diff --git a/aio/README.md b/aio/README.md index 1b75caf..1398488 100644 --- a/aio/README.md +++ b/aio/README.md @@ -8,6 +8,7 @@ 4. wavelogger 波形处理，几乎不花费时间 5. 制动自动化测试 6. 电机电流自动化测试 +7. 耐久工程曲线指标采集（仅适用于六轴） --- @@ -154,6 +155,12 @@ pyinstaller --noconfirm --onedir --windowed --add-data "C:/Users/Administrator/A 基本同第五点 +#### 7) 耐久工程曲线指标采集 + +可实现固定周期指定曲线指标的采集，用于长时间观察指标的变化情况，输入文件： +- configs.xlsx，执行之前需要手动修改好configs.xlsx中的参数，以及间隔时间 +- target.zip，需要确认工程点位和动作无问题后，保存导出 + #### 其他 customtkinter的tabview组件不支持修改字体大小，可以参考 [Changing Font of a Tabview](https://github.com/TomSchimansky/CustomTkinter/issues/2296) 进行手动修改源码实现： a. 运行 `pip show customtkinter`，获取到库的路径 diff --git a/aio/assets/configs.xlsx b/aio/assets/configs.xlsx index e59ffbb..158cdf5 100644 Binary files a/aio/assets/configs.xlsx and b/aio/assets/configs.xlsx differ diff --git a/aio/assets/templates/durable/durable_data_current.xlsx b/aio/assets/templates/durable/durable_data_current.xlsx index ece47de..edca686 100644 Binary files a/aio/assets/templates/durable/durable_data_current.xlsx and b/aio/assets/templates/durable/durable_data_current.xlsx differ diff --git a/aio/assets/templates/durable/durable_data_velocity.xlsx b/aio/assets/templates/durable/durable_data_velocity.xlsx index ece47de..7e04299 100644 Binary files a/aio/assets/templates/durable/durable_data_velocity.xlsx and b/aio/assets/templates/durable/durable_data_velocity.xlsx differ diff --git a/aio/code/durable_action/factory_test.py b/aio/code/durable_action/factory_test.py index 0833162..026baaf 100644 --- a/aio/code/durable_action/factory_test.py +++ b/aio/code/durable_action/factory_test.py @@ -3,12 +3,13 @@ from os.path import exists, dirname from os import scandir from paramiko import SSHClient, AutoAddPolicy from json import loads -from time import sleep, time +from time import sleep, time, strftime, localtime import pandas as pd from openpyxl import load_workbook from math import sqrt tab_name = 'Durable Action' +count = 0 durable_data_current_xlsx = f'{dirname(__file__)}/../../assets/templates/durable/durable_data_current.xlsx' durable_data_velocity_xlsx = f'{dirname(__file__)}/../../assets/templates/durable/durable_data_velocity.xlsx' display_pdo_params = [ @@ -170,26 +171,32 @@ def run_rl(path, config_file, hr, md, w2t): # 6. 关闭诊断曲线，停止程序运行，下电并且换成手动模式 _response = execution('diagnosis.open', hr, w2t, open=False, display_open=False) _response = execution('diagnosis.set_params', hr, w2t, display_pdo_params=[]) - _response = execution('rl_task.stop', hr, w2t, tasks=['current']) sleep(1) # 保证所有数据均已返回 # 7. 保留数据并处理输出 - get_durable_data(path, config_file, data_all, scenario_time, hr, w2t) + _wb = load_workbook(config_file, read_only=True) + _ws = _wb['Target'] + wait_time = float(_ws.cell(row=2, column=10).value) + rcs = [] + for i in range(6): + rcs.append(float(_ws.cell(row=6, column=i + 2).value)) + + get_durable_data(path, data_all, scenario_time, wait_time, rcs, hr, w2t) # 8. 继续运行 - _response = execution('rl_task.run', hr, w2t, tasks=['current']) while True: # 每3分钟，更新一次数据，打开曲线，获取周期内电流，关闭曲线 - sleep(180) + sleep(wait_time) _response = execution('diagnosis.open', hr, w2t, open=True, display_open=True) _response = execution('diagnosis.set_params', hr, w2t, display_pdo_params=display_pdo_params) - sleep(scenario_time + 10) + sleep(scenario_time+5) _response = execution('diagnosis.open', hr, w2t, open=False, display_open=False) _response = execution('diagnosis.set_params', hr, w2t, display_pdo_params=[]) + sleep(2) # 7. 保留数据并处理输出 - get_durable_data(path, config_file, data_all, scenario_time, hr, w2t) + get_durable_data(path, data_all, scenario_time, wait_time, rcs, hr, w2t) -def get_durable_data(path, config_file, data, scenario_time, hr, w2t): +def get_durable_data(path, data, scenario_time, wait_time, rcs, hr, w2t): _data_list = [] for _msg in hr.c_msg: if 'diagnosis.result' in _msg: @@ -207,12 +214,6 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t): # for _ in _data_list: # f_obj.write(f"{_}\n") - _wb = load_workbook(config_file, read_only=True) - _ws = _wb['Target'] - rcs = [] - for i in range(6): - rcs.append(float(_ws.cell(row=6, column=i + 2).value)) - _d2d_trq = { 'device_servo_trq_feedback_0': [], 'device_servo_trq_feedback_1': [], 'device_servo_trq_feedback_2': [], 'device_servo_trq_feedback_3': [], 'device_servo_trq_feedback_4': [], 'device_servo_trq_feedback_5': [], @@ -231,35 +232,35 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t): _d2d_vel[f'hw_joint_vel_feedback_{i}'].extend(item['value']) if len(_d2d_trq['device_servo_trq_feedback_0']) / 1000 > scenario_time + 1: - _df = pd.DataFrame(_d2d_trq) + # ========= for trq ========= + _df_1 = pd.DataFrame(_d2d_trq) for i in range(6): - _ = sqrt(100*_df[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}'])) + _ = sqrt(100*_df_1[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}'])) del data[0][f"axis{i + 1}"][0] data[0][f"axis{i + 1}"].append(_) - _df = pd.DataFrame(data[0]) - while True: - if not hr.durable_lock: - hr.durable_lock = 1 - _df.to_excel(durable_data_current_xlsx, index=False) - hr.durable_lock = 0 - break - else: - sleep(1) - - _df = pd.DataFrame(_d2d_vel) + _df_1 = pd.DataFrame(data[0]) + # ========= for vel ========= + _df_2 = pd.DataFrame(_d2d_vel) for i in range(6): - _ = sqrt(100*_df[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}'])) + _ = sqrt(100*_df_2[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}'])) del data[1][f"axis{i + 1}"][0] data[1][f"axis{i + 1}"].append(_) - _df = pd.DataFrame(data[1]) + _df_2 = pd.DataFrame(data[1]) + while True: if not hr.durable_lock: hr.durable_lock = 1 - _df.to_excel(durable_data_velocity_xlsx, index=False) + _df_1.to_excel(durable_data_current_xlsx, index=False) + _df_2.to_excel(durable_data_velocity_xlsx, index=False) hr.durable_lock = 0 break else: sleep(1) + global count + count += 1 + this_time = strftime("%Y-%m-%d %H:%M:%S", localtime(time())) + next_time = strftime("%Y-%m-%d %H:%M:%S", localtime(time()+wait_time+10+scenario_time)).split()[-1] + w2t(f"[{this_time}] 当前次数：{count:09d} | 预计下次数据更新时间：{next_time}", 0, 0, '#008B8B', tab_name) break else: with open(f'{path}\\device_servo_trq_feedback_0.txt', 'w', encoding='utf-8') as f_obj: