Additive manufacturing equipment and self-checking method and device for hardware configuration parameters of additive manufacturing equipment

Abstract

The invention relates to the technical field of manufacturing equipment, and discloses additive manufacturing equipment and a self-checking method and device for hardware configuration parameters of the additive manufacturing equipment. The method comprises the steps that laser feedback signals are read after lasers are powered on, and the number of the lasers is determined based on the laser feedback signals; comparing the number of the lasers with the laser configuration parameters to obtain a laser configuration parameter detection result; reading sampling values of PLC analog quantity channels and sensor type configuration parameters one by one; the sampling value of the PLC analog quantity channel is compared with the broken line judgment value, and the broken line marking value of the circulating air sensor is determined; and determining a configuration parameter detection result of the circulating air sensor based on the sensor type configuration parameter and the broken line mark value of the circulating air sensor. According to the method, the consequence of printing scrapping possibly caused by negligence of mismatching or mismatching of parameters during manual configuration is avoided, the operation difficulty of a user of the additive manufacturing equipment is reduced, and the intelligent level of the additive manufacturing equipment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of manufacturing equipment, and in particular to an additive manufacturing equipment and a self-checking method and device for hardware configuration parameters thereof. Background Art

[0002] SLM (Selective Laser Melting) additive manufacturing equipment is a metal additive manufacturing technology equipment. In SLM additive manufacturing equipment, the increase in the number of lasers can not only significantly improve printing efficiency, but also optimize printing quality and expand the scope of application. The various types of circulating wind sensors play an indispensable role in ensuring the stability of the printing environment and monitoring the printing process and quality.

[0003] The self-checking method of the related configuration parameters cannot accurately self-check the laser quantity parameters and the circulating wind sensor type parameters, resulting in a decrease in the sintering quality of the workpiece, which may lead to the scrapping of the workpiece. Summary of the invention

[0004] In view of this, the present invention provides a self-inspection method and device for additive manufacturing equipment and its hardware configuration parameters to solve the problem that related self-inspection methods may misdetect laser quantity parameters and circulating wind sensor type parameters, thereby affecting the sintering quality of workpieces and possibly causing the workpieces to be scrapped.

[0005] In a first aspect, the present invention provides a method for self-checking hardware configuration parameters of an additive manufacturing device, the method comprising:

[0006] After the lasers are powered on, the laser feedback signals are read one by one, and the number of lasers is determined based on the laser feedback signals;

[0007] Acquire laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain laser configuration parameter detection results;

[0008] After the circulating air sensor is powered on, read the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one;

[0009] Obtain the disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine the disconnection mark value of the circulating air sensor based on the comparison result;

[0010] Determine a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection flag value of the circulating wind sensor;

[0011] The self-test results of the hardware configuration parameters of the additive manufacturing equipment are determined based on the detection results of the laser configuration parameters and the circulation wind sensor configuration parameters.

[0012] The self-check method of the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment reads the laser feedback signals one by one after the laser is powered on, determines the number of lasers based on the laser feedback signals; obtains the laser configuration parameters, compares the number of lasers with the laser configuration parameters, and obtains the laser configuration parameter detection results; after the circulating air sensor is powered on, reads the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one; obtains the disconnection judgment value, compares the sampling value of the PLC analog channel with the disconnection judgment value, and determines the disconnection mark value of the circulating air sensor based on the comparison result; and determines the disconnection mark value of the circulating air sensor based on the sensor type configuration parameter. The circulating wind sensor configuration parameter detection result is determined based on the laser configuration parameter detection result and the circulating wind sensor configuration parameter detection result; the self-test result of the additive manufacturing equipment hardware configuration parameter is determined based on the laser configuration parameter detection result and the circulating wind sensor configuration parameter detection result; by self-checking the laser quantity parameter and the circulating wind sensor type parameter, the consequence of the possible scrapping of the printed workpiece due to negligent mismatch or missing parameters during manual configuration is avoided, the parameter configuration work pressure of the operator is reduced, the corresponding losses caused by configuration errors are avoided, the operating difficulty of the additive manufacturing equipment users is reduced, and the intelligence of the additive manufacturing equipment is improved.

[0013] In an optional implementation, after the lasers are powered on, the laser feedback signals are read one by one, and the number of lasers is determined based on the laser feedback signals, including:

[0014] Set the initial value of the number of lasers to zero;

[0015] If the laser feedback signal is at a high level, the initial value of the number of lasers is increased by one. If the laser feedback signal is at a low level, the level state of the next laser feedback signal is determined until the laser feedback signals are traversed to obtain the number of lasers.

[0016] The self-checking method of the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment sets the initial value of the number of lasers, and traverses all laser feedback signals according to the level status of the feedback signals to obtain the total number of lasers, thereby realizing the one-by-one detection of the laser level status, and laying a foundation for the self-checking of the laser number configuration parameters.

[0017] In an optional implementation, comparing the sampling value of the PLC analog channel with the disconnection judgment value, and determining the disconnection mark value of the circulating wind sensor based on the comparison result, includes:

[0018] If the sampling value of the PLC analog channel is less than the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to true; wherein the circulating wind sensor is connected to the PLC analog channel in a one-to-one correspondence;

[0019] Alternatively, if the sampling value of the PLC analog channel is greater than or equal to the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to false.

[0020] The self-check method for the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment realizes the setting of the circulating wind sensor disconnection mark value by comparing the sampling value of the PLC analog channel and the disconnection judgment value, thereby laying a foundation for the detection of the circulating wind sensor configuration parameters.

[0021] In an optional implementation, determining the circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection flag value of the circulating wind sensor includes:

[0022] Determine the circulating wind sensor type based on the sensor type configuration parameter; the circulating wind sensor types include wind speed sensor, wind volume sensor and wind pressure sensor;

[0023] The disconnection mark value of the circulating wind sensor is compared based on the circulating wind sensor type, and the circulating wind sensor configuration parameter detection result is determined based on the comparison result.

[0024] The self-checking method for the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment determines the type of the circulating wind sensor through the sensor type configuration parameters, and determines the detection result of the circulating wind sensor configuration parameters using the broken line mark value of the circulating wind sensor and the type of the circulating wind sensor, thereby achieving accurate judgment on the type and connection status of the circulating wind sensor, and avoiding the possible scrapping of the printed workpiece due to negligent mismatching or missing parameters during manual configuration.

[0025] In an optional implementation, comparing the disconnection mark value of the circulating wind sensor based on the circulating wind sensor type, and determining the circulating wind sensor configuration parameter detection result based on the comparison result, includes:

[0026] Match the circulating wind sensor type with the broken wire flag value of the circulating wind sensor;

[0027] If the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is true, the circulating wind sensor configuration parameter detection result is a sensor configuration error alarm;

[0028] Alternatively, if the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is false, the circulating wind sensor configuration parameter detection result is that the sensor configuration is correct.

[0029] The self-checking method for the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment automatically issues an alarm prompt when a sensor configuration error is detected, thereby reducing the parameter configuration workload of operators, avoiding corresponding losses caused by configuration errors, reducing the operating difficulty for users of the additive manufacturing equipment, and improving the intelligence of the additive manufacturing equipment.

[0030] In a second aspect, the present invention provides a self-checking device for hardware configuration parameters of an additive manufacturing device, the device comprising:

[0031] A first reading module, used for reading the laser feedback signals one by one after the lasers are powered on, and determining the number of lasers based on the laser feedback signals;

[0032] A first comparison module is used to obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain a laser configuration parameter detection result;

[0033] The second reading module is used to read the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one after the circulating wind sensor is powered on;

[0034] The second comparison module is used to obtain the disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine the disconnection mark value of the circulating air sensor based on the comparison result;

[0035] A first determination module is used to determine a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor;

[0036] The second determination module is used to determine the self-test results of the hardware configuration parameters of the additive manufacturing equipment based on the detection results of the laser configuration parameters and the detection results of the circulating wind sensor configuration parameters.

[0037] In a third aspect, the present invention provides an additive manufacturing device, comprising: a PLC, a laser, a circulating wind sensor and a self-checking device for hardware configuration parameters of the additive manufacturing device of the second aspect.

[0038] In a fourth aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the self-checking method for hardware configuration parameters of the additive manufacturing equipment of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0039] In a fifth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the self-checking method for hardware configuration parameters of an additive manufacturing device according to the first aspect or any corresponding embodiment thereof.

[0040] In a sixth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the self-checking method for hardware configuration parameters of an additive manufacturing device according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 It is a flowchart of a method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention;

[0043] Figure 2 is a flow chart of another method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention;

[0044] Figure 3 is a flow chart of another method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention;

[0045] Figure 4 is a flow chart of another method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention;

[0046] Figure 5 is a schematic diagram of a process flow of a laser quantity parameter self-check according to an embodiment of the present invention;

[0047] Figure 6 is a schematic diagram of a sensor self-test process according to an embodiment of the present invention;

[0048] Figure 7 is a structural block diagram of a self-checking device for hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention;

[0049] Figure 8 is a schematic structural diagram of an additive manufacturing device according to an embodiment of the present invention;

[0050] Fig. 9 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] The basic principle of the SLM additive manufacturing equipment is layer manufacturing, powder spreading layer by layer and laser sintering layer by layer; to improve work efficiency, the number of lasers used in the additive manufacturing equipment is increasing, and the diversification of customer needs has caused the 3D printing equipment of each manufacturer to develop in a step-by-step series; different series of models are generally divided according to the size of the forming cavity, and in the same series of products, the hardware configuration of the equipment will also vary according to customer needs; for the convenience of program management, generally the same set of control programs will be shared, and the control program can be adapted to different hardware differences through parameter configuration. For example, different numbers of lasers can be set as parameters in the machine parameter configuration file.

[0053] The above method has the lowest cost and the best management, but if the parameter configuration is incorrect, it will also bring some serious consequences; taking the number of lasers as an example: Suppose the number of lasers in the parameter configuration file is M, the actual number of lasers installed in the equipment is N, the laser numbers all start from 1, and each laser has a feedback signal X N , then there are the following 3 cases.

[0054] Case P1: M < N, that is, when the number of lasers M set in the parameter configuration file is less than the actual number of lasers N installed in the equipment, the lasers numbered from M + 1 to N will be regarded as non-existent by the program; therefore, the program will not detect whether the feedback signals of the lasers within these numbered ranges are normal. If one or more lasers within these numbered ranges fail during the printing process, the workpiece in the corresponding area will not be correctly sintered, resulting in workpiece scrapping.

[0055] Case P2: M > N, that is, when the number of lasers M set in the parameter configuration file is greater than the actual number of lasers N installed in the equipment, starting from the laser numbered N + 1, all the lasers numbered up to M actually do not exist, but the control program believes that there are lasers within the numbered range, resulting in the control program being unable to read the feedback signals of the lasers in this numbered section, thus causing the lasers to be unable to control the light output normally. At this time, the printing conditions are not met, and the additive manufacturing equipment cannot enter the printing process. In this case, the workpiece will not be scrapped, and the cause of the failure can be found through troubleshooting.

[0056] Case P3: M=N, that is, when the number of lasers M set in the parameter configuration file is equal to the number of lasers N actually installed on the device, the laser parameter configuration corresponds to the actual number of installations, and the parameter configuration is correct; by analyzing the above three cases, it can be obtained that the most important case to avoid is case P1, that is, the number of lasers set in the parameter configuration file is less than the number of lasers actually installed on the device.

[0057] At the same time, SLM additive manufacturing equipment will produce smoke-like black particles during the laser sintering process. During the actual printing process, the circulating air system of the 3D printing device will collect the above black particles into the filter device. If the black particles are not collected in time, it will affect the sintering quality of the corresponding laminated workpiece, and in severe cases, the printed workpiece will be scrapped. The circulating air system is powered by a fan. First, before the printing process, inert gas will be used to replace the air in the closed space of the entire circulation system. Oxygen content sensors are installed in multiple parts of the closed space to measure the oxygen content value in real time. When the oxygen content value drops below the set value, the fan is turned on to circulate the inert gas and take away the black particles generated during sintering in time. The control core of the circulating air system lies in controlling the speed of its power source fan, and the fan speed control must rely on the actual measurement values ​​of various circulating air sensors as the feedback value of the control model. There are three main circulating air sensors: wind speed sensor, air volume sensor and wind pressure sensor. For models in the same series that are equipped with different sensor types and need to adapt to the same set of programs, there will be a circulating air sensor type parameter. If the circulating air sensor type parameter is configured incorrectly, printing errors will also occur.

[0058] In order to solve the above technical problems, an embodiment of the present invention provides a self-check method for the hardware configuration parameters of additive manufacturing equipment. The method confirms the quantity after the laser is powered on and compares it with the laser configuration parameters. If they match, after the circulating wind sensor is powered on, the sampling value of the PLC (Programmable Logic Controller) analog channel is compared with the disconnection judgment value to determine the disconnection situation, and finally the hardware parameter configuration detection result is obtained, thereby avoiding the consequences of possible scrapping of printed workpieces due to negligent mismatching or missing parameters during manual configuration. At the same time, when a hardware parameter configuration error is detected, the program automatically alarms and prompts, which can reduce the parameter configuration work pressure of the operator and avoid the corresponding losses caused by configuration errors. It is more friendly to equipment users and is also in line with the research direction of equipment intelligence.

[0059] According to an embodiment of the present invention, an embodiment of a self-checking method for hardware configuration parameters of an additive manufacturing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0060] In this embodiment, a method for self-checking hardware configuration parameters of an additive manufacturing device is provided, which can be used for additive manufacturing devices. Figure 1 is a flow chart of a method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0061] Step S101 , after the lasers are powered on, the laser feedback signals are read one by one, and the number of lasers is determined based on the laser feedback signals.

[0062] Specifically, before reading the laser feedback signals one by one, it is necessary to ensure that all laser feedback signals have been connected to the PLC of the 3D printing device. Assuming that the number of lasers is N, the PLC input signals (i.e., laser feedback signals) corresponding to the lasers numbered from 1 to N are X 1 To X N Among them, whether the feedback signal of the laser is normal or not can be reflected in the judgment of high and low level signals, and this level signal can be detected by PLC.

[0063] Furthermore, the PLC collects the feedback signal of the laser through a special input module, and the input module can convert the analog signal or digital signal into a digital quantity that the PLC can process; the PLC processes the collected laser feedback signal, such as filtering, amplifying, normalizing, etc., to eliminate noise interference and improve the accuracy and stability of the signal.

[0064] Step S102, obtaining laser configuration parameters, comparing the number of lasers with the laser configuration parameters, and obtaining laser configuration parameter detection results.

[0065] Specifically, if the value of the number of lasers N is not equal to the value of the laser configuration parameter M, an alarm will be issued to indicate that the number of lasers is configured incorrectly; if the value of the number of lasers N is equal to the value of the laser configuration parameter M, the sensor type judgment link will be entered.

[0066] Step S103, after the circulating wind sensor is powered on, the sampling values ​​of the PLC analog channels and the sensor type configuration parameters are read one by one.

[0067] Specifically, the circulating wind sensor includes a wind speed sensor, an air volume sensor and a wind pressure sensor. After determining that the number of lasers is equal to the laser configuration parameters, it is necessary to ensure that the above three types of circulating wind sensors are connected to different analog quantity acquisition channels of the PLC as required. It is assumed that the wind speed sensor is connected to the CH1 channel, the air volume sensor is connected to the CH2 channel, and the wind pressure sensor is connected to the CH3 channel.

[0068] Specifically, the circulating wind sensor uses a 4-20mA current signal, and may also use other current signal ranges or a voltage signal, which is not limited in the embodiments of the present application.

[0069] Specifically, the analog quantity acquisition channel is composed of an analog quantity input interface, a sampling and holding circuit, and an analog-to-digital converter; the analog quantity signal first enters the acquisition channel through the analog quantity input interface, the sampling and holding circuit samples the input analog quantity signal, and keeps the signal stable during the analog-to-digital conversion process, and then the analog quantity signal is converted into a digital quantity signal by the analog-to-digital converter, and finally the digital quantity signal is transmitted to the central processing unit of the PLC for processing.

[0070] Step S104, obtaining a disconnection judgment value, comparing the sampling value of the PLC analog channel with the disconnection judgment value, and determining a disconnection mark value of the circulating wind sensor based on the comparison result.

[0071] Specifically, when the 4-20mA circulating wind sensor is not disconnected and has no signal input, the collected current value is 4mA. If the circulating wind sensor is disconnected, the collected current value is about 0mA. If the value collected by the circulating wind sensor is around 0mA, it is considered that the circulating wind sensor is abnormal or disconnected.

[0072] Furthermore, the disconnection flag value is a Boolean type variable, which is set to true (True, or 1), otherwise it is set to false (False, or 0).

[0073] Step S105 : determining a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor.

[0074] Step S106, determining the self-test result of the hardware configuration parameters of the additive manufacturing equipment based on the detection result of the laser configuration parameters and the detection result of the circulating wind sensor configuration parameters.

[0075] The self-check method of the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment reads the laser feedback signals one by one after the laser is powered on, determines the number of lasers based on the laser feedback signals; obtains the laser configuration parameters, compares the number of lasers with the laser configuration parameters, and obtains the laser configuration parameter detection results; after the circulating air sensor is powered on, reads the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one; obtains the disconnection judgment value, compares the sampling value of the PLC analog channel with the disconnection judgment value, and determines the disconnection mark value of the circulating air sensor based on the comparison result; and determines the disconnection mark value of the circulating air sensor based on the sensor type configuration parameter. The circulating wind sensor configuration parameter detection result is determined based on the laser configuration parameter detection result and the circulating wind sensor configuration parameter detection result; the self-test result of the additive manufacturing equipment hardware configuration parameter is determined based on the laser configuration parameter detection result and the circulating wind sensor configuration parameter detection result; by self-checking the laser quantity parameter and the circulating wind sensor type parameter, the consequence of the possible scrapping of the printed workpiece due to negligent mismatch or missing parameters during manual configuration is avoided, the parameter configuration work pressure of the operator is reduced, the corresponding losses caused by configuration errors are avoided, the operating difficulty of the additive manufacturing equipment users is reduced, and the intelligence of the additive manufacturing equipment is improved.

[0076] In this embodiment, a method for self-checking hardware configuration parameters of an additive manufacturing device is provided, which can be used for additive manufacturing devices. Figure 2 is a flow chart of a method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0077] Step S201 , after the lasers are powered on, the laser feedback signals are read one by one, and the number of lasers is determined based on the laser feedback signals.

[0078] Specifically, the above step S201 includes:

[0079] Step S2011, setting the initial value of the number of lasers to zero.

[0080] Specifically, after the power is turned on and the laser is powered on, a laser feedback signal is read and an initial value of the laser quantity N is set to zero.

[0081] Step S2012, if the laser feedback signal is at a high level, then the initial value of the number of lasers is increased by one; if the laser feedback signal is at a low level, then the level state of the next laser feedback signal is determined until the laser feedback signals are traversed to obtain the number of lasers.

[0082] Specifically, the feedback signal X from the laser 1At the beginning, the level state of the laser feedback signal is judged one by one. If the laser feedback signal is high level, the laser feedback signal X value is 1, and the laser quantity N value is increased by 1; if the laser feedback signal is low level, the laser feedback signal X value is 0, and the laser quantity N value remains unchanged; the level state of the next laser feedback signal is judged according to the above method until the laser feedback signal X value is traversed. N After that, the judgment is completed and the value of the number of lasers N is obtained.

[0083] Furthermore, the condition for adding 1 to the initial value of the number of lasers needs to be determined according to the type of the detected laser feedback signal. For some types of feedback signals, it can also be set to add 1 when the level is low and remain unchanged when the level is high.

[0084] Step S202, obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain the laser configuration parameter detection result. Figure 1 Step S102 of the illustrated embodiment will not be described in detail here.

[0085] Step S203, after the circulating air sensor is powered on, read the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0086] Step S204, obtain the disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine the disconnection mark value of the circulating air sensor based on the comparison result. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0087] Step S205: Determine the circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor. Figure 1 Step S105 of the illustrated embodiment will not be described in detail here.

[0088] Step S206, based on the laser configuration parameter detection results and the circulating wind sensor configuration parameter detection results, determine the self-test results of the additive manufacturing equipment hardware configuration parameters. Figure 1 Step S106 of the illustrated embodiment will not be described in detail here.

[0089] The self-checking method of the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment sets the initial value of the number of lasers, and traverses all laser feedback signals according to the level status of the feedback signals to obtain the total number of lasers, thereby realizing the one-by-one detection of the laser level status, and laying a foundation for the self-checking of the laser number configuration parameters.

[0090] In this embodiment, a method for self-checking hardware configuration parameters of an additive manufacturing device is provided, which can be used for additive manufacturing devices. Figure 3 is a flow chart of a method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0091] Step S301, after the laser is powered on, read the laser feedback signals one by one, and determine the number of lasers based on the laser feedback signals. Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0092] Step S302, obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain the laser configuration parameter detection result. Figure 2 Step S202 of the illustrated embodiment will not be described in detail here.

[0093] Step S303: After the circulating wind sensor is powered on, the sampling values ​​of the PLC analog channels and the sensor type configuration parameters are read one by one. Figure 2 Step S203 of the illustrated embodiment will not be described in detail here.

[0094] Step S304, obtaining a disconnection judgment value, comparing the sampling value of the PLC analog channel with the disconnection judgment value, and determining a disconnection mark value of the circulating wind sensor based on the comparison result.

[0095] Specifically, the above step S304 includes:

[0096] Step S3041, if the sampling value of the PLC analog channel is less than the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to true; wherein the circulating wind sensor is connected to the PLC analog channel in a one-to-one correspondence.

[0097] Specifically, there is a linear correspondence between the current value collected by the PLC controller and the digital value, and the linear correspondence is determined according to the hardware configuration parameters of the analog channel. For example, the current value collected by the PLC controller is 0-20mA, and the corresponding digital value is 0-32000. The expression of the correspondence between the current value collected by the PLC controller and the digital value is:

[0098] Y=(32000-0) / (20-0)*(Z-0)+0=1600*Z (1)

[0099] Among them, Z represents the current value, and Y represents the digital value. When Z is 4mA, the corresponding Y is 6400. If Z selects a current value near 0mA, the corresponding Y also selects a digital value near 0. Therefore, if Y is 0, it means that the sensor is disconnected. In actual applications, considering the fluctuation of analog sampling values, a disconnection judgment value slightly greater than 0 will be selected for comparison with the analog sampling value. For example, the Bk value can be set to 100. For other hardware configuration parameters, corresponding disconnection judgment values ​​can also be set.

[0100] Step S3042, or, if the sampling value of the PLC analog channel is greater than or equal to the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to false.

[0101] Specifically, after the power is turned on and the circulating wind sensor is powered on, the sampling values ​​of the CH1, CH2 and CH3 analog channels are read respectively. If the sampling value of the CH1 analog channel is less than the disconnection judgment value Bk, the disconnection mark value of the wind speed sensor is set to true, otherwise the disconnection mark value of the wind speed sensor is set to false; if the sampling value of the CH2 analog channel is less than the disconnection judgment value Bk, the disconnection mark value of the wind volume sensor is set to true, otherwise the disconnection mark value of the wind speed sensor is set to false; if the sampling value of the CH3 analog channel is less than the disconnection judgment value Bk, the disconnection mark value of the wind pressure sensor is set to true, otherwise the disconnection mark value of the wind speed sensor is set to false.

[0102] Step S305: Determine the circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor. Figure 2 Step S205 of the illustrated embodiment will not be described in detail here.

[0103] Step S306: Determine the self-test result of the hardware configuration parameters of the additive manufacturing equipment based on the detection results of the laser configuration parameters and the detection results of the circulating wind sensor configuration parameters. Figure 2 Step S206 of the illustrated embodiment will not be described in detail here.

[0104] The self-check method for the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment realizes the setting of the circulating wind sensor disconnection mark value by comparing the sampling value of the PLC analog channel and the disconnection judgment value, thereby laying a foundation for the detection of the circulating wind sensor configuration parameters.

[0105] In this embodiment, a method for self-checking hardware configuration parameters of an additive manufacturing device is provided, which can be used for additive manufacturing devices. Figure 4 is a flow chart of a method for self-checking hardware configuration parameters of an additive manufacturing device according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0106] Step S401, after the laser is powered on, read the laser feedback signals one by one, and determine the number of lasers based on the laser feedback signals. Figure 3 Step S301 of the illustrated embodiment will not be described in detail here.

[0107] Step S402, obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain the laser configuration parameter detection result. Figure 3 Step S302 of the illustrated embodiment will not be described in detail here.

[0108] Step S403: After the circulating wind sensor is powered on, the sampling values ​​of the PLC analog channels and the sensor type configuration parameters are read one by one. Figure 3 Step S303 of the illustrated embodiment will not be described in detail here.

[0109] Step S404, obtain the disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine the disconnection mark value of the circulating air sensor based on the comparison result. Figure 3 Step S304 of the illustrated embodiment will not be described in detail here.

[0110] Step S405 : determining a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor.

[0111] Specifically, the above step S405 includes:

[0112] Step S4051, determining the circulating wind sensor type based on the sensor type configuration parameter; the circulating wind sensor type includes a wind speed sensor, an air volume sensor, and a wind pressure sensor.

[0113] Specifically, the circulating wind sensor type is determined according to the read circulating wind sensor type parameter W. Assume that W=1 indicates the use of a wind pressure sensor, W=2 indicates the use of a wind speed sensor, and W=3 indicates the use of a wind volume sensor. Each additive manufacturing device will only use one circulating wind sensor, so the W value must correspond to one sensor type.

[0114] Step S4052: comparing the disconnection mark value of the circulating wind sensor based on the circulating wind sensor type, and determining the circulating wind sensor configuration parameter detection result based on the comparison result.

[0115] In some optional implementations, the above step S4052 includes:

[0116] Step a1, matching the circulating wind sensor type with the disconnection mark value of the circulating wind sensor.

[0117] Step a2: If the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is true, the circulating wind sensor configuration parameter detection result is a sensor configuration error alarm.

[0118] Step a3, or, if the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is false, the circulating wind sensor configuration parameter detection result is that the sensor configuration is correct.

[0119] Specifically, the broken line mark value of the corresponding circulating wind sensor type is compared according to the parsed circulating wind sensor type. If the broken line mark value is true, the corresponding circulating wind sensor type is configured incorrectly. At this time, the circulating wind sensor configuration parameter detection result of the sensor configuration error alarm is output. If the broken line mark value is false, it means that the sensor configuration is correct and no alarm is given.

[0120] Step S406: Determine the self-test result of the hardware configuration parameters of the additive manufacturing equipment based on the laser configuration parameter test results and the circulating wind sensor configuration parameter test results. Figure 3 Step S306 of the illustrated embodiment will not be described in detail here.

[0121] The self-checking method for the hardware configuration parameters of the additive manufacturing equipment provided in this embodiment determines the circulating wind sensor type through the sensor type configuration parameters, and determines the circulating wind sensor configuration parameter detection result using the broken line mark value of the circulating wind sensor and the circulating wind sensor type, thereby achieving accurate judgment on the circulating wind sensor type and connection status, and avoiding the consequences of possible scrapping of printed workpieces due to negligent mismatching or missing parameters during manual configuration; by automatically issuing an alarm prompt when a sensor configuration error is detected, the parameter configuration work pressure of the operator is reduced, the corresponding losses caused by the configuration error are avoided, the operating difficulty of the additive manufacturing equipment users is reduced, and the intelligence of the additive manufacturing equipment is improved.

[0122] The following is a specific example to illustrate the specific steps of a method for self-checking hardware configuration parameters of an additive manufacturing device.

[0123] Embodiment 1:

[0124] The maximum number of lasers selected for a certain model is L_Max. For example, L_Max is 10. In practice, there are five configurations of laser quantity: 2, 4, 6, 8, and 10. The feedback signal of the laser is X 1 To X 10 , the laser configuration parameter is Set_N, and the actual number of lasers Act_N can be obtained by detecting the laser feedback signal. The detected number of lasers Act_N is compared with the laser configuration parameter Set_N. If the comparison is inconsistent, a laser number configuration error is reported.

[0125] like Figure 5 As shown, the self-checking method of the laser quantity parameter in the self-checking method of the hardware configuration parameters of the additive manufacturing equipment includes the following steps:

[0126] S10, after the additive manufacturing equipment is turned on, all lasers are controlled to be powered on, and the value of the number of lasers Act_N is set to 0 in the program;

[0127] S11, read the laser feedback signal X one by one starting from 1 i , if X i If it is high level, the value of laser quantity Act_N will increase by 1. If it is low level, the value of laser quantity Act_N will remain unchanged. After completion, the value of laser quantity Act_N can be obtained.

[0128] S12, comparing the obtained laser quantity Act_N value with the laser configuration parameter Set_N, if the Act_N value is not equal to the laser configuration parameter Set_N, executing a laser quantity configuration error alarm; if the laser quantity Act_N value is equal to the laser configuration parameter Set_N, no alarm is issued.

[0129] like Figure 6 As shown, after the self-check of the laser quantity parameter, the sensor type self-check is performed. The sensor type self-check method includes the following steps:

[0130] S20, control the sensor to power on after powering on;

[0131] S21, read the sampling value of analog channel 1, if the sampling value of analog channel 1 is less than the disconnection value (i.e., disconnection judgment value), assign the disconnection mark value of the wind speed sensor to 1, otherwise assign it to 0;

[0132] S22, read the sampling value of analog channel 2. If the sampling value of analog channel 2 is less than the disconnection value, assign the disconnection mark value of the air volume sensor to 1, otherwise assign it to 0;

[0133] S23, read the sampling value of analog channel 3, if the sampling value of analog channel 3 is less than the disconnection value, assign the disconnection mark value of the wind pressure sensor to 1, otherwise assign it to 0;

[0134] S24, reading and interpreting the sensor type configuration parameter W, for example, when W=1, it indicates that a wind pressure sensor is used; when W=2, it indicates that a wind speed sensor is used; when W=3, it indicates that a wind volume sensor is used;

[0135] S25. Compare the broken wire mark of the corresponding circulating wind sensor according to the interpreted sensor type configuration parameter W. If the broken wire mark value is 1, it means that the sensor type configuration parameter is wrong, and a sensor configuration error alarm is given. If the broken wire mark value is 0, it means that the configuration is correct, no alarm is given, and the process ends.

[0136] In this embodiment, a self-checking device for the hardware configuration parameters of an additive manufacturing device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated hereafter. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0137] This embodiment provides a self-checking device for hardware configuration parameters of an additive manufacturing device, such as Figure 7 As shown, including:

[0138] The first reading module 701 is used to read the laser feedback signals one by one after the lasers are powered on, and determine the number of lasers based on the laser feedback signals.

[0139] The first comparison module 702 is used to obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain a laser configuration parameter detection result.

[0140] The second reading module 703 is used to read the sampling values ​​and sensor type configuration parameters of the PLC analog channels one by one after the circulating wind sensor is powered on.

[0141] The second comparison module 704 is used to obtain a disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine the disconnection mark value of the circulating wind sensor based on the comparison result.

[0142] The first determination module 705 is used to determine the circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor.

[0143] The second determination module 706 is used to determine the self-test result of the hardware configuration parameters of the additive manufacturing equipment based on the detection result of the laser configuration parameters and the detection result of the circulating wind sensor configuration parameters.

[0144] In some optional implementations, the first reading module 701 includes:

[0145] The first setting unit is used to set the initial value of the number of lasers to zero.

[0146] The judgment unit is used to increase the initial value of the number of lasers by one if the laser feedback signal is at a high level, and to judge the level state of the next laser feedback signal if the laser feedback signal is at a low level, until the laser feedback signals are traversed to obtain the number of lasers.

[0147] In some optional implementations, the second comparison module 704 includes:

[0148] The second setting unit is used to set the disconnection mark value of the circulating wind sensor to one if the sampling value of the PLC analog channel is less than the disconnection judgment value; wherein the circulating wind sensor is connected to the PLC analog channel in a one-to-one correspondence.

[0149] The third setting unit is used to set the disconnection mark value of the circulating wind sensor to zero if the sampling value of the PLC analog channel is greater than or equal to the disconnection judgment value.

[0150] In some optional implementations, the determination module 705 includes:

[0151] The determination unit is used to determine the circulating wind sensor type based on the sensor type configuration parameter; the circulating wind sensor type includes a wind speed sensor, an air volume sensor and a wind pressure sensor.

[0152] The comparison unit compares the disconnection mark value of the circulating wind sensor based on the type of the circulating wind sensor, and determines the detection result of the circulating wind sensor configuration parameter based on the comparison result.

[0153] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0154] The self-checking device of the hardware configuration parameters of the additive manufacturing equipment in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0155] The embodiment of the present invention also provides an additive manufacturing device, such as Figure 8 As shown, it includes PLC801, laser 802, circulating wind sensor 803 and the above Figure 7 The self-checking device 804 of the hardware configuration parameters of the additive manufacturing equipment is shown; wherein, PLC801 is connected to the laser 802 and the circulating wind sensor 803 respectively, that is, the laser feedback signals are all connected to the PLC, and the circulating wind sensor is connected to different analog quantity acquisition channels of the PLC as required; the self-checking device 804 of the hardware configuration parameters of the additive manufacturing equipment is connected to PLC801.

[0156] The embodiment of the present invention also provides a computer device having the above Figure 7 The self-checking device of the hardware configuration parameters of the additive manufacturing equipment is shown.

[0157] See also Fig. 9 , Fig. 9 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig. 9 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig. 9 A processor 10 is taken as an example.

[0158] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0159] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0160] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0161] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0162] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Fig. 9 The example of connecting through bus is taken in the following.

[0163] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0164] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0165] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0166] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for self-checking hardware configuration parameters of additive manufacturing equipment, characterized in that: The method comprises: After the lasers are powered on, the laser feedback signals are read one by one, and the number of lasers is determined based on the laser feedback signals; Acquire laser configuration parameters, compare the laser quantity with the laser configuration parameters, and obtain laser configuration parameter detection results; After the circulating air sensor is powered on, read the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one; Obtaining a disconnection judgment value, comparing the sampling value of the PLC analog channel with the disconnection judgment value, and determining a disconnection mark value of the circulating air sensor based on the comparison result; Determine a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and a disconnection flag value of the circulating wind sensor; A self-test result of the hardware configuration parameters of the additive manufacturing equipment is determined based on the laser configuration parameter detection result and the circulating wind sensor configuration parameter detection result.

2. The method according to claim 1, characterized in that The step of reading the laser feedback signals one by one after the lasers are powered on, and determining the number of lasers based on the laser feedback signals, comprises: Set the initial value of the number of lasers to zero; If the laser feedback signal is at a high level, the initial value of the number of lasers is increased by one; if the laser feedback signal is at a low level, the level state of the next laser feedback signal is determined until the laser feedback signals are traversed to obtain the number of lasers.

3. The method according to claim 1, characterized in that The comparing the sampling value of the PLC analog channel with the disconnection judgment value, and determining the disconnection mark value of the circulating wind sensor based on the comparison result, comprises: If the sampling value of the PLC analog channel is less than the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to true; wherein the circulating wind sensor is connected to the PLC analog channel in a one-to-one correspondence; Alternatively, if the sampling value of the PLC analog channel is greater than or equal to the disconnection judgment value, the disconnection mark value of the circulating wind sensor is set to false.

4. The method according to claim 1, characterized in that: The determining of the circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and the disconnection mark value of the circulating wind sensor includes: Determine the circulating wind sensor type based on the sensor type configuration parameter; the circulating wind sensor type includes a wind speed sensor, an air volume sensor and a wind pressure sensor; The disconnection mark value of the circulating wind sensor is compared based on the circulating wind sensor type, and the circulating wind sensor configuration parameter detection result is determined based on the comparison result.

5. The method according to claim 4, characterized in that The comparing the disconnection mark value of the circulating wind sensor based on the type of the circulating wind sensor, and determining the circulating wind sensor configuration parameter detection result based on the comparison result, includes: Matching the circulating wind sensor type with the disconnection flag value of the circulating wind sensor; If the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is true, the circulating wind sensor configuration parameter detection result is a sensor configuration error alarm; Alternatively, if the disconnection flag value of the circulating wind sensor corresponding to the circulating wind sensor type is false, the circulating wind sensor configuration parameter detection result is that the sensor configuration is correct.

6. A self-checking device for hardware configuration parameters of additive manufacturing equipment, characterized in that: The device comprises: A first reading module, used for reading laser feedback signals one by one after the lasers are powered on, and determining the number of lasers based on the laser feedback signals; A first comparison module is used to obtain laser configuration parameters, compare the number of lasers with the laser configuration parameters, and obtain a laser configuration parameter detection result; The second reading module is used to read the sampling values ​​of the PLC analog channels and the sensor type configuration parameters one by one after the circulating wind sensor is powered on; A second comparison module is used to obtain a disconnection judgment value, compare the sampling value of the PLC analog channel with the disconnection judgment value, and determine a disconnection mark value of the circulating air sensor based on the comparison result; A first determination module, configured to determine a circulating wind sensor configuration parameter detection result based on the sensor type configuration parameter and a disconnection mark value of the circulating wind sensor; The second determination module is used to determine the self-test result of the hardware configuration parameters of the additive manufacturing equipment based on the detection result of the laser configuration parameters and the detection result of the circulating wind sensor configuration parameters.

7. An additive manufacturing device, characterized in that: include: PLC, laser, circulating wind sensor and a self-checking device for hardware configuration parameters of the additive manufacturing equipment as claimed in claim 6.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the self-checking method for hardware configuration parameters of the additive manufacturing equipment according to any one of claims 1 to 5 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the self-checking method for hardware configuration parameters of an additive manufacturing device according to any one of claims 1 to 5.

10. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions are used to cause a computer to execute the self-checking method of hardware configuration parameters of an additive manufacturing device according to any one of claims 1 to 5.

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