and judging whether the current laser pulse parameter is lower than an ablation threshold corresponding to the rust layer or not according to the rust state in the target image.

It should be noted that the ablation threshold is a thermal threshold when the rusty bottom layer is decomposed, and whether the current laser pulse parameter is lower than the thermal threshold when the rusty bottom layer is decomposed is judged by combining the rusty state in the target image and the pulse signal.

Step S502: and when the current laser pulse parameter is lower than an ablation threshold value corresponding to a rust layer, adjusting the pulse parameter until the obtained target image meets a preset rust removal condition.

It should be noted that the pulse parameters are important parameters influencing the rust removal mechanism and the removal rate of the rust removal layer in the pulse laser rust removal process. At a pulsed laser fluence of a, no melting and vaporization of material is observed in the area where the pulsed laser interacts with the corrosion layer, indicating that the laser parameters are below the ablation threshold of the corrosion layer. In the non-melting process, rust removal relies mainly on elastic expansion, and therefore in this case, the removal rate of the rust removal layer is low, but the influence on the damage of the substrate is small. And (4) removing rust in a hot melting state with the pulse parameter b, so that a rust layer is melted and condensed. On the other hand, with increasing laser pulses, ablation plumes and the formation of small ablation splashes occur, the rust layer being removed at present mainly by thermoelastic expansion and melting. However, when the laser fluence exceeds a predetermined ablation threshold, vaporization and even vapor explosion of the rust layer and the steel substrate surface occur. The impact pressure generated by gas-phase explosion accelerates the removal rate of the loose layer, which is more obvious with gasification impact caused by the increase of laser fluence, and the rust removal efficiency is higher. However, this may lead to strong ablation and thermal damage of the steel substrate. The method of combining the pulse signal and the pulse laser to the dynamic process and the form image data under different working condition parameters can effectively avoid the damage of the steel plate body.

In the embodiment, a rust area to be identified is obtained by obtaining a preset type of steel plate image to be derusted and framing a rust image in the steel plate image to be derusted based on a rust preselection frame in a preset rust identification model; segmenting the rust area to be identified based on a deep learning algorithm to obtain segmented area units; performing rust identification on the area unit to obtain rust parameter information, and determining a laser pulse parameter according to the rust type, the rust thickness and a preset rust removal strategy; planning a pulse laser path according to the rust coordinates to obtain a target path; derusting the steel plate to be derusted according to the target path and the laser pulse parameters, and acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; judging whether the current laser pulse parameter is lower than an ablation threshold corresponding to a rust layer or not according to the rust state in the target image; when the current laser pulse parameters are lower than ablation threshold values corresponding to a rust layer, the pulse parameters are adjusted until the obtained target image meets preset rust removal conditions, compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the rust removal process consumes a large amount of manpower and material resources, the rust removal efficiency is low, the production period is prolonged, automatic rust removal is achieved, meanwhile, damage caused by irradiation of pulse laser to a workpiece is avoided, the rust removal efficiency is improved, and the production period is shortened.

In addition, in order to achieve the above object, the present invention also provides a storage medium having a pulse laser derusting program stored thereon, which when executed by a processor, implements the steps of the pulse laser derusting method as described above.

Referring to fig. 5, fig. 5 is a block diagram showing a first embodiment of the pulse laser rust removing apparatus according to the present invention.

As shown in fig. 5, the pulse laser rust removing apparatus according to the embodiment of the present invention includes:

the image acquisition module 10 is used for acquiring a preset type of steel plate image to be derusted;

the rust recognition module 20 is used for carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information;

the laser derusting module 30 is used for determining a laser pulse parameter according to the rust parameter information and a preset derusting strategy and derusting the steel plate to be derusted according to the laser pulse parameter;

the image acquisition module 10 is further configured to acquire a target image irradiated by the laser pulse in the preset dot matrix area in real time;

the laser derusting module 30 is further configured to adjust the laser pulse parameter according to the target image until the obtained target image meets a preset derusting condition.

In the embodiment, the image of the steel plate to be derusted in a preset type is obtained; carrying out rust recognition on the steel plate image to be derusted based on a preset rust recognition model to obtain rust parameter information; determining a laser pulse parameter according to the rust parameter information and a preset rust removal strategy, and removing rust on the steel plate to be subjected to rust removal according to the laser pulse parameter; acquiring a target image irradiated by laser pulses in a preset dot matrix area in real time; according to the method, the laser pulse parameters are adjusted according to the target image until the obtained target image meets the preset derusting condition, compared with the prior art that rust is removed by manually using an iron brush or a chemical reagent, the derusting process consumes a large amount of manpower and material resources, the derusting efficiency is low, the production period is prolonged, automatic derusting is achieved, damage caused by irradiation of pulse laser to a workpiece is avoided, the derusting efficiency is improved, and the production period is shortened.

Further, the rust recognition module 20 is further configured to frame a rust image in the steel plate image to be derusted based on a rust preselection frame in a preset rust recognition model, so as to obtain a rust area to be recognized; segmenting the rust area to be identified based on a deep learning algorithm to obtain segmented area units; and carrying out rust identification on the area unit to obtain rust parameter information.

Further, the rust recognition module 20 is further configured to count feature pixel points at preset coordinate positions in the area units to obtain rust coordinates corresponding to each area unit; performing rust recognition on the characteristic pixel points according to a preset form recognition algorithm to obtain rust types; and performing Fourier transform on the laser reflection signal based on an FFT algorithm, and determining the rust thickness corresponding to the steel plate to be derusted according to the obtained amplitude parameter information.

Further, the laser derusting module 30 is further configured to determine a laser pulse parameter according to the rust type, the rust thickness, and a preset derusting strategy; planning a pulse laser path according to the rust coordinates to obtain a target path; and derusting the steel plate to be derusted according to the target path and the laser pulse parameters.

Further, the laser rust removing module 30 is further configured to determine a rust grade according to a rust type and the rust thickness in the rust type; matching a target rust removal strategy from preset rust removal strategies according to the rust grade; and determining laser pulse parameters according to the laser energy corresponding to the target rust removal strategy.

Further, the laser derusting module 30 is further configured to obtain a pulse signal of the laser in real time; determining the change degree of the thickness of the rust in the preset dot matrix area according to the frequency change value corresponding to the pulse signal; and when the change degree reaches a preset threshold value, executing the step of adjusting the pulse parameters according to the target image until the target image meets a preset derusting condition.

Further, the laser derusting module 30 is further configured to determine whether the current laser pulse parameter is lower than an ablation threshold corresponding to a rust layer according to the rust state in the target image; and when the current laser pulse parameter is lower than an ablation threshold value corresponding to a rust layer, adjusting the pulse parameter until the obtained target image meets a preset rust removal condition.

It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.

It should be noted that the above-mentioned work flows are only illustrative and do not limit the scope of the present invention, and in practical applications, those skilled in the art may select some or all of them according to actual needs to implement the purpose of the solution of the present embodiment, and the present invention is not limited herein.

In addition, the technical details that are not described in detail in this embodiment can be referred to the pulse laser rust removing method provided in any embodiment of the present invention, and are not described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means can be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order, but rather the words first, second, third, etc. are to be interpreted as names.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., a Read Only Memory (ROM)/Random Access Memory (RAM), a magnetic disk, or an optical disk), and includes several instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A pulse laser rust removal method is characterized by comprising the following steps:

acquiring a preset type of steel plate image to be derusted;

2. The pulse laser rust removing method according to claim 1, wherein the step of performing rust recognition on the steel plate image to be subjected to rust removal based on a preset rust recognition model to obtain rust parameter information comprises:

3. The pulsed laser rust removal method according to claim 2, wherein the rust parameter information includes a rust coordinate, a rust type, and a rust thickness; the step of carrying out rust identification on the area unit to obtain rust parameter information comprises the following steps:

performing rust recognition on the characteristic pixel points according to a preset form recognition algorithm to obtain rust types;

4. The pulse laser rust removing method as claimed in claim 1, wherein the step of determining laser pulse parameters according to the rust parameter information and a preset rust removing strategy and removing rust from the steel plate to be rust removed according to the laser pulse parameters comprises:

5. The pulsed laser descaling method according to claim 4, wherein the step of determining laser pulse parameters according to the rust type, the rust thickness and a preset descaling strategy comprises:

determining a rust grade according to a rust type in the rust types and the rust thickness;

6. The pulsed laser rust removing method according to claim 1, wherein the step of adjusting the pulse parameters according to the target image until the target image satisfies a preset rust removing condition further comprises:

acquiring a pulse signal of a laser in real time;

7. The pulse laser rust removing method according to claim 6, wherein the step of adjusting the laser pulse parameters according to the target image until the obtained target image meets a preset rust removing condition includes:

8. A pulse laser rust removing apparatus, characterized in that the pulse laser rust removing apparatus comprises: a memory, a processor, and a pulsed laser descaling program stored on the memory and executable on the processor, the pulsed laser descaling program when executed by the processor implementing the steps of the pulsed laser descaling method according to any one of claims 1 to 7.

9. A storage medium, characterized in that a pulsed laser rust removal program is stored thereon, which when executed by a processor, implements the steps of the pulsed laser rust removal method according to any one of claims 1 to 7.

10. A pulse laser rust removing device is characterized by comprising: