A method for automatic allocation of spacecraft telemetry and telecommand information channels based on cable complexity evaluation algorithm

Abstract

The application discloses a kind of based on cable complexity evaluation algorithm's spacecraft telemetry remote control information channel automatic distribution method, the method includes two steps of channel automatic identification, channel intelligent distribution: channel automatic identification: according to telemetry signal definition, remote control signal definition, connector contact interface definition three parts of data, the corresponding relationship between data is obtained by "signal number"; according to the corresponding relationship, the connector condition is identified and marked; the nature of channel is identified again, and different properties are automatically divided into various channels; channel intelligent distribution: obtain all current resources and load channels and its belonging connector and cable, by the automatic collocation of load and resource combination, the change of cable is analyzed, and the collocation scheme with the lowest cable complexity is automatically obtained to automatically distribute.

Description

Technical Field

[0001] This invention belongs to the technical field of cable network design in spacecraft electrical system engineering, specifically relating to a method for automatic allocation of spacecraft telemetry and remote control information channels based on a cable complexity evaluation algorithm, applicable to the allocation process of telemetry and remote control information channels in cable network design for spacecraft electrical system engineering. Background Technology

[0002] The general principle for allocating telemetry and remote control signal channels is to distribute the entire load to the resource end. However, because telemetry and remote control signals share connectors with other signals, the randomness of cable generation is relatively high, making it difficult to ensure the rationality of the allocation. This irrationality is mainly reflected in the complexity of the final cable, easily resulting in hundreds of connectors on a single cable. The primary reason for this is the lack of effective design support tools for telemetry and remote control channel allocation, which currently relies entirely on manual allocation.

[0003] Currently, information technology is being used to design equipment, connectors, and cables in spacecraft cable networks. For example, patent application 201710395737.1 discloses a three-dimensional design system and method for spacecraft cable networks. This system completely separates the design of the cable network channels from the specific wiring design of each cable bundle. It uses the cable network channels as the "paths" for the cables, and the premise that cables can only pass through the network channels, as the basic starting point. This serves as the unified path basis for subsequent wiring designs of each cable bundle, enabling the specific wiring design of each bundle. This not only provides a unified top-level planning, design process, and design tools for the entire spacecraft's cable network channels, but also provides a unified basis and constraints for the parallel and collaborative design of each cable bundle's wiring. This reduces iterative iterations and modifications during collaborative design, simplifies the design process and steps, and improves design efficiency.

[0004] For example, patent application 202110859389.5 discloses an autonomous optimization design method for spacecraft cable networks. The method includes: S1, obtaining a three-dimensional pre-assembled model of the spacecraft cable network; S2, standardizing the wiring components in the three-dimensional pre-assembled model; S3, extracting the reference information of all wiring components from the three-dimensional pre-assembled model into the cable skeleton model; S4, creating common paths for the cable network based on the reference information of the wiring components in the cable skeleton model; S5, importing a cable connection relationship table; S6, selecting an optimal path for each cable connection relationship in the common paths of the cable network, using the branch order in the cable connection relationship table as an index; S7, generating solid models of each cable branch based on the results of step S6 and the cable gauge; and S8, obtaining cable length, weight, and branch length diagrams from the cable solid models and outputting them in a standardized format.

[0005] However, the aforementioned patent application did not establish direct connections based on connector docking by analyzing all signals from both resource and load ends. This prevented dynamic analysis of resource and load changes during channel allocation, and also hindered analysis of the impact of channel allocation on the complexity of existing cables. These two indicators directly affect the rationality and efficiency of telemetry and remote control channel allocation. The lack of these methods makes it highly susceptible to cable merging and cross-contamination, resulting in complex cables that are difficult to manufacture and install. Furthermore, directly generating connections necessitates redesigning them, which requires significant work. The complex cables must be further broken down into smaller cables using transition connectors, increasing design overhead, cable costs, and aircraft weight.

[0006] Therefore, cable network design must be carried out rationally from a holistic perspective, and the rationality of telemetry and remote control channel allocation is crucial, while the design methodology urgently needs optimization. Summary of the Invention

[0007] To address the aforementioned problems, the primary objective of this invention is to provide a method for automatic allocation of spacecraft telemetry and remote control information channels based on a cable complexity assessment algorithm. This method uses information technology to achieve automatic identification and intelligent allocation of spacecraft telemetry and remote control channels, thereby accurately and efficiently completing channel design tasks while reducing cable complexity.

[0008] Another objective of this invention is to provide a method for automatic allocation of spacecraft telemetry and remote control information channels based on a cable complexity evaluation algorithm. The intelligent channel allocation algorithm applied in this method cleverly utilizes and improves the bin packing algorithm, combines sorting, comparison, and looping procedures, and effectively integrates with electrical design.

[0009] To achieve the above objectives, the technical solution of the present invention is as follows.

[0010] A method for automatic allocation of spacecraft telemetry and remote control information channels based on a cable complexity evaluation algorithm, comprising two steps: automatic channel identification and intelligent channel allocation.

[0011] 1. Automatic Channel Identification: Based on the definitions of telemetry signals, remote control signals, and connector contact interfaces, the system obtains the correspondence between the data through "signal numbers." According to the correspondence, it identifies and marks the connector's "load" or "resource" status. Then, it identifies the channel's nature and automatically classifies it into different types of channels (several contacts form a channel), displaying the number of each type of channel for all load and resource connectors in a visual format. If the number of load channels exceeds the number of resource channels, a prompt is given.

[0012] 2. Intelligent Channel Allocation: Obtain all current resource and load channels, as well as their associated connectors and cables. Through automatic matching of load and resource combinations, analyze cable changes, and automatically obtain the matching scheme with the lowest cable complexity for automatic allocation.

[0013] Furthermore, in the automatic channel identification step, if the load end contact has clearly defined the signal and return line grouping, a channel is directly generated; if the return line has not been assigned, a channel is assigned according to the following rules:

[0014] The rules for the telemetry channel are as follows:

[0015] AN / BL: 4 signals per return line; if the resource end allocates less than 4 pins, the remaining pins will be allocated as one return line.

[0016] TH: One signal and one return line;

[0017] Remote control channels: one return line per device;

[0018] Doo: Direct access;

[0019] Roo: Indirect channel;

[0020] Successfully identified channels are displayed visually, including the number of channels for all loads and resource connectors. If the number of load channels exceeds the number of resource channels, a prompt will be given.

[0021] Furthermore, the intelligent channel allocation process specifically includes the following steps:

[0022] Step 1: Create a table showing the resource and load characteristics of different equipment in each cabin;

[0023] Step 2: Based on the keyword definition, visualize and uniformly number and display the load, resources, and channel quantity of different equipment in each cabin in a matrix, forming load groups and resource groups respectively. The objects in each group are clearly marked with cabin and equipment numbers, labeled as RmLm and RnSn.

[0024] Step 3: Determine if the total number of all resource channels is greater than the total number of load channels. If the number of load channels is greater than the number of resource channels, indicate insufficient resources and please investigate. Otherwise, proceed to Step 4.

[0025] Step 4: Sort the loads RLm in descending order from largest to smallest, and define them as array RL[m]. Sort the resources RSn in ascending order from smallest to largest, and define them as array RS[n]. m and n are the number of loads and resources, respectively.

[0026] Step 5: After sorting, RL[0]>RL[1]>…>RL[m-2]>RL[m-1], RS[0] <RS[1]<…<RS[n-2]> RS[n-1], the program records each load number RL[m] and resource number RS[n];

[0027] Step 6: Iterate through RL[i] (0≤i≤m-1) and compare it with RS[j] (0≤j≤n-1) in turn; if RL[i]≤RS[n-1], execute step 7.1; if RL[i]>RS[n-1], execute step 7.2.

[0028] Step 7.1: Find the smallest value RS[j] that is greater than RL[i], and perform the following operation:

[0029] 7.1.1 Establish the connection between RS[i] and RS[j];

[0030] 7.1.2, Update the resource count of RS[j] = RS[j] - RL[i];

[0031] 7.1.3 Reorder RS[j] and update the array number corresponding to the RS[j] resource.

[0032] 7.1.4 After incrementing i by 1, check if i ≤ m - 1 and return to step 6. If i > m, jump to End.

[0033] Step 7.2: Split the load RL[i], as follows:

[0034] 7.2.1 Establish the connection between RL[i] and RS[n-1];

[0035] 7.2.2, Update the load count of RL[i] = RL[i] - RS[n-1];

[0036] 7.2.3, clear i to zero, reorder RL[i], update the array number corresponding to the RL[i] resource, and return to step 6;

[0037] End:

[0038] All loads were summarized, and a complete resource-load interconnection topology was established.

[0039] The channel is automatically allocated, and the current number of branches is relatively advantageous in terms of feasibility and program complexity.

[0040] The beneficial effects of this invention are:

[0041] 1. It can automatically identify channels and intelligently allocate channels, thus fundamentally eliminating design omissions and errors through automatic allocation;

[0042] 2. By automatically matching load and resource combinations, the efficiency of allocation design can be greatly improved;

[0043] 3. It can automatically obtain the lowest cable complexity matching scheme and automatically allocate it, which can effectively reduce the complexity of the cable. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the channel allocation interface implemented in this invention.

[0045] Figure 2 This is a flowchart of the intelligent channel allocation algorithm implemented in this invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0047] Combination Figure 1 , Figure 2 As shown, the method implemented by this invention includes two steps: automatic channel identification and intelligent channel allocation.

[0048] 1. Automatic Channel Identification: Based on the definitions of telemetry signals, remote control signals, and connector contact interfaces, the system obtains the correspondence between the data through "signal numbers." According to the correspondence, it identifies and marks the connector's "load" or "resource" status. Then, it identifies the channel's nature and automatically classifies it into different types of channels (several contacts form a channel), displaying the number of each type of channel for all load and resource connectors in a visual format. If the number of load channels exceeds the number of resource channels, a prompt is given.

[0049] 2. Intelligent Channel Allocation: Obtain all current resource and load channels, as well as their associated connectors and cables. Through automatic matching of load and resource combinations, analyze cable changes, and automatically obtain the matching scheme with the lowest cable complexity for automatic allocation.

[0050] The specific implementation steps are as follows:

[0051] 1. Automatic channel identification: according to Figure 2Step 1: Based on the three parts of data—telemetry signal definition, remote control signal definition, and connector contact interface definition—create resource and load characteristic tables for each compartment. Obtain the correspondence between data using "signal numbers." If a connector interface definition matches either the telemetry signal definition or the remote control signal definition, the connector to which it belongs is a "load"; otherwise, it is a "resource." Then, based on the signal type, divide the data into telemetry channels and remote control channels. If the load-side contacts have clearly defined signal and return line groupings, directly generate one channel. If the return line is not assigned, allocate channels according to the following rules: (A telemetry channel typically consists of several signal lines and one return line; a remote control channel typically has one connector and one return line.) The rules are as follows:

[0052] Telemetry channel:

[0053] AN / BL: 4 signals per return line; (If the resource end allocates less than 4 pins, the remaining pins will be allocated as one return line)

[0054] TH: One signal and one return line;

[0055] Remote control channel (one return line per device)

[0056] Doo: Direct Path (usually 2 contacts per signal)

[0057] Roo: Indirect Channel

[0058] Successfully identified channels are displayed visually, including the number of various channels for all loads and resource connectors. If the number of load channels exceeds the number of resource channels, a notification will be given. Figure 1 As shown.

[0059] 2. Intelligent channel allocation:

[0060] 1) Algorithm such as Figure 2 As shown, starting from step 2: visualize and uniformly number and display the load, resources, and channel quantity of different equipment in each cabin in a matrix, forming load groups and resource groups respectively. The objects in each group are clearly marked with cabin and equipment numbers, labeled as RmLm and RnSn.

[0061] 2) Step 3: Determine if the total number of all resource channels is greater than the total number of load channels. If the number of load channels exceeds the number of resource channels, indicate insufficient resources and please investigate. Figure 1 As shown, otherwise proceed to step 4;

[0062] 3) Step 4: Sort the load RLm in descending order from largest to smallest, and define it as array RL[m]. Sort the resources RSn in ascending order from smallest to largest, and define it as array RS[n]. m and n are the number of loads and resources, respectively.

[0063] 4) Step 5: After sorting, RL[0]>RL[1]>…>RL[m-2]>RL[m-1], RS[0] <RS[1]<…<RS[n-2]> RS[n-1], the program records each load cell.

[0064] The resource number RL[m] and the resource number RS[n];

[0065] 5) Step 6: Iterate through RL[i] (0≤i≤m-1) and compare it with RS[j] (0≤j≤n-1) in turn. If RL[i]≤RS[n-1], execute step 7.1; if RL[i]>RS[n-1], execute step 7.2.

[0066] 6) Step 7.1: Find the smallest value RS[j] that is greater than RL[i], and perform the following operation:

[0067] ① Establish the connection between RS[i] and RS[j];

[0068] ② Update the resource count of RS[j] = RS[j] - RL[i];

[0069] ③ Reorder RS[j] and update the array number corresponding to the RS[j] resource.

[0070] ④ After incrementing i by 1, check if i ≤ m - 1 and return to step 6. If i > m, jump to End.

[0071] 7) Step 7.2: Split the load RL[i], the operation is as follows:

[0072] ① Establish the connection relationship between RL[i] and RS[n-1];

[0073] ② Update the load count of RL[i] = RL[i] - RS[n-1];

[0074] ③ Clear i to zero, reorder RL[i], update the array number corresponding to the RL[i] resource, and return to step 6;

[0075] 8) End:

[0076] ① All loads were summarized, and a resource-load interconnection topology was established;

[0077] ② Automatic channel allocation, with the current number of branches being relatively advantageous in terms of feasibility and program complexity.

[0078] This invention enables automatic channel identification and intelligent channel allocation, fundamentally eliminating design omissions and errors through automatic allocation. By automatically matching loads and resources, it can greatly improve allocation design efficiency. Moreover, it can automatically obtain the lowest cable complexity matching scheme for automatic allocation, which can effectively reduce cable complexity.

[0079] In summary, the channel-based visualization application design concept and the final solution, along with the user-friendly operation and management interface and the tree-like and matrix-like formal operation windows, greatly improve the readability and ease of maintenance of channel management.

[0080] The intelligent channel allocation algorithm used in this invention cleverly utilizes and improves the bin packing algorithm, combines sorting, comparison and looping procedures, and effectively integrates with electrical design.

[0081] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatic allocation of spacecraft telemetry and remote control information channels based on a cable complexity evaluation algorithm, characterized in that... This method includes two steps: automatic channel identification and intelligent channel allocation. 1) Automatic Channel Identification: Based on the three parts of data—telemetry signal definition, remote control signal definition, and connector contact interface definition—the system obtains the correspondence between the data through "signal number." Based on the correspondence, it identifies and marks the connector's "load" or "resource" status. Then, it identifies the channel's nature and automatically classifies channels according to their nature. If the load-side contact has a clearly defined signal and return line grouping, a channel is directly generated. If the return line is not assigned, channels are assigned according to the following rules: AN / BL: 4 signals per return line; if the resource end allocates less than 4 signals, the remaining pins will be allocated as one return line. TH: One signal and one return line; Remote control channels: one return line per device; Doo: Direct access; Roo: Indirect channel; Successfully identified channels are displayed visually, including the number of various channels for all loads and resource connectors. If the number of load channels exceeds the number of resource channels, a prompt will be given. 2) Intelligent Channel Allocation: This function acquires all current resource and load channels, along with their associated electrical connectors and cables. Through automatic matching of load and resource combinations, it analyzes cable variations and automatically selects the least complex cable configuration for allocation. Specifically, it includes the following steps: Step 1: Create a table showing the resource and load characteristics of different equipment in each cabin; Step 2: Based on the keyword definition, visualize and uniformly number and display the load, resources, and channel quantity of different equipment in each cabin in a matrix, forming load groups and resource groups respectively. The objects in each group are clearly marked with cabin and equipment numbers, labeled as RmLm and RnSn. Step 3: Determine if the total number of all resource channels is greater than the total number of load channels. If the number of load channels is greater than the number of resource channels, indicate insufficient resources and please investigate. Otherwise, proceed to Step 4. Step 4: Sort the loads RLm in descending order from largest to smallest, and define them as array RL[m]. Sort the resources RSn in ascending order from smallest to largest, and define them as array RS[n]. m and n are the number of loads and resources, respectively. Step 5: After sorting, RL[0] > RL[1] > ... > RL[m-2] > RL[m-1]. RS[0] <RS[1] <… <RS[n-2]>RS[n-1], the program records each load cell. The resource number RL[m] and the resource number RS[n]; Step 6: Iterate through RL[i] (0≤i≤m-1) and RS[j] sequentially (0≤j≤m-1). (n-1) Compare the sizes; if RL[i]≤RS[n-1], proceed to step 7.1; if RL[i]>RS[n-1], proceed to step 7.

2. Step 7.1: Find the smallest value RS[j] that is greater than RL[i], and perform the following operation: 7.1.1 Establish the connection between RS[i] and RS[j]; 7.1.2, Update the resource count of RS[j] = RS[j] - RL[i]; 7.1.3 Reorder RS[j] and update the array number corresponding to the RS[j] resource. 7.1.4 After incrementing i by 1, check if i ≤ m - 1 and return to step 6. If i > m, jump to End. Step 7.2: Split the load RL[i], as follows: 7.2.1 Establish the connection between RL[i] and RS[n-1]; 7.2.2, Update the load count of RL[i] = RL[i] - RS[n-1]; 7.2.3, clear i to zero, reorder RL[i], and update the array index corresponding to the resource RL[i]. Return to step 6; End; At the end, all loads are summarized, and a resource-load interconnection topology is established; channels are automatically allocated, and the current number of branches is relatively optimal in terms of feasibility and program complexity.

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