268 lines
12 KiB
Python
268 lines
12 KiB
Python
import json
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import os.path
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import threading
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import time
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import pandas
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import numpy
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import math
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import csv
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from PySide6.QtCore import Signal, QThread
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from codes.common import clibs
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class DoFactoryTest(QThread):
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curve_map = {
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"周期内平均转矩": ["device_servo_trq_feedback", ],
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"周期内最大速度": ["hw_joint_vel_feedback", ],
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}
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def __init__(self, dir_path, interval, procs, /):
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super().__init__()
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self.dir_path = dir_path
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self.interval = int(interval) if interval != "" else clibs.CYCLE
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self.procs = procs
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self.idx = 6
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self.curves = []
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def initialization(self, data_dirs, data_files):
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def check_files():
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for proc_name, is_enabled in self.procs.items():
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if is_enabled:
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self.curves.extend(self.curve_map[proc_name])
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if len(self.curves) == 0:
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clibs.logger("ERROR", "factory", "未查询到需要记录数据的曲线，至少选择一个！", "red")
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if len(data_dirs) != 0 or len(data_files) != 1:
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clibs.logger("ERROR", "factory", "初始路径下不允许有文件夹，且初始路径下只能存在一个工程文件 —— *.zip，确认后重新运行！", "red")
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if not data_files[0].endswith(".zip"):
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clibs.logger("ERROR", "factory", f"{data_files[0]} 不是一个有效的工程文件，需确认！", "red")
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return data_files[0]
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def get_configs():
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robot_type, records = None, None
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msg_id = clibs.c_hr.execution("controller.get_params")
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records = clibs.c_hr.get_from_id(msg_id)
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for record in records:
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if "请求发送成功" not in record[0]:
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robot_type = eval(record[0])["data"]["robot_type"]
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server_file = f"/home/luoshi/bin/controller/robot_cfg/{robot_type}/{robot_type}.cfg"
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local_file = self.dir_path + f"/{robot_type}.cfg"
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clibs.c_pd.pull_file_from_server(server_file, local_file)
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try:
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with open(local_file, mode="r", encoding="utf-8") as f_config:
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configs = json.load(f_config)
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except Exception as err:
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clibs.logger("ERROR", "factory", f"无法打开 {local_file}<br>{err}", "red")
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# 最大角速度，额定电流，减速比，额定转速
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version = configs["VERSION"]
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m_avs = configs["MOTION"]["JOINT_MAX_SPEED"]
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clibs.logger("INFO", "factory", f"get_configs: 机型文件版本 {robot_type}_{version}")
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clibs.logger("INFO", "factory", f"get_configs: 各关节角速度 {m_avs}")
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return m_avs
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clibs.logger("INFO", "factory", "正在做初始化校验和配置，这可能需要一点时间......", "green")
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prj_file = check_files()
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if prj_file is None:
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return
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avs = get_configs()
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params = {
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"prj_file": prj_file,
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"interval": self.interval,
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"avs": avs,
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}
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clibs.logger("INFO", "factory", "数据目录合规性检查结束，未发现问题......", "green")
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return params
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def change_curve_state(self, stat):
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display_pdo_params = [{"name": name, "channel": chl} for name in self.curves for chl in range(6)]
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clibs.c_hr.execution("diagnosis.open", open=stat, display_open=stat)
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clibs.c_hr.execution("diagnosis.set_params", display_pdo_params=display_pdo_params)
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def run_rl(self, params):
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prj_file, interval = params["prj_file"], params["interval"]
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# 1. 关闭诊断曲线，触发软急停，并解除，目的是让可能正在运行着的机器停下来，切手动模式并下电
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self.change_curve_state(False)
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clibs.c_md.r_soft_estop(0)
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clibs.c_md.r_soft_estop(1)
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clibs.c_md.r_reset_estop()
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clibs.c_md.r_clear_alarm()
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clibs.c_md.write_act(False)
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time.sleep(1) # 让曲线彻底关闭
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# 2. reload工程后，pp2main，并且自动模式和上电
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prj_name = ".".join(prj_file.split("/")[-1].split(".")[:-1])
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prj_path = f"{prj_name}/_build/{prj_name}.prj"
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clibs.c_hr.execution("overview.reload", prj_path=prj_path, tasks=["factory"])
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clibs.c_hr.execution("rl_task.pp_to_main", tasks=["factory"])
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clibs.c_hr.execution("state.switch_auto")
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clibs.c_hr.execution("state.switch_motor_on")
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# 3. 开始运行程序
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clibs.logger("INFO", "factory", f"正在采集场景工程的周期，根据周期长短，大约需要2~5分钟左右......", "blue")
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clibs.c_hr.execution("rl_task.set_run_params", loop_mode=True, override=1.0)
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clibs.c_hr.execution("rl_task.run", tasks=["factory"])
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t_start = time.time()
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while True:
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if clibs.c_md.read_ready_to_go() == 1:
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clibs.c_md.write_act(True)
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break
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else:
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if (time.time() - t_start) > 15:
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clibs.logger("ERROR", "factory", "15s 内未收到机器人的运行信号，需要确认RL程序编写正确并正常执行...", "red")
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else:
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time.sleep(clibs.INTERVAL)
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# 4. 获取初始数据，周期时间，首次的各轴平均电流值，打开诊断曲线，并执行采集
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time.sleep(clibs.INTERVAL*10) # 等待 RL 程序中 scenario_time 初始化
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t_start = time.time()
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while True:
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scenario_time = float(f"{float(clibs.c_md.read_scenario_time()):.2f}")
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if scenario_time != 0:
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clibs.logger("INFO", "factory", f"耐久工程的周期时间：{scenario_time}s | 单轮次执行时间：{scenario_time+interval}~{scenario_time*2+interval}")
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break
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else:
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time.sleep(clibs.INTERVAL)
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if (time.time() - t_start) > 900:
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clibs.logger("ERROR", "factory", f"900s内未收到耐久工程的周期时间，需要确认RL程序和工具通信交互是否正常执行（支持最长工程周期时间为300s）......", "red")
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# 6. 准备数据保存文件
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for proc_name, is_enabled in self.procs.items():
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if not is_enabled:
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continue
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with open(f"{self.dir_path}/{proc_name}.csv", mode="a+", newline="") as f_csv:
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for curve in self.curve_map[proc_name]:
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titles = [f"{curve}_{i}" for i in range(6)]
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titles.insert(0, "time")
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csv_writer = csv.writer(f_csv)
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csv_writer.writerow(titles)
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# 7. 开始采集
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count = 0
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while clibs.running[self.idx]:
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this_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time()))
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next_time_1 = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time()+scenario_time+interval+1))
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next_time_2 = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(time.time()+scenario_time+interval+1+scenario_time))
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clibs.logger("INFO", "factory", f"[{this_time}] 当前次数：{count:09d} | 预计下次数据更新时间：{next_time_1}~{next_time_2}", "#008B8B")
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count += 1
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# 固定间隔，更新一次数据，打开曲线，获取周期内电流，关闭曲线
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time.sleep(interval)
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while True:
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capture_start = clibs.c_md.read_capture_start()
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if capture_start == 1:
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break
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else:
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time.sleep(clibs.INTERVAL/10)
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self.change_curve_state(True)
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time.sleep(scenario_time)
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end_time = time.time()
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start_time = end_time - scenario_time
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self.change_curve_state(False)
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# 保留数据并处理输出
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self.gen_results(params, start_time, end_time)
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clibs.stop_flag = False
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clibs.logger("INFO", "factory", "后台数据清零完成，现在可以重新运行其他程序。", "green")
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def gen_results(self, params, start_time, end_time):
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s_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(start_time))
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e_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(end_time))
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try:
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clibs.lock.acquire(True)
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clibs.cursor.execute(f"SELECT content FROM logs WHERE timestamp BETWEEN '{s_time}' AND '{e_time}' AND content LIKE '%diagnosis.result%' ORDER BY id ASC")
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records = clibs.cursor.fetchall()
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finally:
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clibs.lock.release()
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self.data_proc(records, params)
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def data_proc(self, records, params):
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for proc_name, is_enabled in self.procs.items():
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if not is_enabled:
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continue
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if proc_name == "周期内平均转矩":
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# get_avg_trq(records, params, w2t)
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t = threading.Thread(target=self.get_avg_trq, args=(records, params, proc_name))
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t.daemon = True
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t.start()
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elif proc_name == "周期内最大速度":
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# get_joint_max_vel(records, params, w2t)
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t = threading.Thread(target=self.get_joint_max_vel, args=(records, params, proc_name))
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t.daemon = True
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t.start()
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def get_avg_trq(self, records, params, proc_name):
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t = time.strftime("%Y%m%d%H%M%S", time.localtime(time.time()))
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d_trq = {f"device_servo_trq_feedback_{axis}": [] for axis in range(6)}
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result_data, result_file = [t, ], f"device_servo_trq_feedback_{t}"
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for record in records:
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data = eval(record[0])["data"]
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for item in data:
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for axis in range(6):
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if item.get("channel", None) == axis and item.get("name", None) == "device_servo_trq_feedback":
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d_trq[f"device_servo_trq_feedback_{axis}"].extend(reversed(item["value"]))
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for axis in range(6):
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df = pandas.DataFrame.from_dict({"device_servo_trq_feedback": d_trq[f"device_servo_trq_feedback_{axis}"]})
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_ = math.sqrt(numpy.square(df[df.columns[0]].values * 1.27 / 1000).sum() / len(df))
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result_data.append(_)
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path = "/".join(params["prj_file"].split("/")[:-1])
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with open(f"{path}/{proc_name}.csv", mode="a+", newline="") as f_csv:
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csv_writer = csv.writer(f_csv)
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csv_writer.writerow(result_data)
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if not os.path.exists(f"{path}/{proc_name}/"):
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os.mkdir(f"{path}/{proc_name}/")
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df = pandas.DataFrame.from_dict(d_trq)
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df.to_csv(f"{path}/{proc_name}/{result_file}.csv", index=False)
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def get_joint_max_vel(self, records, params, proc_name):
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t = time.strftime("%Y%m%d%H%M%S", time.localtime(time.time()))
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d_vel = {f"hw_joint_vel_feedback_{axis}": [] for axis in range(6)}
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result_data, result_file = [t, ], f"hw_joint_vel_feedback_{t}"
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for record in records:
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data = eval(record[0])["data"]
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for item in data:
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for axis in range(6):
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if item.get("channel", None) == axis and item.get("name", None) == "hw_joint_vel_feedback":
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d_vel[f"hw_joint_vel_feedback_{axis}"].extend(reversed(item["value"]))
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for axis in range(6):
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df = pandas.DataFrame.from_dict({"hw_joint_vel_feedback": d_vel[f"hw_joint_vel_feedback_{axis}"]})
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_ = df.max().iloc[0]
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result_data.append(_)
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path = "/".join(params["prj_file"].split("/")[:-1])
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with open(f"{path}/{proc_name}.csv", mode="a+", newline="") as f_csv:
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csv_writer = csv.writer(f_csv)
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csv_writer.writerow(result_data)
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if not os.path.exists(f"{path}/{proc_name}/"):
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os.mkdir(f"{path}/{proc_name}/")
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df = pandas.DataFrame.from_dict(d_vel)
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df.to_csv(f"{path}/{proc_name}/{result_file}.csv", index=False)
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def processing(self):
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time_start = time.time()
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clibs.running[self.idx] = 1
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if clibs.status["hmi"] != 1 or clibs.status["md"] != 1:
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clibs.logger("ERROR", "factory", "processing: 需要在网络设置中连接HMI以及Modbus通信！", "red")
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data_dirs, data_files = clibs.traversal_files(self.dir_path)
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params = self.initialization(data_dirs, data_files)
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clibs.c_pd.push_prj_to_server(params["prj_file"])
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self.run_rl(params)
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clibs.logger("INFO", "factory", "-"*60 + "<br>全部处理完毕<br>", "purple")
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time_total = time.time() - time_start
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msg = f"处理时间：{time_total // 3600:02.0f} h {time_total % 3600 // 60:02.0f} m {time_total % 60:02.0f} s"
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clibs.logger("INFO", "factory", msg)
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