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1. [APIs: do_brake.py]

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- 修改ready_to_go信号的接收逻辑，适配大负载机型
2. [APIs: do_current.py]
   - 修改ready_to_go信号的接收逻辑，适配大负载机型
   - 调整单轴测试时间为35s，适配大负载机型，调整堵转电流持续时间15s，适当减少测试时间
   - 将act信号置为False的动作放在初始化，增加程序健壮性
   - 修改所有输出文件的命名，在扩展名之前加入时间戳
This commit is contained in:
gitea 2024-07-13 13:40:04 +08:00
parent a66a55bcd3
commit d76ee3d223
5 changed files with 20 additions and 16 deletions
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2
aio/README.md
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@ -472,4 +472,6 @@ v0.1.9.2(2024/07/13)
- 修改ready_to_go信号的接收逻辑，适配大负载机型 - 修改ready_to_go信号的接收逻辑，适配大负载机型
- 调整单轴测试时间为35s，适配大负载机型，调整堵转电流持续时间15s，适当减少测试时间 - 调整单轴测试时间为35s，适配大负载机型，调整堵转电流持续时间15s，适当减少测试时间
- 将act信号置为False的动作放在初始化，增加程序健壮性 - 将act信号置为False的动作放在初始化，增加程序健壮性
- 修改所有输出文件的命名，在扩展名之前加入时间戳
3. [current: current.py]: 在find_point函数种，当无法找到正确点位时，继续执行，而不是直接终止执行

8
aio/assets/file_version_info.txt
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@ -6,8 +6,8 @@ VSVersionInfo(
ffi=FixedFileInfo( ffi=FixedFileInfo(
# filevers and prodvers should be always a tuple with four items: (1, 2, 3, 4) # filevers and prodvers should be always a tuple with four items: (1, 2, 3, 4)
# Set not needed items to zero 0. # Set not needed items to zero 0.
filevers=(0, 1, 9, 1), filevers=(0, 1, 9, 2),
prodvers=(0, 1, 9, 1), prodvers=(0, 1, 9, 2),
# Contains a bitmask that specifies the valid bits 'flags'r # Contains a bitmask that specifies the valid bits 'flags'r
mask=0x3f, mask=0x3f,
# Contains a bitmask that specifies the Boolean attributes of the file. # Contains a bitmask that specifies the Boolean attributes of the file.
@ -31,12 +31,12 @@ VSVersionInfo(
'040904b0', '040904b0',
[StringStruct('CompanyName', 'Rokae - https://www.rokae.com/'), [StringStruct('CompanyName', 'Rokae - https://www.rokae.com/'),
StringStruct('FileDescription', 'All in one automatic toolbox'), StringStruct('FileDescription', 'All in one automatic toolbox'),
StringStruct('FileVersion', '0.1.9.1 (2024-07-12)'), StringStruct('FileVersion', '0.1.9.2 (2024-07-13)'),
StringStruct('InternalName', 'AIO.exe'), StringStruct('InternalName', 'AIO.exe'),
StringStruct('LegalCopyright', '© 2024-2024 Manford Fan'), StringStruct('LegalCopyright', '© 2024-2024 Manford Fan'),
StringStruct('OriginalFilename', 'AIO.exe'), StringStruct('OriginalFilename', 'AIO.exe'),
StringStruct('ProductName', 'AIO'), StringStruct('ProductName', 'AIO'),
StringStruct('ProductVersion', '0.1.9.1 (2024-07-12)')]) StringStruct('ProductVersion', '0.1.9.2 (2024-07-13)')])
]), ]),
VarFileInfo([VarStruct('Translation', [1033, 1200])]) VarFileInfo([VarStruct('Translation', [1033, 1200])])
] ]

2
aio/assets/vers
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@ -1 +1 @@
0.1.9.1 @ 07/12/2024 0.1.9.2 @ 07/13/2024

18
aio/code/automatic_test/do_current.py
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@ -129,7 +129,7 @@ def data_proc_regular(path, filename, channel, scenario_time):
df1 = pandas.DataFrame.from_dict(_d2d_vel) df1 = pandas.DataFrame.from_dict(_d2d_vel)
df2 = pandas.DataFrame.from_dict(_d2d_trq) df2 = pandas.DataFrame.from_dict(_d2d_trq)
df = pandas.concat([df1, df2], axis=1) df = pandas.concat([df1, df2], axis=1)
_filename = f'{path}\\single\\j{channel+1}_single.data' _filename = f'{path}\\single\\j{channel+1}_single_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
elif channel in list(range(6, 9)): elif channel in list(range(6, 9)):
with open(filename, 'r', encoding='utf-8') as f_obj: with open(filename, 'r', encoding='utf-8') as f_obj:
@ -178,37 +178,37 @@ def data_proc_regular(path, filename, channel, scenario_time):
df_01 = pandas.DataFrame.from_dict(_d2d_vel_0) df_01 = pandas.DataFrame.from_dict(_d2d_vel_0)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_0) df_02 = pandas.DataFrame.from_dict(_d2d_trq_0)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j1_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j1_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
df_01 = pandas.DataFrame.from_dict(_d2d_vel_1) df_01 = pandas.DataFrame.from_dict(_d2d_vel_1)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_1) df_02 = pandas.DataFrame.from_dict(_d2d_trq_1)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j2_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j2_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
df_01 = pandas.DataFrame.from_dict(_d2d_vel_2) df_01 = pandas.DataFrame.from_dict(_d2d_vel_2)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_2) df_02 = pandas.DataFrame.from_dict(_d2d_trq_2)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j3_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j3_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
df_01 = pandas.DataFrame.from_dict(_d2d_vel_3) df_01 = pandas.DataFrame.from_dict(_d2d_vel_3)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_3) df_02 = pandas.DataFrame.from_dict(_d2d_trq_3)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j4_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j4_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
df_01 = pandas.DataFrame.from_dict(_d2d_vel_4) df_01 = pandas.DataFrame.from_dict(_d2d_vel_4)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_4) df_02 = pandas.DataFrame.from_dict(_d2d_trq_4)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j5_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j5_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
df_01 = pandas.DataFrame.from_dict(_d2d_vel_5) df_01 = pandas.DataFrame.from_dict(_d2d_vel_5)
df_02 = pandas.DataFrame.from_dict(_d2d_trq_5) df_02 = pandas.DataFrame.from_dict(_d2d_trq_5)
df = pandas.concat([df_01, df_02], axis=1) df = pandas.concat([df_01, df_02], axis=1)
_filename = f'{path}\\s_{channel-5}\\j6_s_{channel-5}_{scenario_time}.data' _filename = f'{path}\\s_{channel-5}\\j6_s_{channel-5}_{scenario_time}_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
elif channel in list(range(9, 15)): elif channel in list(range(9, 15)):
with open(filename, 'r', encoding='utf-8') as f_obj: with open(filename, 'r', encoding='utf-8') as f_obj:
@ -227,7 +227,7 @@ def data_proc_regular(path, filename, channel, scenario_time):
df1 = pandas.DataFrame.from_dict(_d2d_vel) df1 = pandas.DataFrame.from_dict(_d2d_vel)
df2 = pandas.DataFrame.from_dict(_d2d_trq) df2 = pandas.DataFrame.from_dict(_d2d_trq)
df = pandas.concat([df1, df2], axis=1) df = pandas.concat([df1, df2], axis=1)
_filename = f'{path}\\single\\j{channel-8}_hold.data' _filename = f'{path}\\single\\j{channel-8}_hold_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)
@ -248,7 +248,7 @@ def data_proc_inertia(path, filename, channel):
df1 = pandas.DataFrame.from_dict(_d2d_vel) df1 = pandas.DataFrame.from_dict(_d2d_vel)
df2 = pandas.DataFrame.from_dict(_d2d_trq) df2 = pandas.DataFrame.from_dict(_d2d_trq)
df = pandas.concat([df1, df2], axis=1) df = pandas.concat([df1, df2], axis=1)
_filename = f'{path}\\inertia\\j{channel+4}_inertia.data' _filename = f'{path}\\inertia\\j{channel+4}_inertia_{time()}.data'
df.to_csv(_filename, sep='\t', index=False) df.to_csv(_filename, sep='\t', index=False)

6
aio/code/data_process/current.py
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@ -223,7 +223,8 @@ def find_point(data_file, pos, flag, df, _row_s, _row_e, w2t, exitcode, threshol
else: else:
return _row_s, _row_e return _row_s, _row_e
else: else:
w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, exitcode, 'red') # w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, exitcode, 'red')
w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到第{exitcode}个有效点...", 0, 0, 'red')
elif flag == 'gt': elif flag == 'gt':
while _row_e > end_point: while _row_e > end_point:
speed_avg = df.iloc[_row_s:_row_e, 0].abs().mean() speed_avg = df.iloc[_row_s:_row_e, 0].abs().mean()
@ -234,7 +235,8 @@ def find_point(data_file, pos, flag, df, _row_s, _row_e, w2t, exitcode, threshol
else: else:
return _row_s, _row_e return _row_s, _row_e
else: else:
w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到有效起始点或结束点...", 0, exitcode, 'red') # w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到有效起始点或结束点...", 0, exitcode, 'red')
w2t(f"[{pos}] {data_file}数据有误，需要检查，无法找到有效起始点或结束点...", 0, 0, 'red')
def p_single(wb, single, vel, trq, rpms, w2t): def p_single(wb, single, vel, trq, rpms, w2t):