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[国产FPGA] 新人求教静态数码管实验的代码问题

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2023-5-10
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发表于 2023-5-10 18:06:06 | 显示全部楼层 |阅读模式
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正点原子逻辑分析仪DL16劲爆上市
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发表于 2023-5-11 10:42:44 | 显示全部楼层
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 楼主| 发表于 2023-5-11 10:46:52 | 显示全部楼层
QinQZ 发表于 2023-5-11 10:42
所以你的问题是?

不好意思这个图片好像没上传成功
就是我的实验结果是数码管1和0来回亮
我的代码如下:
module time_count(
        input clk,
        input rst_n,
       
        output reg [3:0] num
);

reg [24:0] count;

always @( posedge clk or negedge rst_n)begin
    if(!rst_n)
                count <= 25'd0;
        else if(count < 25'd2500_0000-1)
                count <= count+1;
        else
                count <= 25'd0;
end

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)
                num <= 4'd0;
        else if(count == 25'd2500_0000-1)begin
            if(num<4'hf)
                        num <= num+1'b1;
                else
                        num <= 4'd0;
        end
end

endmodule



module seg_static_led(
        input clk,
        input rst_n,
        input  num,
       
        output reg [5:0] seg_sel,
        output reg [7:0] seg_led
);

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)
                seg_sel <= 6'b111111;
    else
        seg_sel <= 6'b000000;
end

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)begin
                seg_led <= 6'd0;
                seg_sel <= 8'd0;
        end
        else begin
                case(num)
                        4'h0 :    seg_led <= 8'b1100_0000;
            4'h1 :    seg_led <= 8'b1111_1001;
            4'h2 :    seg_led <= 8'b1010_0100;
            4'h3 :    seg_led <= 8'b1011_0000;
            4'h4 :    seg_led <= 8'b1001_1001;
            4'h5 :    seg_led <= 8'b1001_0010;
            4'h6 :    seg_led <= 8'b1000_0010;
            4'h7 :    seg_led <= 8'b1111_1000;
            4'h8 :    seg_led <= 8'b1000_0000;
            4'h9 :    seg_led <= 8'b1001_0000;
            4'ha :    seg_led <= 8'b1000_1000;
            4'hb :    seg_led <= 8'b1000_0011;
            4'hc :    seg_led <= 8'b1100_0110;
            4'hd :    seg_led <= 8'b1010_0001;
            4'he :    seg_led <= 8'b1000_0110;
            4'hf :    seg_led <= 8'b1000_1110;
                endcase
        end
end

endmodule




module seg_static_led_top(
        input sys_clk,
        input sys_rst_n,
       
        output    [5:0]     seg_sel,
    output    [7:0]     seg_led
);

time_count time_count_n(
        .clk         (sys_clk),
        .rst_n       (sys_rst_n),
       
        .num         (num_1)

);
seg_static_led seg_static_led_n(
        .clk         (sys_clk),
        .rst_n       (sys_rst_n),
        .num         (num_1),
       
        .seg_sel     (seg_sel),
        .seg_led     (seg_led)

);
ila_0 your_instance_name (
        .clk(sys_clk), // input wire clk


        .probe0(num) // input wire [3:0] probe0
);


endmodule

求教大佬!非常感谢!
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发表于 2023-5-11 20:04:07 | 显示全部楼层
这种一眼看代码不好找问题的话,一般借助于调试工具应该比较好找的,比如仿真或者在线调试,抓取一些关键信号看波形会更容易找到问题
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发表于 2023-5-13 14:31:38 | 显示全部楼层
module seg_led_static_top (
    input               sys_clk  ,      
    input               sys_rst_n,      

    output    [5:0]     seg_sel  ,      
    output    [7:0]     seg_led         
);

wire     num_flag;

time_count u_time_count(  

    .clk        (sys_clk  ),
    .rst_n      (sys_rst_n),
   
    .num_flag   (num_flag )
);

seg_led_static u_seg_led_static (
    .clk        (sys_clk  ),
    .rst_n      (sys_rst_n),
    .num_flag   (num_flag ),
         
    .seg_sel    (seg_sel  ),
    .seg_led    (seg_led  )
);

endmodule


module time_count(
        input clk,
        input rst_n,
      
        output reg  num_flag
);

reg [24:0] count;

always @( posedge clk or negedge rst_n)begin
    if(!rst_n)
        count <= 25'd0;
       else if(count < 25'd2500_0000-1'b1)
        count <= count+1;
       else
        count <= 25'd0;
end            
   
always @( posedge clk or negedge rst_n)begin
    if(!rst_n)
        num_flag <= 1'b0;
       else if(count == 25'd2500_0000-1'b1)
        num_flag <= 1'b1;
       else
        num_flag <= 1'b0;
end

endmodule

module seg_led_static(
        input clk,
        input rst_n,
        input  num_flag,
      
        output reg [5:0] seg_sel,
        output reg [7:0] seg_led
);

reg [3:0]  num;

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)
       num<=4'b0000;
    else if(num_flag)
       num <= num+1'b1;
         else
       num<=num;         
end

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)
       seg_sel <= 6'b111111;
    else
       seg_sel <= 6'b000000;
end

always @(posedge clk or negedge rst_n)begin
    if(!rst_n)
       seg_led <= 8'd0;
    else begin
         case(num)
            4'h0 :    seg_led <= 8'b1100_0000;
            4'h1 :    seg_led <= 8'b1111_1001;
            4'h2 :    seg_led <= 8'b1010_0100;
            4'h3 :    seg_led <= 8'b1011_0000;
            4'h4 :    seg_led <= 8'b1001_1001;
            4'h5 :    seg_led <= 8'b1001_0010;
            4'h6 :    seg_led <= 8'b1000_0010;
            4'h7 :    seg_led <= 8'b1111_1000;
            4'h8 :    seg_led <= 8'b1000_0000;
            4'h9 :    seg_led <= 8'b1001_0000;
            4'ha :    seg_led <= 8'b1000_1000;
            4'hb :    seg_led <= 8'b1000_0011;
            4'hc :    seg_led <= 8'b1100_0110;
            4'hd :    seg_led <= 8'b1010_0001;
            4'he :    seg_led <= 8'b1000_0110;
            4'hf :    seg_led <= 8'b1000_1110;
                        default :         seg_led <= 8'b1100_0000;
         endcase
     end
end
endmodule

供参考一下哈
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