CN116548998B - Method, device, equipment and medium for determining load of scanning bed - Google Patents

Abstract

Embodiments of the present disclosure provide a method, apparatus, device, and medium for determining a detector scanning bed load, including: determining an association relation table corresponding to the height data and the proportion parameters based on a target association function, wherein the target association function is determined based on a test data sample set; in response to receiving the target height data fed back by the lifting driving module, selecting a target proportion parameter corresponding to the target height data from the association relation table; when the driving force fed back by the sensor module is received, the load of the scanning bed is determined based on the driving force and the target proportion parameter, so that the problem of insufficient accuracy of the determined load of the scanning bed caused by manufacturing and assembly errors can be avoided.

Description

Scanning bed load determination methods, devices, equipment and media

Technical field

Embodiments of the present disclosure relate to the technical field of CT scanning systems and related technical fields, and in particular, to methods, devices, equipment and media suitable for determining a scanning bed load.

Background technique

At present, the CT scanning system mainly consists of two parts: the scanning gantry and the scanning bed, as shown in Figure 1. The scanning gantry is used to emit and receive rays, and the scanning bed is used to move the patient through Y-direction lifting and Z-direction translation movements. It is sent into the scanning hole of the scanning frame to realize the scanning and imaging process of the CT system.

In the existing technology, the Z-direction horizontal motion control parameters of the scanning bed are default values and will not change according to the load size of the scanning bed. However, vibration will occur in the Y-direction due to load changes, as shown in Figure 2. This vibration will cause CT Image quality is degraded, which in turn affects diagnostic efficiency and results. In the existing technology, a theoretical formula is used to calculate the actual load through the driving force fed back by the sensor. However, each component of the scanning bed contains manufacturing errors and installation errors. Examples of its components include support mechanisms, scissor arms, horizontal bed frames, etc. , after the above errors are accumulated, the relationship between driving force and load will be greatly different from the theoretical value. If the theoretical formula is still used to calculate the actual load through the driving force fed back by the sensor, there will be a large error, which will cause the subsequent controller to make wrong judgments. , has a great impact on the subsequent distribution of control parameters, causing the Y-direction vibration to increase, which in turn leads to a decrease in CT image quality.

Based on the problems existing in the existing technology, a method for determining the load of the scanning bed is urgently needed.

Contents of the invention

The embodiments described herein provide a method, device, equipment and medium for determining the load of a scan bed, and solve the problems existing in the existing technology.

In a first aspect, according to the present disclosure, a method for determining a scan bed load is provided, including:

Based on the target correlation function, determine the correlation table corresponding to the height data and the scale parameter, wherein the target correlation function is determined based on the test data sample set;

In response to receiving the target height data fed back by the lifting drive module, select the target proportion parameter corresponding to the target height data from the association table;

When receiving the driving force fed back by the sensor module, the load of the scanning bed is determined based on the driving force and the target proportion parameter.

In some embodiments of the present disclosure, before determining the correlation table corresponding to the height data and the scale parameter based on the target correlation function, the method further includes:

Construct a correlation function between height data and scale parameters, where the correlation function includes correlation functions of different function orders;

Based on the correlation function, determine the test proportion parameters under different test height data;

Based on the relationship between the test proportion parameters and the preset test proportion parameters under different test height data, the target correlation function is determined.

In some embodiments of the present disclosure, determining test proportion parameters under different test height data based on the correlation function includes:

The correlation function with a function order of N order is selected in turn, and the test proportion parameters of different test height data under the correlation function with a function order of N order are determined, where N is an integer greater than or equal to 1.

In some embodiments of the present disclosure, determining the target correlation function based on the relationship between the test proportion parameters and the preset test proportion parameters under different test height data includes:

Compare in turn the relationship between the difference between each test proportion parameter corresponding to the correlation function of the target order and the preset test proportion parameter and the preset difference;

Select the target test height data corresponding to the test proportion parameter whose absolute value is less than or equal to the first preset threshold at each target order and the difference between the preset test proportion parameter and the preset test proportion parameter;

The correlation function corresponding to the largest number of target test height data is determined to be the target correlation function.

In some embodiments of the present disclosure, before determining the test proportion parameters under different test height data based on the correlation function, the method further includes:

The corresponding function coefficients of the correlation function at different function orders are determined based on a random sampling consistency algorithm.

In some embodiments of the present disclosure, determining a correlation table corresponding to height data and scale parameters based on the target correlation function includes:

Based on the target correlation function, determine the proportion parameters corresponding to the data of the scanning bed at different heights;

Build an association table based on height data and scale parameters.

In some embodiments of the present disclosure, the method further includes:

Control parameters are determined based on the load.

In a second aspect, according to the present disclosure, a device for determining a scan bed load is provided, including:

The correlation table determination module is used to determine the correlation table corresponding to the height data and the proportion parameter based on the target correlation function, wherein the target correlation function is determined based on the test data sample set;

A target proportion parameter determination module, configured to select the target proportion parameter corresponding to the target height data from the association table in response to receiving the target height data fed back by the lifting drive module;

A load determination module, configured to determine the load of the scanning bed based on the driving force and the target proportion parameter when receiving the driving force fed back by the sensor module.

In a third aspect, according to the present disclosure, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it implements the steps of the method in any of the above embodiments.

In a fourth aspect, according to the present disclosure, a computer-readable storage medium is provided. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the method in any of the above embodiments are implemented.

The method, device, equipment and medium for determining the load of the scanning bed provided by the embodiments of the present disclosure first determine the correlation table corresponding to the height data and the proportion parameter based on the target correlation function, where the target correlation function is determined based on the test data sample set; and then In response to receiving the target height data fed back by the lifting drive module, select the target proportion parameter corresponding to the target height data from the association table; finally, when receiving the driving force fed back by the sensor module, based on the driving force and the target proportion parameter, determine The load of the scanning bed is determined through the proportional parameters of the driving force and the target. Compared with the existing technology that uses theoretical formulas to calculate the actual load through feedback from the sensor module, the method for determining the load of the scanning bed provided in this application has a target The scaling parameters are determined based on the target correlation function, which can exclude the determined scanning bed load due to manufacturing and assembly errors (every part of the scanning bed contains manufacturing errors and installation errors, including support mechanisms, scissor arms, horizontal bed frames, etc.) To solve the problem of insufficient accuracy, optimal control parameters can be configured according to the load, improving the stability of the motion system, reducing shock and vibration, and improving image scanning quality.

The above description is only an overview of the technical solutions of the embodiments of the present application. In order to have a clearer understanding of the technical means of the embodiments of the present application, they can be implemented according to the content of the description, and in order to achieve the above and other purposes, features and The advantages can be more clearly understood, and the specific implementation methods of the present application are specifically listed below.

Description of the drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly described below. It should be understood that the drawings described below only relate to some embodiments of the present disclosure and do not limit the present disclosure. in:

Figure 1 is a schematic structural diagram of a CT scanning system provided by an embodiment of the present disclosure;

Figure 2 is a schematic diagram of the vibration state of the scanning bed in a CT scanning system provided by an embodiment of the present disclosure;

Figure 3 is a schematic flowchart of a method for determining a scan bed load provided by an embodiment of the present disclosure;

Figure 4 is a schematic structural diagram of a scanning bed provided by an embodiment of the present disclosure;

Figure 5 is a schematic flowchart of another method for determining the load of a scan bed provided by an embodiment of the present disclosure;

Figure 6 is a schematic structural diagram of a device for determining the load of a scanning bed provided by an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of a computer device provided by an embodiment of the present disclosure.

In the drawings, signs with the same last two digits correspond to the same elements. It should be noted that the elements in the figures are schematic and not drawn to scale.

Detailed ways

In order to make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present disclosure. Based on the described embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative efforts also fall within the scope of protection of the present disclosure.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosed subject matter belongs. It will be further understood that terms such as those defined in commonly used dictionaries shall be construed to have meanings consistent with their meanings in the context of the specification and the relevant technology, and shall not be construed in an idealized or overly formal form, Unless otherwise expressly defined herein. As used herein, a statement that two or more parts are "connected" or "coupled" together shall mean that the parts are joined together directly or through one or more intervening components.

Reference herein to "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of the phrase "embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive with other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.

The term "and/or" in this article is just an association relationship that describes related objects, indicating that there can be three relationships. For example, A and/or B can mean: A exists, A and B exist at the same time, and B exists. three conditions. In addition, the character "/" in this article generally indicates that the related objects are an "or" relationship.

Furthermore, in all embodiments of the present disclosure, terms such as “first” and “second” are only used to distinguish one component (or part of a component) from another component (or part of a component).

In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more groups (including two groups).

In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

Based on the problems existing in the prior art, Figure 3 is a schematic flowchart of a method for determining the load of the scan bed provided by an embodiment of the present disclosure. As shown in Figure 3, the specific process of the method for determining the load of the scan bed includes:

S110. Based on the target correlation function, determine the correlation table corresponding to the height data and the scale parameter.

Among them, the target correlation function is determined based on the test data sample set.

As shown in Figure 4, the scanning bed body includes a bed board 101, a horizontal bed frame 102, a scissor lifting frame 103, a lifting drive module 104 and a base plate 105; among them, the bed board 101 is horizontally slidably assembled on the top surface of the horizontal bed frame 102; the scissors The top two ends of the lifting frame 103 include a top transfer end and a top sliding end. The top transfer end is transferred and assembled on the bottom end surface of the horizontal bed frame 102. The top sliding end is slidably assembled on the bottom end surface of the horizontal bed frame 102, and the scissors The bottom two ends of the lifting frame 103 include a bottom transfer end and a bottom sliding end. The bottom transfer end is transferred and assembled on the top surface of the base plate 105, and the bottom sliding end is slidably assembled on the top surface of the base plate 105; the two lifting drive modules 104 The working ends are respectively connected to the top surface of the bottom plate 105 and one side force arm of the scissor lifting frame 103 in a one-to-one correspondence, so as to effectively complete the predetermined lifting and translation functions of the scanning bed through the above structure.

In addition, the sensor module is arranged on the lifting drive module 104 or the bottom plate 105. When the load of the scanning bed changes, the sensor module can feed back the driving force corresponding to the load.

As a specific implementation, based on the target correlation function, the specific process of determining the correlation table corresponding to the height data and the scale parameter is:

Specifically, before installing the horizontal bed frame 102, the data of the sensor module is reset to zero. After installing the horizontal bed frame 102, the scanning bed is lowered to the lowest point. At this time, based on the target correlation function, it can be determined that the scanning bed is at the lowest point. When the point is reached, the scale parameter is: By raising the scanning bed at equal intervals, the corresponding scaling parameters are determined when the scanning bed is at different heights, that is, the correlation table between the height data and the scaling parameter is shown in Table 1 below:

Table 1: Association table

In this embodiment, during the process of determining the correlation table corresponding to the height data and the proportion parameter, the corresponding mass of the scanning bed is M=M1+0, and M1 is the mass of the horizontal bed frame, that is, the height is determined under zero load. Correlation table corresponding to data and scale parameters.

In the above embodiments, the method for determining the load of the scan bed is applied to the control terminal. The control terminal may be a personal computer, a laptop, or an iPad. This is not specifically limited in the embodiments of the present disclosure.

S120. In response to receiving the target height data fed back by the lifting drive module, select the target proportion parameter corresponding to the target height data from the association table.

After determining the correlation table corresponding to the height data and the proportion parameter, the scanning bed enters the normal workflow. During the working process of the scanning bed, the control terminal receives the target height data of the scanning bed rising fed back by the lifting drive module. After the target height data is fed back by the drive module, the target proportion parameter corresponding to the target height data is searched from the association table. For example, based on Table 1, when the control terminal receives the target height data responded by the lifting drive module, then from the association table Select and target height data from table The corresponding target proportion parameter is/> , the target height data that the control terminal receives from the lift drive module is/> , then select the target height data/> from the association table The corresponding target proportion parameter is/> .

S130. When receiving the driving force fed back by the sensor module, determine the load of the scanning bed based on the driving force and the target proportion parameter.

After determining the target proportion parameter corresponding to the target height data of the lifting drive module of the scanning bed, the control terminal receives the driving force fed back by the sensor module, and after receiving the driving force fed back by the sensor, determines the scan based on the driving force and the target proportion parameter. Loads of beds.

Specifically, the relationship between driving force, proportional parameters and load satisfies , where,/> Indicates the proportional parameter corresponding to height h, m is the mass of the load, and F is the driving force.

That is, when the scanning bed scans the load, the scissor lifting frame 103 of the scanning bed drives the bed board 101 and the horizontal bed frame 102 to move in the Y direction, and the lifting drive module feeds back the height information of the bed board 101 and the horizontal bed frame 102, that is, The target height data and the sensor module feedback the detected driving force. At this time, based on the driving force and target proportion parameters, the load of the scanning bed is determined, and then the target object determines the control parameters based on the determined load, and realizes the scanning signal sent to the target object. accuracy.

The method for determining the load of the scan bed provided by the embodiment of the present disclosure first determines the correlation table corresponding to the height data and the proportion parameter based on the target correlation function, where the target correlation function is determined based on the test data sample set; and then in response to receiving the lift drive For the target height data fed back by the module, the target proportion parameter corresponding to the target height data is selected from the association table; finally, when the driving force fed back by the sensor module is received, the load of the scanning bed is determined based on the driving force and the target proportion parameter, that is, The load of the scanning bed is determined through the driving force and the target proportional parameter. Compared with the existing technology that uses theoretical formulas to calculate the actual load through feedback from the sensor module, the target proportional parameter in the method for determining the load of the scanning bed provided by this application is based on the target correlation function. Determined, the problem of insufficient accuracy of the determined scanning bed load due to manufacturing and assembly errors (every part of the scanning bed contains manufacturing errors and installation errors, including support mechanisms, scissor arms, horizontal bed frames, etc.) can be eliminated, and then The optimal control parameters can be configured according to the load to improve the stability of the motion system, reduce impact and vibration, and improve image scanning quality.

Based on the above embodiments, Figure 5 is a schematic flowchart of another method for determining the load of a scan bed provided by an embodiment of the present disclosure. As shown in Figure 5 , before step S110, it also includes:

S101. Construct a correlation function between height data and scale parameters.

Among them, the correlation function includes correlation functions of different function orders.

Specifically, the correlation function corresponding to the constructed height data and the scale parameter satisfies: , h is the height data, i represents the order of the correlation function, i is greater than or equal to 1 and less than or equal to n,/> Indicates the proportional parameters corresponding to different height parameters h when the order of the correlation function is n. That is, the correlation function can be a correlation function of order 1. In this case, the correlation function is: , the correlation function is a correlation function that can also be a second-order correlation function. In this case, the correlation function is:/> .

S102. Based on the correlation function, determine the test proportion parameters under different test height data.

In a specific implementation, the specific process of determining the test proportion parameters under different test height data is: sequentially selecting a correlation function with an N-order function, and determining a correlation function with an N-order function for different test height data. The test proportion parameter below, where N is an integer greater than or equal to 1.

Specifically, select the correlation function whose function order is 1st order , determine the test proportion parameters corresponding to different test height data under the current order correlation function, for example, the test height data includes/> , respectively obtain the test height data/> Correlation function of order 1/> The corresponding test proportion parameters are as follows, namely/> ;Select a correlation function whose function order is 2nd order , determine the test proportion parameters corresponding to different test height data under the current order correlation function, for example, the test height data includes/> , respectively obtain the test height data Correlation function at 2nd order/> The corresponding test proportion parameters are as follows, namely ;Select a correlation function whose function order is nth order/> , determine the test proportion parameters corresponding to different test height data under the current order correlation function, for example, the test height data includes/> , respectively obtain the test height data/> Correlation function of order n The corresponding test proportion parameters are as follows, namely/> .

S103. Determine the target correlation function based on the relationship between the test proportion parameters and the preset test proportion parameters under different test height data.

In a specific implementation, based on the relationship between the test proportion parameters and the preset test proportion parameters under different test height data, the target correlation function is determined, including:

Compare in turn the relationship between the difference between each test proportion parameter corresponding to the correlation function of the target order and the preset test proportion parameter and the preset difference; select the absolute value of the difference from the preset test proportion parameter at each target order The target test height data corresponding to the test proportion parameter that is less than or equal to the first preset threshold; when the number of target test height data is greater than or equal to the second preset threshold, the association with the target order corresponding to the target test height data The function is the target correlation function.

Among them, the preset test proportion parameters are based on the geometric dimensions of the horizontal bed frame of the scanning bed. The corresponding test proportion parameters of the horizontal bed frame under different test height data are calculated using the principle of virtual work. That is, the preset test proportion parameters include .

Specifically, first find the first-order correlation function The corresponding test proportion parameter when and preset test ratio parameters/> The difference of /> with/> The difference/> ,/> with/> The difference/> ,...,/> with/> The difference/> , and then compare/> with/> The difference/> Difference from default/> ,/> with/> The difference/> Difference from default/> ,...,/> with/> The difference/> Difference from default/> The relationship between the test proportion parameter and the preset test proportion parameter is obtained, and the test height data corresponding to the test proportion parameter whose absolute value is less than or equal to the first preset threshold is the target test height data.

Then find the second-order correlation function The corresponding test proportion parameter when and preset test ratio parameters/> The difference of /> with/> The difference/> ,/> with/> The difference/> ,...,/> with/> The difference , and then compare/> with/> The difference/> Difference from default/> ,/> with/> The difference Difference from default/> ,...,/> with/> The difference/> Difference from default/> The relationship between the test proportion parameter and the preset test proportion parameter is obtained, and the test height data corresponding to the test proportion parameter whose absolute value is less than or equal to the first preset threshold is the target test height data.

Then find the correlation function of order n The corresponding test proportion parameter when and preset test ratio parameters/> The difference of /> with/> The difference/> ,/> with/> The difference/> ,...,/> with/> The difference/> , and then compare/> with/> The difference/> Difference from default/> ,/> with/> The difference/> Difference from default/> ,...,/> with/> The difference/> Difference from default/> The relationship between the test proportion parameter and the preset test proportion parameter is obtained, and the test height data corresponding to the test proportion parameter whose absolute value is less than or equal to the first preset threshold is the target test height data.

Finally, the target correlation function is determined based on the number of target test height data determined under different order correlation functions.

As an implementation manner, the correlation function corresponding to the largest number of target test height data is selected as the target correlation function.

In the above embodiment, before determining the test proportion parameters under different test height data based on the correlation function, it also includes:

Determine the corresponding function coefficients of the correlation function at different function orders.

The specific process of determining the function coefficients corresponding to the correlation function at different function orders includes: based on the random sampling consensus algorithm (RANSAC), through random sampling and increasing the number of iterations, determine the function coefficients corresponding to the correlation function at different function orders.

In addition, in order to ensure the accuracy of the function coefficients corresponding to the determined correlation function at different function orders, by increasing the number of iterations, the accuracy of the obtained function coefficients is guaranteed to be higher, and the increase in the number of iterations means that the test sample data The amount of calculation will increase as the amount of calculation increases. This application can use CUDA to accelerate when determining the function coefficients corresponding to the correlation function at different function orders, thereby improving the efficiency of determining the function coefficients corresponding to the correlation function.

In addition, after the load is determined, the control parameters are determined based on the load, so that the scanning bed can operate stably under the determined control parameters and reduce the impact vibration of the scanning bed body, which in turn helps to improve the image scanning quality.

Based on the above embodiments, Figure 6 is a schematic structural diagram of a device for determining the load of a scan bed provided by an embodiment of the present disclosure. As shown in Figure 6, the device for determining the load of a scan bed includes:

The correlation table determination module 610 is used to determine the correlation table corresponding to the height data and the scale parameter based on the target correlation function, where the target correlation function is determined based on the test data sample set;

The target proportion parameter determination module 620 is configured to select the target proportion parameter corresponding to the target height data from the association table in response to receiving the target height data fed back by the lifting drive module;

The load determination module 630 is configured to determine the load of the scanning bed based on the driving force and the target proportion parameter when receiving the driving force fed back by the sensor module.

The device for determining the load of the scanning bed provided by the embodiment of the present application first determines the correlation table corresponding to the height data and the proportion parameter based on the target correlation function, where the target correlation function is determined based on the test data sample set; and then in response to receiving the lift drive For the target height data fed back by the module, the target proportion parameter corresponding to the target height data is selected from the association table; finally, when the driving force fed back by the sensor module is received, the load of the scanning bed is determined based on the driving force and the target proportion parameter, that is, The load of the scanning bed is determined through the driving force and the target proportional parameter. Compared with the existing technology that uses theoretical formulas to calculate the actual load through feedback from the sensor module, the target proportional parameter in the method for determining the load of the scanning bed provided by this application is based on the target correlation function. Determined, the problem of insufficient accuracy of the determined scanning bed load due to manufacturing and assembly errors (every part of the scanning bed contains manufacturing errors and installation errors, including support mechanisms, scissor arms, horizontal bed frames, etc.) can be eliminated, and then The optimal control parameters can be configured according to the load to improve the stability of the motion system, reduce impact and vibration, and improve image scanning quality.

In a specific implementation, the device for determining the load of the scan bed also includes a correlation function building module, a test proportion parameter determination module and a target correlation function determination module;

A correlation function building module, used to construct a correlation function between height data and proportion parameters, where the correlation function includes correlation functions of different function orders;

The test proportion parameter determination module is used to determine the test proportion parameters under different test height data based on the correlation function;

The target correlation function determination module is used to determine the target correlation function based on the relationship between the test proportion parameters and the preset test proportion parameters under different test height data.

In a specific implementation, the specific implementation process of the test proportion parameter determination module includes:

Select the correlation function with an N-order function in turn to determine the test proportion parameters of different test height data under the N-order correlation function, where N is an integer greater than or equal to 1.

In a specific implementation, the target correlation function determination module includes a comparison unit, a target test height data selection unit and a target correlation function determination unit;

The comparison unit is used to sequentially compare the relationship between the difference between each test proportion parameter corresponding to the correlation function of the target order and the preset test proportion parameter and the preset difference;

The target test height data selection unit is used to select the target test height data corresponding to the test proportion parameter whose absolute value of the difference from the preset test proportion parameter is less than or equal to the first preset threshold at each target order;

The target correlation function determination unit is used to determine the correlation function corresponding to the maximum number of target test height data, which is the target correlation function.

In a specific implementation, the device for determining the load of the scan bed also includes: a function coefficient determination module;

The function coefficient determination module is used to determine the function coefficients corresponding to the correlation function at different function orders.

In a specific implementation, the association table determination module includes a proportion parameter determination unit and an association table construction unit;

Based on the target correlation function, determine the proportion parameters corresponding to the data of the scanning bed at different heights;

Build an association table based on height data and scale parameters.

The function coefficients corresponding to the function at different function orders.

In a specific implementation, the association table determination module includes a proportion parameter determination unit and an association table construction unit;

An embodiment of the present application also provides a computer device. Please refer to Figure 7 for details. Figure 7 is a basic structural block diagram of the computer equipment in this embodiment.

The computer device includes a memory 410 and a processor 420 that are communicatively connected to each other via a system bus. It should be noted that the figure only shows a computer device having components 410-420, but it should be understood that implementation of all illustrated components is not required, and more or fewer components may be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and/or information processing according to preset or stored instructions. Its hardware includes but is not limited to microprocessors, special-purpose Integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate array (Field-ProgrammableGate Array, FPGA), digital processor (Digital Signal Processor, DSP), embedded devices, etc.

Computer equipment can be computing equipment such as desktop computers, notebooks, PDAs, and cloud servers. Computer equipment can interact with users through keyboards, mice, remote controls, touch pads, or voice-activated devices.

The memory 410 includes at least one type of readable storage medium. The readable storage medium includes non-volatile memory (non-volatile memory) or volatile memory, such as flash memory (flash memory), hard disk, multimedia card, card type Memory (for example, SD or DX memory, etc.), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) ), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disks, optical disks, etc. RAM can include static RAM or dynamic RAM RAM. In some embodiments, memory 410 may be an internal storage unit of the computer device, such as a hard drive or memory of the computer device. In other embodiments, the memory 410 may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), or a secure digital (SD) device equipped on the computer device. card or flash card (Flash Card), etc. Of course, the memory 410 may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the memory 410 is usually used to store the operating system and various application software installed on the computer device, such as the program code of the above method. In addition, the memory 410 can also be used to temporarily store various types of data that have been output or will be output.

Processor 420 is generally used to perform the overall operations of the computer device. In this embodiment, the memory 410 is used to store program codes or instructions, and the program codes include computer operation instructions. The processor 420 is used to execute the program codes or instructions stored in the memory 410 or process data, such as the program codes for running the above methods.

In this article, the bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus system can be divided into address bus, data bus, control bus, etc. For ease of presentation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

Another embodiment of the present application also provides a computer-readable medium. The computer-readable medium may be a computer-readable signal medium or a computer-readable medium. The processor in the computer reads the computer-readable program code stored in the computer-readable medium, so that the processor can perform the functional actions specified in each step or a combination of steps in the above method; generate a program implemented in the block diagram A device that performs specified functional actions in each block or combination of blocks.

Computer-readable media include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared memory or semiconductor systems, equipment or devices, or any appropriate combination of the foregoing. The memory is used to store program code or instructions. The program code includes computer operating instructions, The processor is used to execute the program codes or instructions of the above methods stored in the memory.

For the definitions of the memory and the processor, reference may be made to the foregoing description of the computer device embodiments, which will not be described again here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.

Each functional unit or module in various embodiments of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

Integrated units may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on this understanding, the technical solution of the present application is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to cause a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code.

As used herein and in the appended claims, the singular form of a word includes the plural form and vice versa, unless the context clearly dictates otherwise. Thus, references to the singular will usually include the plural of the corresponding term. Similarly, the words "comprising" and "includes" will be interpreted to mean inclusively and not exclusively. Likewise, the terms "including" and "or" should be construed as inclusive unless such construction is expressly prohibited by the context. Where the term "example" is used herein, particularly when it follows a group of terms, it is illustrative and illustrative only and should not be considered exclusive or comprehensive. .

Further aspects and scope of adaptability become apparent from the description provided herein. It should be understood that various aspects of the present application may be implemented alone or in combination with one or more other aspects. It should also be understood that the description and specific examples herein are intended for purposes of illustration only and are not intended to limit the scope of the application.

Several embodiments of the present disclosure have been described in detail above, but it is obvious that those skilled in the art can make various modifications and variations to the embodiments of the present disclosure without departing from the spirit and scope of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims (6)

1. A method of determining a load of a scanning bed, comprising:

constructing a correlation function of the height data and the proportion parameters, wherein the correlation function comprises correlation functions of different function orders, and the correlation functions satisfy the following conditions:h is height data, n represents the order of the correlation function, i is greater than or equal to 1 and less than or equal to n, ">The method comprises the steps that proportional parameters corresponding to different height parameters h when the order of the correlation function is n, wherein the proportional parameters are proportional parameters of load and driving force;

determining corresponding function coefficients of the association function in different function orders based on a random sampling consistency algorithm;

determining test proportion parameters under different test height data based on the correlation function;

determining a target association function based on the relation between the test proportion parameters under different test height data and the preset test proportion parameters;

determining an association relation table corresponding to the height data and the proportion parameters under a zero load state based on a target association function, wherein the target association function is determined based on a test data sample set, and the target association function is an association function of the height data and the proportion parameters;

responding to the received target height data fed back by the lifting driving module, and selecting a target proportion parameter corresponding to the target height data from the association relation table;

upon receiving the driving force fed back by the sensor module, determining the scanning bed based on the driving force and the target proportion parameterA load, wherein the relationship of the driving force, the target proportion parameter and the load of the scanning bed satisfies，/>The height is h, m is the mass of the scanning bed and the load, and F is the driving force;

wherein, based on the association function, determining the test proportion parameters under different test height data comprises:

sequentially selecting the correlation functions with the function orders of N, and determining test proportion parameters of different test height data under the correlation functions with the function orders of N, wherein N is an integer greater than or equal to 1;

the determining the target association function based on the relation between the test proportion parameters under different test height data and the preset test proportion parameters comprises the following steps:

sequentially comparing the relation between the difference value of each test proportion parameter corresponding to the correlation function of the target order and the preset test proportion parameter and the preset difference value;

selecting target test height data corresponding to test proportion parameters with absolute values of differences from preset test proportion parameters smaller than or equal to a first preset threshold under each target order;

and determining the corresponding association function as the target association function when the number of the target test height data is the largest.

2. The method according to claim 1, wherein determining the association table of the height data and the scale parameter based on the target association function includes:

determining proportional parameters corresponding to the data of the scanning bed at different heights based on the target correlation function;

and constructing an association relation table based on the height data and the proportion parameters.

3. The method according to claim 1, wherein the method further comprises:

a control parameter is determined based on the load.

4. A scanning bed load determination apparatus, comprising:

the correlation function construction module is used for constructing correlation functions of the height data and the proportion parameters, wherein the correlation functions comprise correlation functions with different function orders, and the correlation functions satisfy the following conditions:h is height data, n represents the order of the correlation function, i is greater than or equal to 1 and less than or equal to n, ">The method comprises the steps that proportional parameters corresponding to different height parameters h when the order of the correlation function is n, wherein the proportional parameters are proportional parameters of load and driving force;

the function coefficient determining module is used for determining the function coefficients corresponding to the correlation functions in different function orders based on a random sampling consistency algorithm;

the test proportion parameter determining module is used for determining test proportion parameters under different test height data based on the association function;

the target association function determining module is used for determining a target association function based on the relation between the test proportion parameters under different test height data and the preset test proportion parameters;

the association relation table determining module is used for determining an association relation table corresponding to the height data and the proportion parameters under the zero load state based on a target association function, wherein the target association function is determined based on a test data sample set, and the target association function is an association function of the height data and the proportion parameters;

the target proportion parameter determining module is used for responding to the target height data fed back by the lifting driving module and selecting target proportion parameters corresponding to the target height data from the association relation table;

a load determining module for determining the load of the scanning bed based on the driving force and the target proportion parameter when the driving force fed back by the sensor module is received, wherein the relation among the driving force, the target proportion parameter and the load of the scanning bed satisfies，/>The height is h, m is the mass of the scanning bed and the load, and F is the driving force;

the test proportion parameter determining module is further used for sequentially selecting the correlation functions with the function orders of N, and determining test proportion parameters of different test height data under the correlation functions with the function orders of N, wherein N is an integer greater than or equal to 1;

the target correlation function determining module comprises a comparing unit, a target test height data selecting unit and a target correlation function determining unit;

the comparison unit is used for sequentially comparing the relation between the difference value of each test proportion parameter corresponding to the correlation function of the target order and the preset test proportion parameter and the preset difference value;

the target test height data selecting unit is used for selecting target test height data corresponding to the test proportion parameters with the absolute value of the difference value smaller than or equal to the first preset threshold value under each target order;

the target correlation function determining unit is used for determining that the correlation function corresponding to the maximum number of the target test height data is the target correlation function.

5. A computer device, comprising:

one or more processors;

storage means for storing one or more programs,

when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-3.

6. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1-3.