完善耐久采集
This commit is contained in:
@ -14,7 +14,6 @@ class CurrentDataProcess(QThread):
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self.dir_path = dir_path
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self.proc = proc
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self.idx = 1
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self.logger = clibs.logger
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def initialization(self):
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_, data_files = clibs.traversal_files(self.dir_path)
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@ -30,16 +29,16 @@ class CurrentDataProcess(QThread):
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if not re.match("^j[1-7].*\\.data$", filename):
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msg = f"不合规 {data_file}<br>"
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msg += "所有数据文件必须以 j[1-7]_ 开头，以 .data 结尾，比如j1_abcdef.data，请检查整改后重新运行"
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self.logger("ERROR", "current", msg, "red")
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clibs.logger("ERROR", "current", msg, "red")
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if count != 2:
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msg = "需要有一个机型配置文件\"*.cfg\"，以及一个数据处理文件\"T_电机电流.xlsx\"表格，请检查整改后重新运行"
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self.logger("ERROR", "current", msg, "red")
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clibs.logger("ERROR", "current", msg, "red")
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return data_files, config_file
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def current_max(self, data_files, rts):
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self.logger("INFO", "current", f"正在处理最大转矩值逻辑......")
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clibs.logger("INFO", "current", f"正在处理最大转矩值逻辑......")
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current = {1: [], 2: [], 3: [], 4: [], 5: [], 6: []}
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for data_file in data_files:
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if data_file.endswith(".data"):
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@ -47,11 +46,11 @@ class CurrentDataProcess(QThread):
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else:
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continue
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self.logger("DEBUG", "current", f"正在处理 {data_file} ...")
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clibs.logger("DEBUG", "current", f"正在处理 {data_file} ...")
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cols = len(df.columns)
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axis = int(data_file.split("/")[-1].split("_")[0].removeprefix("j"))
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rt = rts[axis-1]
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self.logger("DEBUG", "current", f"最大列数为 {cols}，{axis} 轴的额定转矩为 {rt}")
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clibs.logger("DEBUG", "current", f"最大列数为 {cols}，{axis} 轴的额定转矩为 {rt}")
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col = df.columns.values[clibs.c_servo_trq-1] # 获取 "device_servo_trq_feedback"
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c_max = df[col].abs().max()
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@ -59,8 +58,8 @@ class CurrentDataProcess(QThread):
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scale = 1000
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_ = abs(c_max/scale*rt)
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current[axis].append(_)
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self.logger("DEBUG", "current", f"{data_file}: {_:.2f}")
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self.logger("DEBUG", "current", f"获取到的列名为 {col}，最大转矩为 {_}")
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clibs.logger("DEBUG", "current", f"{data_file}: {_:.2f}")
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clibs.logger("DEBUG", "current", f"获取到的列名为 {col}，最大转矩为 {_}")
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with open(data_file, "a+") as f_data:
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csv_writer = csv.writer(f_data, delimiter="\t")
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@ -73,14 +72,14 @@ class CurrentDataProcess(QThread):
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_ = ""
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for value in cur:
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_ += f"{value:.4f} "
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self.logger("INFO", "current", f"{axis}轴最大转矩数据：{_}")
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clibs.logger("INFO", "current", f"{axis}轴最大转矩数据：{_}")
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self.logger("DEBUG", "current", f"获取最大转矩值结束 current_max = {current}")
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self.logger("INFO", "current", f"最大转矩数据处理完毕......")
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clibs.logger("DEBUG", "current", f"获取最大转矩值结束 current_max = {current}")
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clibs.logger("INFO", "current", f"最大转矩数据处理完毕......")
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return current
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def current_avg(self, data_files, rts):
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self.logger("INFO", "current", f"正在处理平均转矩值逻辑......")
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clibs.logger("INFO", "current", f"正在处理平均转矩值逻辑......")
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current = {1: [], 2: [], 3: [], 4: [], 5: [], 6: []}
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for data_file in data_files:
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if data_file.endswith(".data"):
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@ -88,11 +87,11 @@ class CurrentDataProcess(QThread):
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else:
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continue
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self.logger("DEBUG", "current", f"正在处理 {data_file} ...")
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clibs.logger("DEBUG", "current", f"正在处理 {data_file} ...")
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cols = len(df.columns)
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axis = int(data_file.split("/")[-1].split("_")[0].removeprefix("j"))
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rt = rts[axis-1]
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self.logger("DEBUG", "current", f"最大列数为 {cols}，{axis} 轴的额定转矩为 {rt}")
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clibs.logger("DEBUG", "current", f"最大列数为 {cols}，{axis} 轴的额定转矩为 {rt}")
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col = df.columns.values[clibs.c_servo_trq-1]
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c_std = df[col].std()
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@ -101,8 +100,8 @@ class CurrentDataProcess(QThread):
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scale = 1000
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_ = (abs(c_avg)+c_std*3)/scale*rt
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current[axis].append(_)
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self.logger("DEBUG", "current", f"{data_file}: {_:.2f}")
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self.logger("DEBUG", "current", f"获取到的列名为 {col}，平均转矩为 {_}")
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clibs.logger("DEBUG", "current", f"{data_file}: {_:.2f}")
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clibs.logger("DEBUG", "current", f"获取到的列名为 {col}，平均转矩为 {_}")
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with open(data_file, "a+") as f_data:
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csv_writer = csv.writer(f_data, delimiter="\t")
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@ -115,10 +114,10 @@ class CurrentDataProcess(QThread):
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_ = ""
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for value in cur:
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_ += f"{value:.4f} "
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self.logger("INFO", "current", f"{axis}轴平均转矩数据：{_}")
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clibs.logger("INFO", "current", f"{axis}轴平均转矩数据：{_}")
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self.logger("DEBUG", "current", f"获取平均转矩值结束 current_avg = {current}")
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self.logger("INFO", "current", f"平均转矩数据处理完毕......")
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clibs.logger("DEBUG", "current", f"获取平均转矩值结束 current_avg = {current}")
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clibs.logger("INFO", "current", f"平均转矩数据处理完毕......")
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return current
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def current_cycle(self, data_files, rrs, rts, params):
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@ -136,11 +135,11 @@ class CurrentDataProcess(QThread):
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single.append(data_file)
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clibs.stop, filename = True, result.split("/")[-1]
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self.logger("INFO", "current", f"正在打开文件 {filename}，这可能需要一些时间......", "blue")
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clibs.logger("INFO", "current", f"正在打开文件 {filename}，这可能需要一些时间......", "blue")
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try:
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wb = openpyxl.load_workbook(result)
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except Exception as err:
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self.logger("ERROR", "current", f"{filename}文件打开失败，可能是文件已损坏，确认后重新执行！<br>{err}", "red")
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clibs.logger("ERROR", "current", f"{filename}文件打开失败，可能是文件已损坏，确认后重新执行！<br>{err}", "red")
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ws = wb["统计"]
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for idx in range(len(params)-1):
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@ -160,7 +159,7 @@ class CurrentDataProcess(QThread):
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else:
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self.p_scenario(wb, scenario, rrs, dur_time)
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self.logger("INFO", "current", f"正在保存文件 {filename}，这可能需要一些时间......", "blue")
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clibs.logger("INFO", "current", f"正在保存文件 {filename}，这可能需要一些时间......", "blue")
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wb.save(result)
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wb.close()
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@ -177,10 +176,10 @@ class CurrentDataProcess(QThread):
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# 从实际数据看，这开逻辑很小概率能触发到
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speed_avg = df.iloc[row_s-end_point*skip_scale:row_e-end_point*skip_scale].abs().mean()
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if speed_avg < threshold:
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self.logger("WARNING", "current", f"【lt】{axis} 轴第 {seq} 次查找数据可能有异常，row_s = {row_s}, row_e = {row_e}！", "purple")
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clibs.logger("WARNING", "current", f"【lt】{axis} 轴第 {seq} 次查找数据可能有异常，row_s = {row_s}, row_e = {row_e}！", "purple")
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return row_s, row_e
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else:
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self.logger("ERROR", "current", f"{data_file} 数据有误，需要检查，无法找到第 {seq} 个有效点......", "red")
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clibs.logger("ERROR", "current", f"{data_file} 数据有误，需要检查，无法找到第 {seq} 个有效点......", "red")
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elif flag == "gt":
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while row_e > end_point:
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speed_avg = df.iloc[row_s:row_e].abs().mean()
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@ -193,10 +192,10 @@ class CurrentDataProcess(QThread):
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# 从实际数据看，这开逻辑很小概率能触发到
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speed_avg = df.iloc[row_s-end_point*skip_scale:row_e-end_point*skip_scale].abs().mean()
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if speed_avg > threshold:
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self.logger("WARNING", "current", f"【gt】{axis} 轴第 {seq} 次查找数据可能有异常，row_s = {row_s}, row_e = {row_e}！", "purple")
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clibs.logger("WARNING", "current", f"【gt】{axis} 轴第 {seq} 次查找数据可能有异常，row_s = {row_s}, row_e = {row_e}！", "purple")
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return row_s, row_e
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else:
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self.logger("ERROR", "current", f"{data_file} 数据有误，需要检查，无法找到第 {seq} 个有效点......", "red")
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clibs.logger("ERROR", "current", f"{data_file} 数据有误，需要检查，无法找到第 {seq} 个有效点......", "red")
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def get_row_number(self, threshold, flag, df, row_s, row_e, axis):
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count_1, count_2 = 0, 0
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@ -220,7 +219,7 @@ class CurrentDataProcess(QThread):
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count_1 = 0
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places = {"start": "起点", "middle": "中间点", "end": "终点"} # 因为是终点数据，所以可能有异常
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self.logger("DEBUG", "current", f"{axis} 轴获取{places[flag]}数据 {row_e} 可能有异常，需关注！", "purple")
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clibs.logger("DEBUG", "current", f"{axis} 轴获取{places[flag]}数据 {row_e} 可能有异常，需关注！", "purple")
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return row_e
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def p_single(self, wb, single, rrs):
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@ -296,13 +295,13 @@ class CurrentDataProcess(QThread):
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row_s, row_e = self.find_point(data_file, df, "gt", row_s, row_e, threshold, step, end_point, skip_scale, axis, 3)
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row_start = self.get_row_number(threshold, "start", df, row_s, row_e, axis)
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self.logger("DEBUG", "current", f"{axis} 轴起点：{row_start}")
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self.logger("DEBUG", "current", f"{axis} 轴中间点：{row_middle}")
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self.logger("DEBUG", "current", f"{axis} 轴终点：{row_end}")
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self.logger("DEBUG", "current", f"{axis} 轴数据非零段点数：{row_middle-row_start+1}")
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self.logger("DEBUG", "current", f"{axis} 轴数据为零段点数：{row_end-row_middle+1}")
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clibs.logger("DEBUG", "current", f"{axis} 轴起点：{row_start}")
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clibs.logger("DEBUG", "current", f"{axis} 轴中间点：{row_middle}")
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clibs.logger("DEBUG", "current", f"{axis} 轴终点：{row_end}")
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clibs.logger("DEBUG", "current", f"{axis} 轴数据非零段点数：{row_middle-row_start+1}")
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clibs.logger("DEBUG", "current", f"{axis} 轴数据为零段点数：{row_end-row_middle+1}")
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if abs(row_end+row_start-2*row_middle) > 1000:
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self.logger("WARNING", "current", f"{axis} 轴数据占空比异常，处理数据可能有误，需检查！", "purple")
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clibs.logger("WARNING", "current", f"{axis} 轴数据占空比异常，处理数据可能有误，需检查！", "purple")
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data, first_c, second_c, third_c, fourth_c = [], clibs.c_joint_vel-1, clibs.c_servo_trq-1, clibs.c_sensor_trq-1, clibs.c_estimate_trans_trq-1
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for row in range(row_start, row_end+1):
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@ -327,7 +326,7 @@ class CurrentDataProcess(QThread):
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i += 1
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def p_scenario(self, wb, scenario, rrs, dur_time):
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self.logger("INFO", "current", f"本次处理的是电机电流场景数据，场景运动周期为 {dur_time}s", "blue")
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clibs.logger("INFO", "current", f"本次处理的是电机电流场景数据，场景运动周期为 {dur_time}s", "blue")
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for data_file in scenario:
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cycle = 0.001
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axis = int(data_file.split("/")[-1].split("_")[0].removeprefix("j"))
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@ -344,7 +343,7 @@ class CurrentDataProcess(QThread):
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row_start = 3000
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row_end = row_start + int(dur_time/cycle)
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if row_end > df.index[-1]:
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self.logger("ERROR", "current", f"位置超限：{data_file} 共有 {df.index[-1]} 条数据，无法取到第 {row_end} 条数据，需要确认场景周期时间...", "red")
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clibs.logger("ERROR", "current", f"位置超限：{data_file} 共有 {df.index[-1]} 条数据，无法取到第 {row_end} 条数据，需要确认场景周期时间...", "red")
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data, first_c, second_c, third_c, fourth_c = [], clibs.c_joint_vel-1, clibs.c_servo_trq-1, clibs.c_sensor_trq-1, clibs.c_estimate_trans_trq-1
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for row in range(row_start, row_end+1):
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@ -391,13 +390,13 @@ class CurrentDataProcess(QThread):
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r_max_t = configs["TRANSMISSION"]["MAX_PEAK_TORQUE"] # 减速器瞬时最大转矩
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r_avg_t = configs["TRANSMISSION"]["MAX_AVERAGE_TORQUE"] # 减速器平均负载转矩允许最大值
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self.logger("INFO", "current", f"get_configs: 机型文件版本 {config_file}_{version}")
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self.logger("INFO", "current", f"get_configs: 减速比 {r_rrs}")
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self.logger("INFO", "current", f"get_configs: 额定转矩 {m_rts}")
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self.logger("INFO", "current", f"get_configs: 最大角速度 {m_avs}")
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clibs.logger("INFO", "current", f"get_configs: 机型文件版本 {config_file}_{version}")
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clibs.logger("INFO", "current", f"get_configs: 减速比 {r_rrs}")
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clibs.logger("INFO", "current", f"get_configs: 额定转矩 {m_rts}")
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clibs.logger("INFO", "current", f"get_configs: 最大角速度 {m_avs}")
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return sc, r_rrs, m_avs, m_stall_ts, m_rts, m_max_ts, m_r_rpms, m_max_rpms, r_max_sst, r_max_t, r_avg_t, robot_type
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except Exception as err:
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self.logger("ERROR", "current", f"get_config: 无法打开 {config_file}，或获取配置文件参数错误 {err}", "red")
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clibs.logger("ERROR", "current", f"get_config: 无法打开 {config_file}，或获取配置文件参数错误 {err}", "red")
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def processing(self):
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time_start = time.time()
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@ -413,7 +412,7 @@ class CurrentDataProcess(QThread):
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elif self.proc == "周期":
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self.current_cycle(data_files, rrs, rts, params)
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self.logger("INFO", "current", "-"*60 + "<br>全部处理完毕<br>", "purple")
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clibs.logger("INFO", "current", "-"*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"数据处理时间：{time_total // 3600:02.0f} h {time_total % 3600 // 60:02.0f} m {time_total % 60:02.0f} s"
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self.logger("INFO", "current", msg)
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clibs.logger("INFO", "current", msg)
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